Beta-lactam plus macrolide treatment versus beta-lactam monotherapy for community-acquired pneumonia: a propensity score analysis using data from a multicenter prospective cohort study

Beta-lactam plus macrolide treatment versus beta-lactam monotherapy for community-acquired pneumonia: a propensity score analysis using data from a multicenter prospective cohort study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Beta-lactam plus macrolide treatment versus beta-lactam monotherapy for community-acquired pneumonia: a propensity score analysis using data from a multicenter prospective cohort study Kei Nakashima, Masahiro Aoshima, Hiroki Matusi, Atsushi Shiraishi, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5738269/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Dec, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted 11 You are reading this latest preprint version Abstract Background Community-acquired pneumonia (CAP) substantially contributes to mortality and morbidity globally, with beta-lactams being a primary therapeutic agent. The efficacy of adding macrolides to beta-lactams in CAP treatment remains controversial. Here, we evaluated whether beta-lactam plus macrolide treatment (BLM) is more effective than beta-lactam monotherapy (BL) for preventing CAP mortality. Methods We performed a secondary data analysis of a multicenter prospective cohort study involving patients diagnosed with CAP at four institutions. We selected patients treated with either BLM or BL. The primary endpoint was the outcome at the end of the observation period (death or recovery). The secondary endpoints were the length of hospital stay and duration of antibiotic use. Multiple imputations with bootstrapping were used to address missing data. Background characteristics were adjusted via propensity score matching. Results Of the 3,470 patients initially included in the study, 2,784 were analyzed; 306 received BLM and 2,478 received BL. The average observation period for the groups was 17.0 (± 18.4) and 24.0 days (± 24.6), respectively. After propensity score matching, mortality was similar between the groups (5.06% for BLM vs. 4.98% for BL; difference 0.00, 95% confidence interval [CI] − 3.73 to 3.71), as were recovery rates (91.79% for BLM vs. 91.69% for BL; difference 0.00, 95% CI − 4.48 to 4.82). In the subgroup analysis of patients with severe CAP, mortality was 12.00% for BLM vs. 13.33% for BL (difference 0.00, 95% CI − 20.00 to 16.13), and recovery rates were 82.86% vs. 83.33% (difference 0.00, 95% CI − 20.00 to 20.00). Conclusion Similar outcomes were observed in the mortality and recovery rates between the BLM and BL groups among patients with CAP. Clinicians should thoughtfully weigh the benefits of BLM against the potential risks, including adverse effects and antimicrobial resistance, when managing patients with CAP. Trial registration: This study protocol was registered with the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR), identifier UMIN000006909, on December 19, 2011. Anti-Bacterial Agents beta-Lactams Macrolides Pneumonia Propensity score Figures Figure 1 Figure 2 Introduction Community-acquired pneumonia (CAP) represents the most prevalent infectious cause of mortality globally, accounting for 2.6 million deaths per year, according to the report of World Health Organization [ 1 ]. CAP is associated with a 30-day all-cause risk-standardized mortality rate of 11.6% and readmission rate of 18.2% [ 2 ]. Beta-lactams, which primarily target bacterial pathogens such as Streptococcus pneumoniae , represent the principal therapeutic agents for CAP [ 3 ]. In empirical therapy for hospitalized patients or patients with comorbidities, macrolides are generally added to beta-lactams to treat infections of atypical pathogens, particularly severe CAP [ 3 , 4 ]. The efficacy of adding macrolides to beta-lactams in reducing mortality in the treatment of CAP remains controversial [ 5 , 6 ]. Several prospective and retrospective observational studies have reported that dual therapy involving beta-lactam plus macrolide treatment (BLM) reduces the 30-day and in-hospital mortality of hospitalized patients with CAP, particularly in those with severe disease [ 5 , 7 – 9 ]. In contrast, data from randomized controlled trials (RCTs) have not shown a mortality benefit despite showing an improvement in early clinical response [ 10 , 11 ]. An RCT demonstrated that patients in the BLM group exhibited a more favorable trend towards achieving clinical stability after 7 days of treatment than those in the beta-lactam monotherapy (BL) group. However, there were no differences in the 30- and 90-d mortality rates between the BLM and BL groups [ 11 ]. Moreover, a cluster RCT found that BL was not inferior to BLM for the treatment of CAP in patients admitted to non-ICU wards in terms of 90-d mortality [ 12 ]. Furthermore, a recent network meta-analysis of RCTs found no significant difference in efficacy between BLM and BL for CAP treatment [ 13 ]. Moreover, a recent RCT of patients with CAP and systemic inflammatory response syndrome showed that, compared with BL, BLM improved the early clinical response, but the 28- and 90-day mortality rates did not differ between the treatment groups [ 10 ]. Further contributing to this debate, a recent (2025) large, real-world observational study from the United Kingdom found that BLM was not associated with a reduction in mortality, even in patients with severe pneumonia [ 14 ]. This finding is consistent with the results from previous RCTs. The persistent controversy highlights an urgent need for additional high-quality, real-world evidence. Such evidence is crucial for inclusion in future meta-analyses to definitively resolve these clinical uncertainties [ 15 ]. Therefore, our objective was to assess the effectiveness of BLM compared with BL in reducing mortality across the entire spectrum of CAP, using data from a multicenter prospective cohort study with propensity score matching to control for differences in baseline patient characteristics between groups. Methods Study setting and population We performed a secondary analysis of data from a multicenter prospective cohort study of patients with CAP collected by the Adult Pneumonia Study Group-Japan (APSG-J), utilizing propensity score analysis. The APSG-J study prospectively collected data on patients diagnosed with CAP from both outpatient and inpatient services at Ebetsu City Hospital, Kameda Medical Center, Chikamori Hospital, and Juzenkai Hospital between September 2011 and September 2014 [ 16 ]. CAP was diagnosed when all the following criteria were met: patients 1) aged ≥ 15 years, 2) exhibited symptoms compatible with pneumonia, such as fever, cough, sputum production, pleuritic chest pain, and dyspnea; and 3) displayed new pulmonary infiltrates on chest X-ray images or CT scans consistent with pneumonia. Our analysis included all participants enrolled in APSG-J. Chest X-rays were performed within 24 hours of admission, while CT scans were performed at the discretion of the attending physicians. The exclusion criteria were as follows: 1) patients did not receive antimicrobial agents; 2) patients who were initially treated solely with macrolides; and 3) patients who were initially treated with antibiotics other than beta-lactams or macrolides, as well as those who received antifungal agents, antituberculosis drugs, or antiviral agents. To specifically measure the effect of BLM compared to BL, we excluded patients receiving macrolide monotherapy or antimicrobial agents other than those in the two classes of interest. The study was conducted in accordance with the Guideline for Ethical Aspects in Epidemiological Study (Ministry of Health, Labour and Welfare, Japan 2008). This study received approval from the review board of the Institute of Tropical Medicine at Nagasaki University and the review boards of Ebetsu City Hospital, Kameda Medical Center, Chikamori Hospital, and Juzenkai Hospital (registration no. 11063070). We obtained written informed consent from all conscious patients. Given that the study was observational and involved no invasive interventions or deviations from standard medical treatment, all the institutional review boards waived the requirement for written informed consent for a few unconscious patients. The study was registered with the University Hospital Medical Information Network (UMIN000006909). Treatment group definitions Patients were categorized into two groups based on the initial treatment received: those who were started on a combination of beta-lactam and macrolide treatment (BLM group) and those treated with beta-lactam alone (BL group). Specifically, inclusion in the BLM group required that the patient received at least one dose of a macrolide antibiotic in conjunction with beta-lactam therapy. Although antibiotic dosing generally followed standard reference guidelines [ 17 ], the specific dosage regimens were determined by the attending physicians at each institution without standardization across study sites. The classification into these treatment groups occurred at the time of CAP diagnosis, and the observation period for outcomes commenced immediately thereafter. Outcome measures The primary endpoint was the outcome at the end of the observation period (death or recovery). The end of the observation period was defined according to the patient's clinical course. For hospitalized patients, follow-up was completed at the time of discharge. For patients whose pneumonia improved and were followed as outpatients, the date of the final outpatient visit related to CAP was considered the end of the observation period. If the final clinical outcome was unknown—such as in cases in which outpatient follow-up ended due to transfer to another hospital—follow-up was censored on the date of the most recent clinic visit. The outcomes were recorded at the end of the observation period, and included recovery, stable condition, deterioration, death, and transfer to another hospital. Death was defined as an in-hospital death from any cause. The secondary endpoints were the length of hospital stay and duration of antibiotic use. Microbiological test Good quality sputum and blood specimens were collected on admission. If patients were unable to expectorate sputum, it was induced by inhalation of hypertonic saline soon after admission, and sputum was collected before antibiotic administration. Upon arrival at each hospital's laboratory, clinical specimens were promptly processed. All sputum samples were subjected to semi-quantitative or quantitative cultures. In addition, these samples were analyzed at the Institute of Tropical Medicine, Nagasaki University, using in-house multiplex polymerase chain reaction (PCR) to detect a panel of bacterial and viral pathogens. This panel included three typical bacteria ( Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis ), three atypical bacteria (Mycoplasma pneumoniae, Chlamydophila pneumoniae, and Legionella pneumophila ), and 13 viruses (influenza A and B, respiratory syncytial virus, human metapneumovirus, parainfluenza virus types 1–4, rhinovirus, coronavirus 229E/OC43, adenovirus, and bocavirus). The specific primers and PCR protocols used have been detailed in previous studies [ 18 , 19 ]. Commercial kits (Binax NOW; Alere Inc.) were also used to conduct urinary antigen tests for Streptococcus pneumoniae and Legionella pneumophila . Data collection The APSG-J study prospectively collected the following clinical information: age, sex, registered hospital, treatment setting (outpatient or inpatient), history of hospitalization (hospitalization for more than 2 days within 3 months before CAP diagnosis), residing in a nursing home or convalescent facility, dialysis (within 30 days), preexisting comorbidities (diabetes, heart failure, liver disease, renal disease, dementia, malignancy, asthma, and chronic respiratory disease [chronic obstructive pulmonary disease and bronchiectasis]), prescribed drugs before admission (oral steroids, antacids, and sleep-inducing drugs), aspiration-associated factors (aspiration episodes, impaired consciousness, neuromuscular disease, insertion or placement of devices (e.g., nasogastric tubes), cerebrovascular disease, and long-term bedridden status), vital signs at diagnosis (consciousness, heart rate, respiratory rate, systolic blood pressure, and body temperature), laboratory data at diagnosis (hematocrit, blood urea nitrogen, sodium, glucose, and albumin levels), chest X-ray findings (pleural effusion), microbiological test findings (culture, urinary antigen, and polymerase chain reaction [PCR] analysis), administered antibiotics, outcome at the end of the observation period, length of hospital stay, and duration of antibiotic use. Statistical analysis Owing to the observational nature of this study, we used the available number of cases and did not perform any sample size calculations [ 15 ]. All statistical analyses were performed in R 4.3.0 for statistical computing ( https://www.r-project.org/ ), with the add-on packages “tableone” for creating tables [ 20 ], “mice” for multiple imputation [ 21 ], “MatchIt” for propensity score matching [ 22 ], and “cmprsk” for survival analysis [ 23 , 24 ]. All tests were two-tailed, and differences were considered statistically significant at p < 0.05. As there were several missing values, we used multiple imputation by employing chained equations to complement all missing values in the study variables and generated 50 datasets with five iterations. To calculate the 95% confidence interval (CI), we employed the bootstrap method described by Schomaker and Heumann to appropriately integrate uncertainty from both multiple imputation and resampling [ 25 ]. Specifically, we used "Method 1: MI Boot (pooled sample [PS])" from their study. Following this procedure, we generated 1000 bootstrap samples for each of the 50 imputed datasets. The estimates from all resulting samples were then pooled into a single distribution, and the lower and upper limit of the 95% CI was defined by the 2.5th and 97.5th percentiles of this pooled distribution. In addition, we conducted a sensitivity analysis by excluding all cases with missing data prior to imputation. After performing multiple imputations, no missing values remained, and the subsequent propensity score-matched analysis (described below) was conducted including all the relevant variables. Propensity score matching A logistic regression analysis was used to estimate the propensity score to predict the use of BLM rather than BL from 34 pretreatment covariates, including age, sex, treatment setting (outpatient or inpatient), history of hospitalization (hospitalization for more than 2 days within 3 months before the diagnosis of CAP), residing in a nursing home or convalescent facility, dialysis (within 30 d before diagnosis), preexisting comorbidities (diabetes, heart failure, liver disease, renal disease, dementia, malignancy, asthma, and chronic respiratory disease [chronic obstructive pulmonary disease and bronchiectasis]), prescribed drugs before admission (oral steroids, antacid, and sleeping drugs), aspiration-associated factors (aspiration episodes, impaired consciousness, neuromuscular disease, insertion or placement of devices (e.g., nasogastric tubes), cerebrovascular disease, and long-term bedridden status), vital signs at diagnosis (consciousness, heart rate, respiratory rate, systolic blood pressure, and body temperature), laboratory data at diagnosis (hematocrit, blood urea nitrogen, sodium, glucose, and albumin), and findings of chest X-ray (pleural effusion). We selected these as covariates because they are risk factors for antibiotic-resistant bacteria, prognostic factors, and risk factors for aspiration pneumonia [ 3 , 26 – 28 ]. Propensity score matching selected participants pairwise on a 1:1 basis after all propensity scores across the imputed datasets were averaged and logit-transformed. The match caliper was set to standard deviation of the propensity score multiplied by 0.05. We used standardized mean differences (SMDs) of all variables included in the propensity score estimation to assess the match balance, and SMDs of < 0.1 were defined as appropriate match balance [ 29 ]. Primary and secondary analyses The primary endpoints were assessed by frequency in each group and absolute difference between the groups. The secondary endpoints were validated as continuous variables and absolute differences between the groups. A cumulative incidence curve of the primary endpoints (death or recovery) of patients was generated from one of the datasets after imputing missing values from the original dataset using multiple imputation [ 21 ]. To assess the efficacy of BLM in severe CAP treatment, a subgroup analysis was conducted on patients with a CURB-65 score of 3 or higher [ 30 ]. In addition, based on previous reports suggesting that BLM may be effective in treating pneumococcal and bacteremic pneumonia [ 31 , 32 ], we conducted an exploratory subgroup analysis limited to patients with microbiologically confirmed non-atypical bacterial pneumonia. Microbiologically confirmed non-atypical bacterial pneumonia was defined by the presence of at least one of the following criteria: (1) a positive blood culture for a bacterial pathogen (excluding atypical pathogens) that could be the causative organism of pneumonia; (2) pleural fluid cultures yielding a bacterial pathogen other than atypical pathogens; or (3) a high-quality sputum sample (> 25 polymorphonuclear cells and < 10 epithelial cells per low-power field [total magnification ×100]) showing predominant growth of non-atypical bacterial pathogens in culture at ≥ 1 × 10⁶ CFU/mL, or a semiquantitative culture score of 3+; or (4) a positive pneumococcal urinary antigen test based on definitions used in previous studies [ 33 , 34 ]. Sensitivity Analysis To assess possible biases associated with multiple imputations, the primary outcome was reassessed using propensity score-matched analysis with the original dataset. In addition, we conducted a sensitivity analysis using a narrower caliper width of 0.01 for matching. Results A flowchart of the patient selection process is shown in Figure 1. Of the 3470 enrollees in the APSG-J study, 686 individuals were excluded. Subsequently, data of 2784 patients treated with BLM (306 patients) or BL (2478 patients) were analyzed. Table 1 shows the pretreatment variables of patients with CAP in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching. SMDs 0.1 indicated balanced and unbalanced patient characteristics between groups, respectively. Before matching, the average observation periods for the two groups were 17.0 (±18.4) days and 24.0 (±24.6) days, respectively. The mean age of the patients was 64.51 years (±20.63) in the BLM group and 76.04 (±15.08) years in the BL group, indicating that the patients in the BL group were older. Notably, 90% of the patients in the BLM group were enrolled at Kameda Medical Center. The most common comorbidities included diabetes mellitus, malignancy, and chronic obstructive pulmonary disease or bronchiectasis. Oral corticosteroid use was observed in 8.6% of the patients in the overall cohort. A history of aspiration was noted in 12.5% of patients in the BLM group and 28.6% of patients in the BL group, with a higher frequency in the latter group. Similarly, cerebrovascular disease was more prevalent in the BL group. Patients with a CURB-65 score of ≥3 were also more common in the BL group. After propensity score matching, 34 covariates were adjusted. Among these, 29 variables achieved an SMD of <0.1, indicating balance, except for female sex, sleep-inducing drugs, impaired consciousness, systemic blood pressure, and pleural effusion on chest X-ray. Table 2 shows the microbiological characteristics in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching. Before matching, the most commonly identified bacteria in sputum cultures were Streptococcus pneumoniae , Haemophilus influenzae , methicillin-sensitive Staphylococcus aureus , Pseudomonas aeruginosa , Moraxella catarrhalis , and Klebsiella pneumoniae . Among the entire pre-matching cohort, Mycoplasma pneumoniae was the most commonly identified atypical pathogen (1.9%), followed by Chlamydia pneumoniae (0.2%). Among the urinary antigen tests, Streptococcus pneumoniae and Legionella pneumophila were positive in 9.2% and 0.1% (3 cases), respectively. The most frequently detected viruses on PCR testing of sputum samples, in descending order of prevalence were human rhinovirus, respiratory syncytial virus, influenza A virus, human parainfluenza virus type 3, and human metapneumovirus. After matching, bacterial pathogens, such as Streptococcus pneumoniae , Haemophilus influenzae , Moraxella catarrhalis , Pseudomonas aeruginosa , and Escherichia coli , were more frequently isolated in the BL group than in the BLM group. However, the number of patients with a positive pneumococcal urinary antigen test result was higher in the BLM group. Positive blood cultures were also more common in the BLM group. As for atypical pathogens, Mycoplasma pneumoniae PCR positivity was more frequent in the BLM group, and one patient in the BLM group tested positive for L. pneumophila on the urinary antigen test. Table 3 lists the antibiotics used by study participants in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching. Before matching, the most commonly used β-lactam antibiotics were, in descending order of frequency, ceftriaxone, ampicillin-sulbactam, piperacillin-tazobactam, amoxicillin, and amoxicillin-clavulanate. Azithromycin accounted for almost all macrolide use. After matching, ceftriaxone and piperacillin-tazobactam were more frequently used in the BLM group than in the BL group, whereas ampicillin-sulbactam was more frequently used in the BL group. Table4 presents the results for the primary and secondary endpoints. Regarding the primary endpoints, the death rate was 5.06% (95% CI 2.73%–7.78%) in the BLM group and 4.98% (95% CI 2.36%–8.21%) in the BL group. The absolute difference was 0.00% (95% CI −3.73% to 3.71%). Similarly, the recovery rate was 91.79% (95% CI 88.43%–94.77%) in the BLM group and 91.69% (95% CI 87.73%–95.10%) in the BL group, with an absolute difference of 0.00% (95% CI −4.48% to 4.82%). For the secondary endpoints, the length of hospital stay and duration of antibiotic treatment were similar between groups. Figure 2 shows the cumulative incidence curve of the primary endpoints (death or recovery) of patients, generated using one of the datasets in which missing values in the original dataset were replaced with values imputed using multiple imputation. Supplementary Table S1 presents the pretreatment variables of patients CAP in the subgroup with a CURB-65 score of 3 or higher from one of the bootstrapped imputed datasets, before and after propensity score matching. Despite a decrease in the number of cases and not all variables reaching SMD < 0.1, a statistical balance was attained for 18 of the 34 pretreatment covariates attempted to adjust, showing SMDs < 0.1, after matching. The results of the primary and secondary endpoint analyses are displayed in Table 5. No difference was observed in the death or recovery rates. Furthermore, the duration of antibiotic treatment and the length of hospital stay did not differ between the groups. Supplementary Table S2 shows the pretreatment variables of patients with CAP in the subgroup with microbiologically confirmed non-atypical bacterial pneumonia, using one of the bootstrapped imputed datasets, before and after propensity score matching. Although the number of cases decreased, 27 patients in each group were successfully matched. Supplementary Table S3 presents the primary and secondary endpoints of this subgroup. No differences were observed between the two groups in either primary or secondary outcomes. For the sensitivity analysis, we performed a complete case analysis. Supplementary Table S4 presents presents the pretreatment variables of patients with CAP in the original dataset including only complete cases with no missing values, before and after propensity score matching. In the complete case cohort, the proportion of outpatients was lower than that in the imputed datasets used in the primary analysis (236/1628 [14.5%] vs. 576/2784 [20.7%] before matching; 60/262 [22.9%] vs. 244/596 [40.9%] after matching). Supplementary Table S5 shows the primary and secondary endpoints. After matching, a balance was achieved between the groups for 25 of the 34 variables attempted for adjustment, with SMD < 0.1. The study outcomes were consistent with no differences in the primary endpoints of mortality and recovery rates. Similarly, no differences were observed in the secondary endpoints, namely, duration of antibiotic treatment and length of hospital stay. As an additional sensitivity analysis, we performed propensity score matching using a caliper width of 0.01. Supplementary Table S6 shows the pretreatment variables of patients with CAP in one of the datasets generated through bootstrapping of the imputed datasets, before and after matching using a caliper width of 0.01. Supplementary Table S7 shows the results for the primary and secondary endpoints. Consistent with the results of the main analysis, no differences were observed between the BLM and BL groups for any endpoint. Discussion In this study, we compared the mortality and recovery rates between the BLM and BL groups in patients with CAP. Our findings indicated that the primary endpoints did not differ between the two treatments. Analysis of patients with a CURB-65 score of 3–5 showed that mortality and recovery rates were similar between the BLM and BL groups. A subgroup analysis limited to cases of microbiologically confirmed non-atypical bacterial CAP also revealed no differences between BLM and BL. Sensitivity analysis using complete case data and a narrower caliper of 0.01 showed no differences between the treatments. The relevance of incorporating a macrolide with a beta-lactam in the management of CAP remains a contentious issue [ 5 , 6 ]. Discordance is also observed among national guidelines. The American Thoracic Society and Infectious Diseases Society of America guidelines recommend the administration of beta-lactams and macrolides to outpatients with underlying diseases or to hospitalized patients [ 3 ]. Conversely, the United Kingdom and Japanese guidelines suggest prescribing beta-lactams and macrolides to patients with moderately severe CAP when atypical pathogens are suspected [ 4 , 35 ]. For severe CAP, all guidelines advocate the use of beta-lactams and macrolides [ 3 , 4 , 35 ]. In this study, we did not detect an additional benefit of macrolides in the overall analysis or the subgroup analysis limited to cases with a CURB-65 of 3 or higher. Several previous observational studies—particularly those focusing on severe pneumonia—have reported that BLM therapy reduces mortality in patients with CAP, and these reports have served as a basis for the recommendations contained in the current guidelines [ 5 , 7 – 9 ]. In contrast, several RCTs have not shown a mortality benefit of BLM therapy compared with BL therapy [ 10 – 12 ]. Two RCTs published in 2014 and 2015 did not demonstrate the superiority of BLM over BL in reducing mortality in the treatment of CAP [ 11 , 12 ]. More recently, a 2024 RCT that examined patients with CAP along with systemic inflammatory response syndrome found that BLM enhanced the initial clinical response compared with BL [ 10 ]. However, it revealed no difference in mortality at both 28 and 90 days following treatment between the groups. The discrepancy between findings from observational studies and RCTs may be attributable to several factors, including unmeasured confounding in observational data, differences in patient characteristics, or variation in circulating pathogens across geographic regions [ 14 ]. Additionally, the lack of significant differences in mortality between groups in some RCTs may be attributable to insufficient statistical power due to limited sample sizes. [ 10 ]. A recent large-scale observational study from the United Kingdom published in 2025, that used real-world data and adjusted for a broad range of patient characteristics and disease severity factors that could influence treatment selection [ 14 ]. Our study showed similar mortality outcomes between the BLM and BL groups, consistent with the results of the United Kingdom study and those of RCTs [ 10 – 12 , 14 ]. Macrolide therapy is associated with an increased risk of cardiovascular events and death [ 36 , 37 ]. Macrolide combination regimens are effective in patients without cardiovascular diseases or patients with respiratory diseases and high leukocyte counts in the respiratory secretion [ 38 ]. Excessive use of macrolides is also a cause for concerns such as increasing emergence of macrolide-resistant bacteria [ 39 ]. The global importance of antimicrobial stewardship has been increasingly recognized. Avoiding unnecessary macrolide use is important from an antimicrobial stewardship perspective [ 40 ]. Therefore, healthcare professionals should understand both the advantages and disadvantages of macrolide use; make prescribing decisions accordingly, based on local epidemiological data and antibiogram profiles; and exercise caution when using macrolides in combination with beta-lactams for treating CAP. Several potential mechanisms may account for the lack of an add-on effect of macrolides for reducing mortality in this study. First, the very low incidence of atypical pathogens in our cohort—including Legionella pneumophila (0.1%), Mycoplasma pneumoniae (1.9%), and Chlamydia pneumoniae (0.2%)—is likely to have attenuated any survival advantage conferred by empiric macrolide therapy. In previous observational studies reporting the effectiveness of BLM therapy, the proportion of Mycoplasma pneumoniae in the cohort was 2.8% [ 41 ], while the proportion of Legionella species ranged from 2.9–3.0% [ 41 , 42 ]. A 2012 Cochrane review showed that broad atypical coverage (predominantly fluoroquinolone monotherapy) did not improve overall survival or clinical success in patients hospitalized for CAP, although clinical success was significantly higher in the subset with Legionella pneumophila infection [ 43 ]. In Japan, fluoroquinolones are often prescribed as soon as Legionella pneumophila is detected by urinary antigen testing; thereby limiting the number of cases of Legionella pneumophila infection available for inclusion in our study dataset. Second, previous observational studies showing the efficacy of BLM compared with BL may have been unadjusted for unknown confounding factors. A meta-analysis of RCTs in which the effects of unknown confounders were removed found no advantage of BLM over BL in terms of mortality [ 13 ]. In this study, after imputing missing values by employing multiple imputations followed by bootstrapping, we attempted to adjust 34 variables related to patient outcomes and treatment factors, including risk factors for antimicrobial resistance, prognosis, and aspiration-associated risk. We believe that we adjusted the covariates as much as possible. Third, the inclusion of cases of macrolide-resistant Streptococcus pneumoniae or Mycoplasma pneumoniae infection may have attenuated the effectiveness of BLM therapy. During the study period (2011–2014), many cases of macrolide-resistant Streptococcus pneumoniae and Mycoplasma. pneumoniae were reported in Japan [ 44 – 48 ]. Resistance mechanisms in Streptococcus pneumoniae include the presence of the mef gene, which promotes efflux of the antibiotic, and the ermB gene, which alters the antibiotic target site [ 47 ]. In Mycoplasma pneumoniae , macrolide resistance is primarily caused by point mutations in the ribosomal genes that encode the drug’s binding site [ 48 ]. These resistance patterns could have diminished the clinical effectiveness of the BLM regimen. A strength of this study is that it used a multicenter prospective cohort with a large number of patients in a real-world setting. In addition to the overall analysis, we performed subgroup analysis for CAP patients with CURB-65 score ≥ 3 and conducted a complete case sensitivity analysis. Across all analyses, similar results were observed in the primary outcomes between the BLM and BL groups. Future research should focus on specific patient subgroups, in which BLM therapy may be effective in reducing mortality. In our exploratory subgroup analysis of patients with microbiologically confirmed non-atypical bacterial pneumonia, mortality did not differ between the BLM and BL. However, this finding is inconclusive owing to the limited sample size. Previous studies have suggested that macrolides may exert beneficial anti-inflammatory and immunomodulatory effects [ 10 ], particularly in patients with systemic inflammatory responses or elevated inflammatory markers such as C-reactive protein or procalcitonin [ 10 , 32 ]. Moreover, macrolides have been shown to be effective in patients with pneumococcal pneumonia and pneumonia with bacteremia [ 31 , 32 ], highlighting the need to further investigate the potential benefit of macrolides in specific microbiologically defined subpopulations. As previously mentioned, underlying comorbidities—such as the presence or absence of cardiovascular or respiratory diseases—may also influence the effectiveness of BLM [ 38 ]. Therefore, further studies focusing on identifying specific subgroups based on inflammatory markers, microbiological findings, and underlying comorbidities are warranted. Clarifying these factors may contribute to the advancement of personalized treatment strategies for CAP. Until specific patient populations in which macrolides are effective are clearly established, the use of BLM should be limited to cases in which the use of BLM is recommended by current guidelines, such as patients with severe pneumonia or hospitalized patients, particularly those in whom atypical pathogens are suspected [ 3 , 4 , 35 ]. This study has several limitations. First, as an observational study, the potential for residual confounding from unmeasured variables remains despite the use of propensity score analysis, in contrast to RCTs. This concern is underscored by the fact that several variables did not achieve a SMD of less than 0.1 in the main analysis. Furthermore, in the subset analysis of severely ill patients with a CURB-65 score of 3 or above, indicative of higher risk, we could successfully adjust only approximately half of the 34 variables owing to the limited number of qualifying cases. Second, the study may have been underpowered to exclude a clinically meaningful difference between the treatment groups, partly because of the lack of a priori sample size calculation and a low overall mortality rate (< 5%). This is highlighted in our primary analysis, where the 95% CI for the absolute difference in mortality (− 3.73–3.71%) crossed the 3% non-inferiority margin often considered clinically significant in trials of CAP [ 12 , 49 ]. Thus, a modest, but clinically relevant, treatment effect cannot be ruled out. Nevertheless, publishing these findings is essential, as they will contribute valuable real-world evidence for inclusion in future meta-analyses, which can lead to more robust and precise conclusions [ 15 ]. Third, the generalizability of the findings may be limited. The study was conducted at four specific hospitals in Japan, with the majority of cases from a single center (Kameda Medical Center, as shown in Table 1 ), which could introduce bias from unmeasured institutional-level factors (e.g., patient management protocols). Moreover, a substantial number of patients (686 of 3,470) were excluded because they received other treatments, potentially creating a selection bias and limiting the applicability of our results to a broader patient population. Fourth, the observation period was relatively short, allowing only short-term outcomes to be assessed. Consequently, long-term endpoints, such as 90-day mortality, could not be evaluated. Fifth, data on antimicrobial susceptibility were not collected. Given the high prevalence of macrolide-resistant Streptococcus pneumoniae and Mycoplasma pneumoniae in the region [ 45 – 48 ], the inability to assess the impact of resistance patterns on treatment effectiveness is a significant limitation. Given these limitations, our results should be interpreted with caution. Conclusions In this study, similar outcomes were observed in the mortality and recovery rates between the BLM and BL groups among patients with CAP, both in the overall population and in patients with a CURB-65 score of 3 or higher. Clinicians should thoughtfully weigh the benefits of BLM against the potential risks, including adverse effects and antimicrobial resistance, when managing patients with CAP. Further large-scale prospective studies are warranted to generate a hypothesis regarding whether BLM is superior in patients with certain baseline characteristics in terms of reducing mortality and to test it through an RCT. Declarations Ethics approval and consent to participate: The study received approval from the ethics review boards of the Institute of Tropical Medicine at Nagasaki University, Ebetsu City Hospital, Kameda Medical Center, Chikamori Hospital, and Juzenkai Hospital (registration no. 11063070). This study was conducted in accordance with the principles outlined in the Declaration of Helsinki. We obtained written informed consent from all conscious patients. In the cases of adults with cognitive decline, a legal guardian or an appropriate representative of these participants provided informed consent on their behalf. Given that the study was observational and involved no invasive interventions or deviations from standard medical treatment, all the institutional review boards waived the requirement for written informed consent for a few unconscious patients. Consent for publication : Not applicable Availability of data and materials Data pertaining to this study will be available by the corresponding author upon reasonable request. Competing interests: K.M. received research funding support from Pfizer. K.M. and K.A. received collaborative research funding from Pfizer. Funding: The Department of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University received financial support from Pfizer for this study. The funding source played no role in study design, or data collection, analysis, or interpretation. Author Contributions Conceptualization: K.N., M.A., H.M., A.S. Data curation: K.N., H.M., K.M. Formal analysis: H.M. Funding acquisition: K,M, K.A. Investigation: K.N., M.A., H.I., M.S., K.M. Methodology: K.N., H.M., A.S. Project administration: K.M, K.A. Resources: K.N., M.A., H.I., M.S., K.M., K.A. Software: H.M. Supervision: K.M., A.K. Validation: K.N. Visualization: K.N., H.M. Writing - original draft: K.N. Writing - review & editing: K.N., M.A., H.M., A.S., H.I, M.S., K.M, A.K. Acknowledgments The adult pneumonia study group Japan comprises Masahiko Abe 1 , Takao Wakabayashi 1 , Masahiro Aoshima 2 , Naoto Hosokawa 3 , Norihiro Kaneko 2 , Naoko Katsurada 2 , Kei Nakashima 2 , Yoshihito Otsuka 4 , Eiichiro Sando 5 , Kaori Shibui 5 , Daisuke Suzuki 3 , Kenzo Tanaka 6 , Kentaro Tochitani 3 , Makito Yaegashi 5 , Masayuki Chikamori 7 , Naohisa Hamashige 7 , Masayuki Ishida 7 , Hiroshi Nakaoka 7 , Norichika Aso 8 , Hiroyuki Ito 8 , Kei Matsuki 8 , Yoshiko Tsuchihashi 8 , Koya Ariyoshi 9 , Bhim G. Dhoubhadel 9 , Akitsugu Furumoto 9 , Sugihiro Hamaguchi 1, 9 , Tomoko Ishifuji 9 , Shungo Katoh 1,9 , Satoshi Kakiuchi 9 , Emi Kitashoji 9 , Takaharu Shimazaki 9 , Motoi Suzuki 9 , Masahiro Takaki 9 , Konosuke Morimoto 9 , Kiwao Watanabe 9 , and Lay-Myint Yoshida 10 . 1 Department of General Internal Medicine, Ebetsu City Hospital, Hokkaido, Japan 2 Department of Pulmonology, Kameda Medical Center, Chiba, Japan 3 Department of Infectious Diseases, Kameda Medical Center, Chiba, Japan 4 Department of Laboratory Medicine, Kameda Medical Center, Chiba, Japan 5 Department of General Internal Medicine, Kameda Medical Center, Chiba, Japan 6 Emergency and Trauma Center, Kameda Medical Center, Chiba, Japan 7 Department of Internal Medicine, Chikamori Hospital, Kochi, Japan 8 Department of Internal Medicine, Juzenkai Hospital, Nagasaki, Japan 9 Department of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan 10 Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan References World Health Organization. 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Schweitzer VA, van Heijl I, Boersma WG, Rozemeijer W, Verduin K, Grootenboers MJ, Sankatsing SUC, van der Bij AK, de Bruijn W, Ammerlaan HSM et al : Narrow-spectrum antibiotics for community-acquired pneumonia in Dutch adults (CAP-PACT): a cross-sectional, stepped-wedge, cluster-randomised, non-inferiority, antimicrobial stewardship intervention trial . Lancet Infect Dis 2022, 22 (2):274-283. Tables Table 1. Pretreatment variables of patients with community-acquired pneumonia in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching Variable Before matching After matching BLM BL SMD a BLM BL SMD a N = 311 N = 2473 N = 298 N = 298 Age, year 64.51 (20.63) 76.04 (15.08) 0.638 66.03 (19.50) 66.82 (19.71) 0.040 Female sex 142 (45.7) 952 (38.5) 0.145 134 (45.0) 117 (39.3) 0.116 Hospital 0.991 0.704 Chikamori Hospital 6 (1.9) 484 (19.6) 6 (2.0) 44 (14.8) Ebetsu City Hospital 25 (8.0) 344 (13.9) 24 (8.1) 34 (11.4) Juzenkai Hospital 0 (0.0) 339 (13.7) 0 (0.0) 24 (8.1) Kameda Medical Center 280 (90.0) 1306 (52.8) 268 (89.9) 196 (65.8) Treatment setting Outpatient 134 (43.1) 442 (17.9) 0.570 122 (40.9) 122 (40.9) <0.001 Risk of bacterial resistance Hospitalization for more than 2 days within 3 months 29 (9.3) 500 (20.2) 0.311 29 (9.7) 26 (8.7) 0.035 Residing in a nursing home or convalescent facility 15 (4.8) 443 (17.9) 0.421 15 (5.0) 13 (4.4) 0.032 Dialysis (within 30 days) 8 (2.6) 40 (1.6) 0.067 8 (2.7) 9 (3.0) 0.020 Comorbidity Diabetes mellitus 51 (16.4) 523 (21.1) 0.122 51 (17.1) 46 (15.4) 0.045 Heart failure 27 (8.7) 404 (16.3) 0.233 27 (9.1) 23 (7.7) 0.048 Liver disease 4 (1.3) 155 (6.3) 0.264 4 (1.3) 4 (1.3) <0.001 Renal disease 27 (8.7) 282 (11.4) 0.091 26 (8.7) 26 (8.7) <0.001 Dementia 10 (3.2) 424 (17.1) 0.473 10 (3.4) 9 (3.0) 0.019 Malignancy 35 (11.8) 510 (20.6) 0.258 35 (11.7) 35 (11.7) <0.001 Asthma 26 (8.5) 258 (10.4) 0.132 21 (7.0) 20 (6.7) 0.013 COPD or bronchiectasis 50 (16.4) 600 (24.3) 0.306 39 (13.1) 48 (16.1) 0.086 Medication Oral steroids 38 (12.5) 201 (8.1) 0.042 28 (9.4) 24 (8.1) 0.048 Antacids 82 (26.4) 746 (30.2) 0.084 79 (26.5) 83 (27.9) 0.030 Sleep-inducing drugs 29 (9.3) 315 (12.7) 0.109 29 (9.7) 17 (5.7) 0.151 Aspiration-associated risk factors Aspiration episodes 39 (12.5) 708 (28.6) 0.406 39 (13.1) 36 (12.1) 0.030 Impaired consciousness 9 (2.9) 159 (6.4) 0.168 9 (3.0) 2 (0.7) 0.175 Neuromuscular diseases 8 (2.6) 199 (8.0) 0.246 8 (2.7) 7 (2.3) 0.021 Insertion or placement of devices (e.g., nasogastric tubes) 2 (0.6) 64 (2.6) 0.155 2 (0.7) 2 (2.3) <0.001 Cerebrovascular diseases 25 (8.0) 608 (24.6) 0.460 25 (8.4) 26 (8.7) 0.012 Long-term bedridden status 25 (8.0) 332 (13.4) 0.175 25 (8.4) 18 (6.0) 0.091 Vital signs at diagnosis Impaired consciousness 30 (9.6) 499 (20.2) 0.299 30 (10.1) 22 (7.4) 0.095 Heart rate, beats/minute 97.26 (17.90) 96.11 (20.39) 0.060 96.90 (17.82) 97.65 (19.36) 0.040 Respiratory rate, breaths/minute 21.91 (5.57) 22.52 (6.09) 0.105 21.96 (5.59) 22.49 (6.31) 0.090 Systolic blood pressure, mmHg 127.08 (23.46) 130.18 (25.79) 0.126 127.42 (23.57) 128.14 (19.36) 0.159 Body temperature Celsius 37.50 (1.06) 37.45 (1.10) 0.050 37.50 (1.06) 37.47 (1.04) 0.031 Laboratory data at diagnosis Hematocrit, % 38.02 (5.46) 36.59 (5.89) 0.252 37.92 (5.53) 37.88 (5.72) 0.007 BUN, mg/dL 17.54 (12.99) 22.39 (15.57) 0.338 17.91 (13.12) 17.74 (10.60) 0.014 Na, mEq/L 137.80 (3.54) 137.62 (4.64) 0.044 137.76 (3.59) 137.73 (4.24) 0.006 Glucose, mg/dL 135.20 (59.95) 139.67 (59.01) 0.075 136.19 (60.60) 138.73 (60.59) 0.042 Albumin, g/dL 3.52 (0.55) 3.41 (0.56) 0.188 3.49 (0.54) 3.48 (0.59) 0.031 Pleural effusion on chest X-ray 11 (3.5) 186 (7.5) 0.175 11 (3.7) 6 (2.0) 0.101 CURB-65 ≥3 52 (16.7) 621 (25.1) 0.207 52 (17.4) 53 (17.8) 0.009 ≥4 15 (4.8) 129 (5.2) 0.018 15 (5.0) 11 (3.7) 0.066 Data are presented as number (%) or mean (standard deviation). a Propensity score matching was conducted using 34 variables: age, sex, treatment setting (outpatient or inpatient), history of hospitalization (hospitalization for more than 2 days within 3 months before the diagnosis of CAP), residing in a nursing home or convalescent facility, dialysis (within 30 days before diagnosis), preexisting comorbidities (diabetes, heart failure, liver disease, renal disease, dementia, malignancy, asthma, and chronic respiratory disease [COPD and bronchiectasis]), prescribed drugs before admission (oral steroids, antacids, and sleeping drugs), aspiration-associated factors (aspiration episodes, impaired consciousness, neuromuscular disease, insertion or placement of devices (e.g., nasogastric tubes), cerebrovascular disease, and long-term bedridden status), vital signs at diagnosis (consciousness, heart rate, respiratory rate, systolic blood pressure, and body temperature), laboratory data at diagnosis (hematocrit, BUN, sodium, glucose, and albumin), and findings of chest X-ray (pleural effusion). An SMD of <0.1 among the covariates was considered an appropriate match balance. BL, beta-lactam monotherapy; BLM, beta-lactam plus macrolide; BUN, blood urea nitrogen; CAP; community-acquired pneumonia; COPD, chronic obstructive pulmonary disease; SMD, standardized mean difference Table 2. Microbiological test findings, including culture and polymerase chain reaction analysis results, in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching Causative pathogen Before matching After matching BLM N = 311 BL N = 2473 BLM N = 298 BL N = 298 Sputum culture performed a 275 (88.4) 2305 (93.2) 267 (89.6) 268 (89.9) Streptococcus pneumoniae 25 (8.0) 274 (11.1) 25 (8.4) 40 (13.4) Haemophilus influenzae 32 (10.3) 246 (9.9) 31 (10.4) 35 (11.7) Methicillin-sensitive Staphylococcus aureus 9 (2.9) 153 (6.2) 9 (3.0) 17 (5.7) Pseudomonas aeruginosa 4 (1.3) 164 (6.6) 4 (1.3) 17 (5.7) Moraxella catarrhalis 15 (4.8) 159 (6.4) 14 (4.7) 20 (6.7) Klebsiella pneumoniae 4 (1.3) 141 (5.7) 3 (1.0) 1 (0.3) Methicillin-resistant Staphylococcus aureus 4 (1.3) 78 (3.2) 4 (1.3) 6 (2.0) Escherichia coli 2 (0.6) 72 (2.9) 2 (0.7) 10 (3.4) Klebsiella oxytoca 0 (0.0) 14 (0.6) 0 (0.0) 4 (1.3) Serratia marcescens 0 (0.0) 24 (1.0) 0 (0.0) 2 (0.7) Escherichia coli (ESBL) 0 (0.0) 12 (0.5) 0 (0.0) 0 (0.0) Legionella pneumophila 1 (0.3) 0 (0.0) 1 (0.3) 0 (0.0) Urinary antigen of Streptococcus pneumoniae performed 194 (62.4) 1446 (78.6) 188 (63.1) 152 (51.0) Positive 22 (7.1) 235 (9.5) 22 (7.4) 25 (8.4) Urinary antigen of Legionella pneumophila performed 180 (57.9) 1109 (48.8) 176 (59.0) 123 (41.3) Positive 1 (0.3) 2 (0.1) 1 (0.3) 0 (0.0) Prompt antigen of influenza virus performed 39 (12.5) 467 (18.9) 39 (13.1) 53 (17.8) positive 6 (1.9) 19 (0.8) 6 (2.0) 1 (0.3) Sputum bacterial PCR performed 209 (67.2) 1943 (78.6) 205 (68.8) 206 (69.1) Streptococcus pneumoniae 44 (14.1) 394 (15.9) 44 (14.8) 53 (17.8) Haemophilus influenzae 51 (16.4) 280 (11.3) 50 (16.8) 46 (15.4) Moraxella catarrhalis 47 (15.1) 222 (9.0) 46 (15.4) 21 (7.0) Mycoplasma pneumoniae 22 (7.1) 31 (1.3) 20 (6.7) 8 (2.7) Chlamydia pneumoniae 1 (0.3) 4 (0.2) 1 (0.3) 0 (0.0) Legionella pneumophila 0 (0.0) 2 (0.1) 0 (0.0) 0 (0.0) Sputum viral PCR performed 211 (67.8) 1943 (78.6) 207 (69.5) 205 (68.8) Human rhinovirus 15 (4.8) 197 (8.0) 14 (4.7) 20 (6.7) Respiratory syncytial virus 6 (1.9) 73 (3.0) 6 (2.0) 6 (2.0) Influenza A 7 (2.3) 58 (2.3) 7 (2.3) 12 (4.0) Human parainfluenza virus type 3 2 (0.6) 40 (1.6) 2 (0.7) 6 (2.0) Human metapneumovirus 7 (2.3) 30 (1.2) 7 (2.3) 1 (0.3) Human parainfluenza virus type 1 1 (0.3) 21 (0.8) 1 (0.3) 4 (1.3) Influenza B 3 (1.0) 15 (0.6) 3 (1.0) 2 (0.7) Human parainfluenza virus type 2 0 (0.0) 7 (0.3) 0 (0.0) 1 (0.3) Human coronavirus (229E/OC43) 0 (0.0) 22 (0.9) 0 (0.0) 3 (1.0) Human adenovirus 0 (0.0) 2 (0.1) 0 (0.0) 0 (0.0) Human bocavirus 0 (0.0) 2 (0.1) 0 (0.0) 0 (0.0) Blood culture performed a 193 (62.1) 1556 (62.9) 187 (62.8) 173 (58.1) Escherichia coli 3 (1.0) 15 (0.6) 3 (1.0) 1 (0.3) Streptococcus pneumoniae 3 (1.0) 13 (0.5) 3 (1.0) 0 (0.0) Methicillin-sensitive Staphylococcus aureus 0 (0.0) 14 (0.6) 0 (0.0) 0 (0.0) Klebsiella pneumoniae 0 (0.0) 12 (0.5) 0 (0.0) 1 (0.3) Haemophilus influenzae 3 (1.3) 0 (0.0) 4 (1.3) 0 (0.0) Pseudomonas aeruginosa 0 (0.0) 3 (0.1) 0 (0.0) 0 (0.0) Escherichia coli (ESBL) 0 (0.0) 2 (0.1) 0 (0.0) 0 (0.0) Moraxella catarrhalis 0 (0.0) 1 (0.0) 0 (0.0) 0 (0.0) Methicillin-resistant Staphylococcus aureus 0 (0.0) 2 (0.1) 0 (0.0) 1 (0.3) Data are presented as number (%). a In the analysis of sputum and blood cultures, only pathogens assessed as clinically pertinent to pneumonia were reported. Bacteria of ambiguous clinical significance, uncommon bacteria, and organisms recognized as normal flora were excluded from the report. BLM, beta-lactam plus macrolide; BL, beta-lactam monotherapy; ESBL, extended spectrum beta-lactamase; PCR, polymerase chain reaction Table 3 Antibiotics used in this study participants in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching Antibiotics Before matching After matching BLM N = 311 BL N = 2473 BLM N = 298 BL N = 298 Beta-lactam a Ceftriaxone 139 (44.7) 794 (32.1) 132 (44.3) 102 (34.2) Ampicillin-sulbactam 13 (4.2) 715 (28.9) 13 (4.4) 64 (21.5) Piperacillin-tazobactam 46 (14.8) 450 (18.2) 46 (15.4) 35 (11.7) Amoxicillin 62 (19.9) 207 (8.4) 58 (19.5) 45 (15.1) Amoxicillin-clavulanate 57 (18.3) 204 (8.2) 53 (17.8) 45 (15.1) Cefotaxime 10 (3.2) 79 (3.2) 10 (3.4) 11 (3.7) Meropenem 0 (0) 45 (1.8) 0 (0.0) 3 (1.0) Cefditoren-pivoxil 36 (11.6) 141 (5.7) 35 (11.7) 36 (12.1) Cefepime 6 (1.9) 34 (1.4) 6 (2.0) 4 (1.3) Ampicillin 1 (0.3) 19 (0.8) 1 (0.3) 2 (0.7) Benzylpenicillin 2 (0.6) 5 (0.2) 2 (0.7) 0 (0.0) Cefotiam 2 (0.6) 12 (0.5) 2 (0.7) 0 (0.0) Piperacillin 0 (0) 9 (0.4) 0 (0.0) 1 (0.3) Others 11 (3.5) 87 (3.5) 10 (3.4) 10 (3.4) Macrolide Azithromycin 300 (96.5) 287 (96.3) Clarithromycin 8 (2.6) 8 (2.7) Erythromycin 3 (1.0) 3 (1.0) Data are presented as number (%). a Owing to duplications, the total number of each column exceeded the number of patients in each group. BLM, beta-lactam plus macrolide; BL, beta-lactam monotherapy Table 4 Primary and secondary endpoints for the patients with community-acquired pneumonia treated with beta-lactam plus macrolide dual therapy and beta-lactam monotherapy BLM (N = 285) a BL (N = 285) a Absolute difference Primary endpoints Death, % 5.06 (2.73 – 7.78) 4.98 (2.36 – 8.21) 0.00 (−3.73 to 3.71) Recovery, % 91.79 (88.43 – 94.77) 91.69 (87.73 – 95.10) 0.00 (−4.48 to 4.82) Secondary endpoints Duration of antibiotic treatment (days) 8.97 (8.46 – 9.51) 9.93 (9.01 – 17.10) −0.99 (−8.20 to 0.10) Length of hospital stay (days) b 17.72 (15.29 – 20.50) 20.30 (17.31 – 24.09) −2.59 (−6.99 to 1.45) Values in parentheses indicate the 95% CI. a N represents the point estimates derived from the median of the bootstrap results. The median and the 95% CI for N are 285 (253–318). b Regarding the length of hospital stay, the number of cases was 166 (95%CI 140–192) in both the BLM and BL groups, as these endpoints were assessed exclusively in hospitalized patients. BLM, beta-lactam plus macrolide; BL, beta-lactam monotherapy; CI, confidence interval Table 5 Primary and secondary endpoints for patients with a CURB-65 score of 3 or above who were treated for community-acquired pneumonia with beta-lactam plus macrolide dual therapy and beta-lactam monotherapy BLM (N = 29) a BL (N = 29) a Absolute difference Primary endpoints Death, % 12.00 (0.00 – 25.71) 13.33 (0.00–29.41) 0.00 (−20.00 to 16.13) Recovery, % 82.86 (68.00–95.65) 83.33 (66.67–96.42) 0.00 (−20.00 to 20.00) Secondary endpoints Duration of antibiotic treatment (days) 9.62 (7.82–11.77) 10.52 (8.14–14.32) −0.92 (−5.07 to 2.30) Length of hospital stay (days) b 24.06 (14.72–35.64) 23.57 (14.93–36.62) 0.28 (−15.11 to 14.64) Values in parentheses indicate the 95% CI. a N represents the point estimates derived from the median of the bootstrap results. The median and the 95% CI for N are 29 (16–44). b Regarding the length of hospital stay, the number of cases was 21 (95%CI 10–34) in both the BLM and BL groups because these endpoints were assessed exclusively in hospitalized patients. BLM, beta-lactam plus macrolide; BL, beta-lactam monotherapy; CI, confidence interval Additional Declarations Competing interest reported. K.M. received research funding support from Pfizer. K.M. and K.A. received collaborative research funding from Pfizer. Supplementary Files 20250629Supplementarymaterialkn13clean.docx Cite Share Download PDF Status: Published Journal Publication published 29 Dec, 2025 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 16 Oct, 2025 Reviews received at journal 15 Oct, 2025 Reviews received at journal 10 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviews received at journal 09 Oct, 2025 Reviewers agreed at journal 09 Oct, 2025 Reviewers invited by journal 09 Oct, 2025 Editor assigned by journal 15 Sep, 2025 Submission checks completed at journal 01 Jul, 2025 First submitted to journal 29 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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14:45:19","extension":"html","order_by":19,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":235369,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-5738269/v1/4d078cdc3a3d021305328e2a.html"},{"id":93342739,"identity":"3755559d-eb2b-4814-ac06-d2a3a1abf72a","added_by":"auto","created_at":"2025-10-12 14:45:18","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":921777,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient selection. In this analysis, 50 datasets were created using multiple imputation. Each dataset underwent 1,000 bootstrap resamplings, and one of the datasets was randomly selected to serve as a reference dataset. The imputation process resulted in slight variations in the sample sizes of the beta-lactam plus macrolide treatment (BLM) and beta-lactam monotherapy (BL) groups. (The original dataset had 306 patients and 2,478 patients in the BLM and BL groups, respectively, whereas the reference dataset generated using bootstrapping had 311 and 2,473 patients in the BLM and BL groups, respectively). These variations can be attributed to the differing imputed values across the datasets in the multiple imputation process and the variability introduced by the random sampling inherent in the bootstrap method.\u003c/p\u003e\n\u003cp\u003eAPSG-J, the Adult Pneumonia Study Group-Japan; BL, beta-lactam monotherapy; BLM, beta-lactam plus macrolide; CAP, community-acquired pneumonia\u003c/p\u003e","description":"","filename":"Figure1revision.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5738269/v1/8bb1852102a86e2a2bcf42b9.jpg"},{"id":93343463,"identity":"db66d811-e184-4a97-b9ab-6ebdd29f0e9c","added_by":"auto","created_at":"2025-10-12 14:53:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":236692,"visible":true,"origin":"","legend":"\u003cp\u003eCumulative incidence curve of the primary endpoints (death or recovery) of patients, generated from one of the datasets in which missing values in the original dataset were replaced with values imputed using multiple imputation\u003c/p\u003e\n\u003cp\u003eBL, beta-lactam monotherapy; BLM, beta-lactam plus macrolide\u003c/p\u003e","description":"","filename":"Figure2revision.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5738269/v1/6ae146cf78d2aa1acdc8347e.jpg"},{"id":99545514,"identity":"31e8f9a3-17f7-4ee5-a67d-f3b5e7b895c5","added_by":"auto","created_at":"2026-01-05 16:08:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4769421,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5738269/v1/d0225d18-5061-405b-ae56-9d818bf7f211.pdf"},{"id":93343464,"identity":"7c691f6e-15d6-4015-8ce5-dc38bbaf1105","added_by":"auto","created_at":"2025-10-12 14:53:18","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":92949,"visible":true,"origin":"","legend":"","description":"","filename":"20250629Supplementarymaterialkn13clean.docx","url":"https://assets-eu.researchsquare.com/files/rs-5738269/v1/a8c0b52b7564c5d869a9480d.docx"}],"financialInterests":"Competing interest reported. K.M. received research funding support from Pfizer. K.M. and K.A. received collaborative research funding from Pfizer.","formattedTitle":"Beta-lactam plus macrolide treatment versus beta-lactam monotherapy for community-acquired pneumonia: a propensity score analysis using data from a multicenter prospective cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCommunity-acquired pneumonia (CAP) represents the most prevalent infectious cause of mortality globally, accounting for 2.6\u0026nbsp;million deaths per year, according to the report of World Health Organization [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. CAP is associated with a 30-day all-cause risk-standardized mortality rate of 11.6% and readmission rate of 18.2% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Beta-lactams, which primarily target bacterial pathogens such as \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e, represent the principal therapeutic agents for CAP [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In empirical therapy for hospitalized patients or patients with comorbidities, macrolides are generally added to beta-lactams to treat infections of atypical pathogens, particularly severe CAP [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe efficacy of adding macrolides to beta-lactams in reducing mortality in the treatment of CAP remains controversial [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Several prospective and retrospective observational studies have reported that dual therapy involving beta-lactam plus macrolide treatment (BLM) reduces the 30-day and in-hospital mortality of hospitalized patients with CAP, particularly in those with severe disease [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e–\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In contrast, data from randomized controlled trials (RCTs) have not shown a mortality benefit despite showing an improvement in early clinical response [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. An RCT demonstrated that patients in the BLM group exhibited a more favorable trend towards achieving clinical stability after 7 days of treatment than those in the beta-lactam monotherapy (BL) group. However, there were no differences in the 30- and 90-d mortality rates between the BLM and BL groups [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Moreover, a cluster RCT found that BL was not inferior to BLM for the treatment of CAP in patients admitted to non-ICU wards in terms of 90-d mortality [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Furthermore, a recent network meta-analysis of RCTs found no significant difference in efficacy between BLM and BL for CAP treatment [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Moreover, a recent RCT of patients with CAP and systemic inflammatory response syndrome showed that, compared with BL, BLM improved the early clinical response, but the 28- and 90-day mortality rates did not differ between the treatment groups [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurther contributing to this debate, a recent (2025) large, real-world observational study from the United Kingdom found that BLM was not associated with a reduction in mortality, even in patients with severe pneumonia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This finding is consistent with the results from previous RCTs. The persistent controversy highlights an urgent need for additional high-quality, real-world evidence. Such evidence is crucial for inclusion in future meta-analyses to definitively resolve these clinical uncertainties [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTherefore, our objective was to assess the effectiveness of BLM compared with BL in reducing mortality across the entire spectrum of CAP, using data from a multicenter prospective cohort study with propensity score matching to control for differences in baseline patient characteristics between groups.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eStudy setting and population\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWe performed a secondary analysis of data from a multicenter prospective cohort study of patients with CAP collected by the Adult Pneumonia Study Group-Japan (APSG-J), utilizing propensity score analysis. The APSG-J study prospectively collected data on patients diagnosed with CAP from both outpatient and inpatient services at Ebetsu City Hospital, Kameda Medical Center, Chikamori Hospital, and Juzenkai Hospital between September 2011 and September 2014 [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. CAP was diagnosed when all the following criteria were met: patients 1) aged ≥ 15 years, 2) exhibited symptoms compatible with pneumonia, such as fever, cough, sputum production, pleuritic chest pain, and dyspnea; and 3) displayed new pulmonary infiltrates on chest X-ray images or CT scans consistent with pneumonia. Our analysis included all participants enrolled in APSG-J. Chest X-rays were performed within 24 hours of admission, while CT scans were performed at the discretion of the attending physicians. The exclusion criteria were as follows: 1) patients did not receive antimicrobial agents; 2) patients who were initially treated solely with macrolides; and 3) patients who were initially treated with antibiotics other than beta-lactams or macrolides, as well as those who received antifungal agents, antituberculosis drugs, or antiviral agents. To specifically measure the effect of BLM compared to BL, we excluded patients receiving macrolide monotherapy or antimicrobial agents other than those in the two classes of interest.\u003c/p\u003e\u003cp\u003e The study was conducted in accordance with the Guideline for Ethical Aspects in Epidemiological Study (Ministry of Health, Labour and Welfare, Japan 2008). This study received approval from the review board of the Institute of Tropical Medicine at Nagasaki University and the review boards of Ebetsu City Hospital, Kameda Medical Center, Chikamori Hospital, and Juzenkai Hospital (registration no. 11063070). We obtained written informed consent from all conscious patients. Given that the study was observational and involved no invasive interventions or deviations from standard medical treatment, all the institutional review boards waived the requirement for written informed consent for a few unconscious patients. The study was registered with the University Hospital Medical Information Network (UMIN000006909).\u003c/p\u003e\u003cp\u003e\u003cem\u003eTreatment group definitions\u003c/em\u003e\u003c/p\u003e\u003cp\u003ePatients were categorized into two groups based on the initial treatment received: those who were started on a combination of beta-lactam and macrolide treatment (BLM group) and those treated with beta-lactam alone (BL group). Specifically, inclusion in the BLM group required that the patient received at least one dose of a macrolide antibiotic in conjunction with beta-lactam therapy. Although antibiotic dosing generally followed standard reference guidelines [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], the specific dosage regimens were determined by the attending physicians at each institution without standardization across study sites. The classification into these treatment groups occurred at the time of CAP diagnosis, and the observation period for outcomes commenced immediately thereafter.\u003c/p\u003e\u003cp\u003e\u003cem\u003eOutcome measures\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe primary endpoint was the outcome at the end of the observation period (death or recovery). The end of the observation period was defined according to the patient's clinical course. For hospitalized patients, follow-up was completed at the time of discharge. For patients whose pneumonia improved and were followed as outpatients, the date of the final outpatient visit related to CAP was considered the end of the observation period. If the final clinical outcome was unknown—such as in cases in which outpatient follow-up ended due to transfer to another hospital—follow-up was censored on the date of the most recent clinic visit. The outcomes were recorded at the end of the observation period, and included recovery, stable condition, deterioration, death, and transfer to another hospital. Death was defined as an in-hospital death from any cause. The secondary endpoints were the length of hospital stay and duration of antibiotic use.\u003c/p\u003e\u003cp\u003e\u003cem\u003eMicrobiological test\u003c/em\u003e\u003c/p\u003e\u003cp\u003eGood quality sputum and blood specimens were collected on admission. If patients were unable to expectorate sputum, it was induced by inhalation of hypertonic saline soon after admission, and sputum was collected before antibiotic administration. Upon arrival at each hospital's laboratory, clinical specimens were promptly processed. All sputum samples were subjected to semi-quantitative or quantitative cultures. In addition, these samples were analyzed at the Institute of Tropical Medicine, Nagasaki University, using in-house multiplex polymerase chain reaction (PCR) to detect a panel of bacterial and viral pathogens. This panel included three typical bacteria (\u003cem\u003eStreptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis\u003c/em\u003e), three atypical bacteria \u003cem\u003e(Mycoplasma pneumoniae, Chlamydophila pneumoniae, and Legionella pneumophila\u003c/em\u003e), and 13 viruses (influenza A and B, respiratory syncytial virus, human metapneumovirus, parainfluenza virus types 1–4, rhinovirus, coronavirus 229E/OC43, adenovirus, and bocavirus). The specific primers and PCR protocols used have been detailed in previous studies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Commercial kits (Binax NOW; Alere Inc.) were also used to conduct urinary antigen tests for \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e and \u003cem\u003eLegionella pneumophila\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe APSG-J study prospectively collected the following clinical information: age, sex, registered hospital, treatment setting (outpatient or inpatient), history of hospitalization (hospitalization for more than 2 days within 3 months before CAP diagnosis), residing in a nursing home or convalescent facility, dialysis (within 30 days), preexisting comorbidities (diabetes, heart failure, liver disease, renal disease, dementia, malignancy, asthma, and chronic respiratory disease [chronic obstructive pulmonary disease and bronchiectasis]), prescribed drugs before admission (oral steroids, antacids, and sleep-inducing drugs), aspiration-associated factors (aspiration episodes, impaired consciousness, neuromuscular disease, insertion or placement of devices (e.g., nasogastric tubes), cerebrovascular disease, and long-term bedridden status), vital signs at diagnosis (consciousness, heart rate, respiratory rate, systolic blood pressure, and body temperature), laboratory data at diagnosis (hematocrit, blood urea nitrogen, sodium, glucose, and albumin levels), chest X-ray findings (pleural effusion), microbiological test findings (culture, urinary antigen, and polymerase chain reaction [PCR] analysis), administered antibiotics, outcome at the end of the observation period, length of hospital stay, and duration of antibiotic use.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eOwing to the observational nature of this study, we used the available number of cases and did not perform any sample size calculations [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. All statistical analyses were performed in R 4.3.0 for statistical computing (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org/\u003c/span\u003e\u003cspan address=\"https://www.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), with the add-on packages “tableone” for creating tables [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], “mice” for multiple imputation [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], “MatchIt” for propensity score matching [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and “cmprsk” for survival analysis [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. All tests were two-tailed, and differences were considered statistically significant at p \u0026lt; 0.05. As there were several missing values, we used multiple imputation by employing chained equations to complement all missing values in the study variables and generated 50 datasets with five iterations. To calculate the 95% confidence interval (CI), we employed the bootstrap method described by Schomaker and Heumann to appropriately integrate uncertainty from both multiple imputation and resampling [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Specifically, we used \"Method 1: MI Boot (pooled sample [PS])\" from their study. Following this procedure, we generated 1000 bootstrap samples for each of the 50 imputed datasets. The estimates from all resulting samples were then pooled into a single distribution, and the lower and upper limit of the 95% CI was defined by the 2.5th and 97.5th percentiles of this pooled distribution. In addition, we conducted a sensitivity analysis by excluding all cases with missing data prior to imputation. After performing multiple imputations, no missing values remained, and the subsequent propensity score-matched analysis (described below) was conducted including all the relevant variables.\u003c/p\u003e\u003cp\u003e\u003cem\u003ePropensity score matching\u003c/em\u003e\u003c/p\u003e\u003cp\u003eA logistic regression analysis was used to estimate the propensity score to predict the use of BLM rather than BL from 34 pretreatment covariates, including age, sex, treatment setting (outpatient or inpatient), history of hospitalization (hospitalization for more than 2 days within 3 months before the diagnosis of CAP), residing in a nursing home or convalescent facility, dialysis (within 30 d before diagnosis), preexisting comorbidities (diabetes, heart failure, liver disease, renal disease, dementia, malignancy, asthma, and chronic respiratory disease [chronic obstructive pulmonary disease and bronchiectasis]), prescribed drugs before admission (oral steroids, antacid, and sleeping drugs), aspiration-associated factors (aspiration episodes, impaired consciousness, neuromuscular disease, insertion or placement of devices (e.g., nasogastric tubes), cerebrovascular disease, and long-term bedridden status), vital signs at diagnosis (consciousness, heart rate, respiratory rate, systolic blood pressure, and body temperature), laboratory data at diagnosis (hematocrit, blood urea nitrogen, sodium, glucose, and albumin), and findings of chest X-ray (pleural effusion). We selected these as covariates because they are risk factors for antibiotic-resistant bacteria, prognostic factors, and risk factors for aspiration pneumonia [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e–\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Propensity score matching selected participants pairwise on a 1:1 basis after all propensity scores across the imputed datasets were averaged and logit-transformed. The match caliper was set to standard deviation of the propensity score multiplied by 0.05. We used standardized mean differences (SMDs) of all variables included in the propensity score estimation to assess the match balance, and SMDs of \u0026lt; 0.1 were defined as appropriate match balance [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003ePrimary and secondary analyses\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe primary endpoints were assessed by frequency in each group and absolute difference between the groups. The secondary endpoints were validated as continuous variables and absolute differences between the groups. A cumulative incidence curve of the primary endpoints (death or recovery) of patients was generated from one of the datasets after imputing missing values from the original dataset using multiple imputation [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. To assess the efficacy of BLM in severe CAP treatment, a subgroup analysis was conducted on patients with a CURB-65 score of 3 or higher [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In addition, based on previous reports suggesting that BLM may be effective in treating pneumococcal and bacteremic pneumonia [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], we conducted an exploratory subgroup analysis limited to patients with microbiologically confirmed non-atypical bacterial pneumonia. Microbiologically confirmed non-atypical bacterial pneumonia was defined by the presence of at least one of the following criteria: (1) a positive blood culture for a bacterial pathogen (excluding atypical pathogens) that could be the causative organism of pneumonia; (2) pleural fluid cultures yielding a bacterial pathogen other than atypical pathogens; or (3) a high-quality sputum sample (\u0026gt; 25 polymorphonuclear cells and \u0026lt; 10 epithelial cells per low-power field [total magnification ×100]) showing predominant growth of non-atypical bacterial pathogens in culture at ≥ 1 × 10⁶ CFU/mL, or a semiquantitative culture score of 3+; or (4) a positive pneumococcal urinary antigen test based on definitions used in previous studies [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cem\u003eSensitivity Analysis\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo assess possible biases associated with multiple imputations, the primary outcome was reassessed using propensity score-matched analysis with the original dataset. In addition, we conducted a sensitivity analysis using a narrower caliper width of 0.01 for matching.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA flowchart of the patient selection process is shown in Figure 1. Of the 3470 enrollees in the APSG-J study, 686 individuals were excluded. Subsequently, data of 2784 patients treated with BLM (306 patients) or BL (2478 patients) were analyzed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1 shows the pretreatment variables of patients with CAP in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching. SMDs \u0026lt; 0.1 and \u0026gt; 0.1 indicated balanced and unbalanced patient characteristics between groups, respectively. Before matching, the average observation periods for the two groups were 17.0 (\u0026plusmn;18.4) days and 24.0 (\u0026plusmn;24.6) days, respectively. The mean age of the patients was 64.51 years (\u0026plusmn;20.63) in the BLM group and 76.04 (\u0026plusmn;15.08) years in the BL group, indicating that the patients in the BL group were older. Notably, 90% of the patients in the BLM group were enrolled at Kameda Medical Center. The most common comorbidities included diabetes mellitus, malignancy, and chronic obstructive pulmonary disease or bronchiectasis. Oral corticosteroid use was observed in 8.6% of the patients in the overall cohort. A history of aspiration was noted in 12.5% of patients in the BLM group and 28.6% of patients in the BL group, with a higher frequency in the latter group. Similarly, cerebrovascular disease was more prevalent in the BL group. Patients with a CURB-65 score of \u0026ge;3 were also more common in the BL group. After propensity score matching, 34 covariates were adjusted. Among these, 29 variables achieved an SMD of \u0026lt;0.1, indicating balance, except for female sex, sleep-inducing drugs, impaired consciousness, systemic blood pressure, and pleural effusion on chest X-ray.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 shows the microbiological characteristics in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching. Before matching, the most commonly identified bacteria in sputum cultures were \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e, \u003cem\u003eHaemophilus influenzae\u003c/em\u003e, methicillin-sensitive \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eMoraxella\u003c/em\u003e \u003cem\u003ecatarrhalis\u003c/em\u003e, and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e. Among the entire pre-matching cohort, \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e was the most commonly identified atypical pathogen (1.9%), followed by \u003cem\u003eChlamydia pneumoniae\u0026nbsp;\u003c/em\u003e(0.2%). Among the urinary antigen tests, \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e and \u003cem\u003eLegionella pneumophila\u0026nbsp;\u003c/em\u003ewere positive in 9.2% and 0.1% (3 cases), respectively. The most frequently detected viruses on PCR testing of sputum samples, in descending order of prevalence were human rhinovirus, respiratory syncytial virus, influenza A virus, human parainfluenza virus type 3, and human metapneumovirus. After matching, bacterial pathogens, such as \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e, \u003cem\u003eHaemophilus influenzae\u003c/em\u003e, \u003cem\u003eMoraxella catarrhalis\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, and \u003cem\u003eEscherichia coli\u003c/em\u003e, were more frequently isolated in the BL group than in the BLM group. However, the number of patients with a positive pneumococcal urinary antigen test result was higher in the BLM group. Positive blood cultures were also more common in the BLM group. As for atypical pathogens, \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e PCR positivity was more frequent in the BLM group, and one patient in the BLM group tested positive for \u003cem\u003eL. pneumophila\u003c/em\u003e on the urinary antigen test.\u003c/p\u003e\n\u003cp\u003eTable 3 lists the antibiotics used by study participants in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching. Before matching, the most commonly used \u0026beta;-lactam antibiotics were, in descending order of frequency, ceftriaxone, ampicillin-sulbactam, piperacillin-tazobactam, amoxicillin, and amoxicillin-clavulanate. Azithromycin accounted for almost all macrolide use. After matching, ceftriaxone and piperacillin-tazobactam were more frequently used in the BLM group than in the BL group, whereas ampicillin-sulbactam was more frequently used in the BL group.\u003c/p\u003e\n\u003cp\u003eTable4 presents the results for the primary and secondary endpoints. Regarding the primary endpoints, the death rate was 5.06% (95% CI 2.73%\u0026ndash;7.78%) in the BLM group and 4.98% (95% CI 2.36%\u0026ndash;8.21%) in the BL group. The absolute difference was 0.00% (95% CI \u0026minus;3.73% to 3.71%). Similarly, the recovery rate was 91.79% (95% CI 88.43%\u0026ndash;94.77%) in the BLM group and 91.69% (95% CI 87.73%\u0026ndash;95.10%) in the BL group, with an absolute difference of 0.00% (95% CI \u0026minus;4.48% to 4.82%). For the secondary endpoints, the length of hospital stay and duration of antibiotic treatment were similar between groups. Figure 2 shows the cumulative incidence curve of the primary endpoints (death or recovery) of patients, generated using one of the datasets in which missing values in the original dataset were replaced with values imputed using multiple imputation.\u003c/p\u003e\n\u003cp\u003eSupplementary Table S1 presents the pretreatment variables of patients CAP in the subgroup with a CURB-65 score of 3 or higher from one of the bootstrapped imputed datasets, before and after propensity score matching. Despite a decrease in the number of cases and not all variables reaching SMD \u0026lt; 0.1, a statistical balance was attained for 18 of the 34 pretreatment covariates attempted to adjust, showing SMDs \u0026lt; 0.1, after matching. The results of the primary and secondary endpoint analyses are displayed in Table 5. No difference was observed in the death or recovery rates. Furthermore, the duration of antibiotic treatment and the length of hospital stay did not differ between the groups. Supplementary Table S2 shows the pretreatment variables of patients with CAP in the subgroup with microbiologically confirmed non-atypical bacterial pneumonia, using one of the bootstrapped imputed datasets, before and after propensity score matching. Although the number of cases decreased, 27 patients in each group were successfully matched. Supplementary Table S3 presents the primary and secondary endpoints of this subgroup. No differences were observed between the two groups in either primary or secondary outcomes.\u003c/p\u003e\n\u003cp\u003eFor the sensitivity analysis, we performed a complete case analysis. Supplementary Table S4 presents presents the pretreatment variables of patients with CAP in the original dataset including only complete cases with no missing values, before and after propensity score matching. In the complete case cohort, the proportion of outpatients was lower than that in the imputed datasets used in the primary analysis (236/1628 [14.5%] vs. 576/2784 [20.7%] before matching; 60/262 [22.9%] vs. 244/596 [40.9%] after matching). Supplementary Table S5 shows the primary and secondary endpoints. After matching, a balance was achieved between the groups for 25 of the 34 variables attempted for adjustment, with SMD \u0026lt; 0.1. The study outcomes were consistent with no differences in the primary endpoints of mortality and recovery rates. Similarly, no differences were observed in the secondary endpoints, namely, duration of antibiotic treatment and length of hospital stay. As an additional sensitivity analysis, we performed propensity score matching using a caliper width of 0.01. Supplementary Table S6 shows the pretreatment variables of patients with CAP in one of the datasets generated through bootstrapping of the imputed datasets, before and after matching using a caliper width of 0.01. Supplementary Table S7 shows the results for the primary and secondary endpoints. Consistent with the results of the main analysis, no differences were observed between the BLM and BL groups for any endpoint.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we compared the mortality and recovery rates between the BLM and BL groups in patients with CAP. Our findings indicated that the primary endpoints did not differ between the two treatments. Analysis of patients with a CURB-65 score of 3\u0026ndash;5 showed that mortality and recovery rates were similar between the BLM and BL groups. A subgroup analysis limited to cases of microbiologically confirmed non-atypical bacterial CAP also revealed no differences between BLM and BL. Sensitivity analysis using complete case data and a narrower caliper of 0.01 showed no differences between the treatments.\u003c/p\u003e\u003cp\u003eThe relevance of incorporating a macrolide with a beta-lactam in the management of CAP remains a contentious issue [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Discordance is also observed among national guidelines. The American Thoracic Society and Infectious Diseases Society of America guidelines recommend the administration of beta-lactams and macrolides to outpatients with underlying diseases or to hospitalized patients [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Conversely, the United Kingdom and Japanese guidelines suggest prescribing beta-lactams and macrolides to patients with moderately severe CAP when atypical pathogens are suspected [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. For severe CAP, all guidelines advocate the use of beta-lactams and macrolides [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In this study, we did not detect an additional benefit of macrolides in the overall analysis or the subgroup analysis limited to cases with a CURB-65 of 3 or higher. Several previous observational studies\u0026mdash;particularly those focusing on severe pneumonia\u0026mdash;have reported that BLM therapy reduces mortality in patients with CAP, and these reports have served as a basis for the recommendations contained in the current guidelines [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In contrast, several RCTs have not shown a mortality benefit of BLM therapy compared with BL therapy [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Two RCTs published in 2014 and 2015 did not demonstrate the superiority of BLM over BL in reducing mortality in the treatment of CAP [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. More recently, a 2024 RCT that examined patients with CAP along with systemic inflammatory response syndrome found that BLM enhanced the initial clinical response compared with BL [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, it revealed no difference in mortality at both 28 and 90 days following treatment between the groups. The discrepancy between findings from observational studies and RCTs may be attributable to several factors, including unmeasured confounding in observational data, differences in patient characteristics, or variation in circulating pathogens across geographic regions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Additionally, the lack of significant differences in mortality between groups in some RCTs may be attributable to insufficient statistical power due to limited sample sizes. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A recent large-scale observational study from the United Kingdom published in 2025, that used real-world data and adjusted for a broad range of patient characteristics and disease severity factors that could influence treatment selection [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our study showed similar mortality outcomes between the BLM and BL groups, consistent with the results of the United Kingdom study and those of RCTs [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMacrolide therapy is associated with an increased risk of cardiovascular events and death [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Macrolide combination regimens are effective in patients without cardiovascular diseases or patients with respiratory diseases and high leukocyte counts in the respiratory secretion [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Excessive use of macrolides is also a cause for concerns such as increasing emergence of macrolide-resistant bacteria [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The global importance of antimicrobial stewardship has been increasingly recognized. Avoiding unnecessary macrolide use is important from an antimicrobial stewardship perspective [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Therefore, healthcare professionals should understand both the advantages and disadvantages of macrolide use; make prescribing decisions accordingly, based on local epidemiological data and antibiogram profiles; and exercise caution when using macrolides in combination with beta-lactams for treating CAP.\u003c/p\u003e\u003cp\u003eSeveral potential mechanisms may account for the lack of an add-on effect of macrolides for reducing mortality in this study. First, the very low incidence of atypical pathogens in our cohort\u0026mdash;including \u003cem\u003eLegionella pneumophila\u003c/em\u003e (0.1%), \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e (1.9%), and \u003cem\u003eChlamydia pneumoniae\u003c/em\u003e (0.2%)\u0026mdash;is likely to have attenuated any survival advantage conferred by empiric macrolide therapy. In previous observational studies reporting the effectiveness of BLM therapy, the proportion of \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e in the cohort was 2.8% [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], while the proportion of \u003cem\u003eLegionella species\u003c/em\u003e ranged from 2.9\u0026ndash;3.0% [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. A 2012 Cochrane review showed that broad atypical coverage (predominantly fluoroquinolone monotherapy) did not improve overall survival or clinical success in patients hospitalized for CAP, although clinical success was significantly higher in the subset with \u003cem\u003eLegionella pneumophila\u003c/em\u003e infection [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In Japan, fluoroquinolones are often prescribed as soon as \u003cem\u003eLegionella pneumophila\u003c/em\u003e is detected by urinary antigen testing; thereby limiting the number of cases of \u003cem\u003eLegionella pneumophila\u003c/em\u003e infection available for inclusion in our study dataset. Second, previous observational studies showing the efficacy of BLM compared with BL may have been unadjusted for unknown confounding factors. A meta-analysis of RCTs in which the effects of unknown confounders were removed found no advantage of BLM over BL in terms of mortality [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this study, after imputing missing values by employing multiple imputations followed by bootstrapping, we attempted to adjust 34 variables related to patient outcomes and treatment factors, including risk factors for antimicrobial resistance, prognosis, and aspiration-associated risk. We believe that we adjusted the covariates as much as possible. Third, the inclusion of cases of macrolide-resistant \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e or \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e infection may have attenuated the effectiveness of BLM therapy. During the study period (2011\u0026ndash;2014), many cases of macrolide-resistant \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e and \u003cem\u003eMycoplasma. pneumoniae\u003c/em\u003e were reported in Japan [\u003cspan additionalcitationids=\"CR45 CR46 CR47\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Resistance mechanisms in \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e include the presence of the \u003cem\u003emef\u003c/em\u003e gene, which promotes efflux of the antibiotic, and the \u003cem\u003eermB\u003c/em\u003e gene, which alters the antibiotic target site [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. In \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e, macrolide resistance is primarily caused by point mutations in the ribosomal genes that encode the drug\u0026rsquo;s binding site [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. These resistance patterns could have diminished the clinical effectiveness of the BLM regimen.\u003c/p\u003e\u003cp\u003eA strength of this study is that it used a multicenter prospective cohort with a large number of patients in a real-world setting. In addition to the overall analysis, we performed subgroup analysis for CAP patients with CURB-65 score\u0026thinsp;\u0026ge;\u0026thinsp;3 and conducted a complete case sensitivity analysis. Across all analyses, similar results were observed in the primary outcomes between the BLM and BL groups.\u003c/p\u003e\u003cp\u003eFuture research should focus on specific patient subgroups, in which BLM therapy may be effective in reducing mortality. In our exploratory subgroup analysis of patients with microbiologically confirmed non-atypical bacterial pneumonia, mortality did not differ between the BLM and BL. However, this finding is inconclusive owing to the limited sample size. Previous studies have suggested that macrolides may exert beneficial anti-inflammatory and immunomodulatory effects [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], particularly in patients with systemic inflammatory responses or elevated inflammatory markers such as C-reactive protein or procalcitonin [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Moreover, macrolides have been shown to be effective in patients with pneumococcal pneumonia and pneumonia with bacteremia [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], highlighting the need to further investigate the potential benefit of macrolides in specific microbiologically defined subpopulations. As previously mentioned, underlying comorbidities\u0026mdash;such as the presence or absence of cardiovascular or respiratory diseases\u0026mdash;may also influence the effectiveness of BLM [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Therefore, further studies focusing on identifying specific subgroups based on inflammatory markers, microbiological findings, and underlying comorbidities are warranted. Clarifying these factors may contribute to the advancement of personalized treatment strategies for CAP. Until specific patient populations in which macrolides are effective are clearly established, the use of BLM should be limited to cases in which the use of BLM is recommended by current guidelines, such as patients with severe pneumonia or hospitalized patients, particularly those in whom atypical pathogens are suspected [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, as an observational study, the potential for residual confounding from unmeasured variables remains despite the use of propensity score analysis, in contrast to RCTs. This concern is underscored by the fact that several variables did not achieve a SMD of less than 0.1 in the main analysis. Furthermore, in the subset analysis of severely ill patients with a CURB-65 score of 3 or above, indicative of higher risk, we could successfully adjust only approximately half of the 34 variables owing to the limited number of qualifying cases. Second, the study may have been underpowered to exclude a clinically meaningful difference between the treatment groups, partly because of the lack of a priori sample size calculation and a low overall mortality rate (\u0026lt;\u0026thinsp;5%). This is highlighted in our primary analysis, where the 95% CI for the absolute difference in mortality (\u0026minus;\u0026thinsp;3.73\u0026ndash;3.71%) crossed the 3% non-inferiority margin often considered clinically significant in trials of CAP [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Thus, a modest, but clinically relevant, treatment effect cannot be ruled out. Nevertheless, publishing these findings is essential, as they will contribute valuable real-world evidence for inclusion in future meta-analyses, which can lead to more robust and precise conclusions [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Third, the generalizability of the findings may be limited. The study was conducted at four specific hospitals in Japan, with the majority of cases from a single center (Kameda Medical Center, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), which could introduce bias from unmeasured institutional-level factors (e.g., patient management protocols). Moreover, a substantial number of patients (686 of 3,470) were excluded because they received other treatments, potentially creating a selection bias and limiting the applicability of our results to a broader patient population. Fourth, the observation period was relatively short, allowing only short-term outcomes to be assessed. Consequently, long-term endpoints, such as 90-day mortality, could not be evaluated. Fifth, data on antimicrobial susceptibility were not collected. Given the high prevalence of macrolide-resistant \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e and \u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e in the region [\u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], the inability to assess the impact of resistance patterns on treatment effectiveness is a significant limitation. Given these limitations, our results should be interpreted with caution.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, similar outcomes were observed in the mortality and recovery rates between the BLM and BL groups among patients with CAP, both in the overall population and in patients with a CURB-65 score of 3 or higher. Clinicians should thoughtfully weigh the benefits of BLM against the potential risks, including adverse effects and antimicrobial resistance, when managing patients with CAP. Further large-scale prospective studies are warranted to generate a hypothesis regarding whether BLM is superior in patients with certain baseline characteristics in terms of reducing mortality and to test it through an RCT.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThe study received approval from the ethics review boards of the Institute of Tropical Medicine at Nagasaki University, Ebetsu City Hospital, Kameda Medical Center, Chikamori Hospital, and Juzenkai Hospital (registration no. 11063070). This study was conducted in accordance with the principles outlined in the Declaration of Helsinki. We obtained written informed consent from all conscious patients. In the cases of adults with cognitive decline, a legal guardian or an appropriate representative of these participants provided informed consent on their behalf. Given that the study was observational and involved no invasive interventions or deviations from standard medical treatment, all the institutional review boards waived the requirement for written informed consent for a few unconscious patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData pertaining to this study will be available by the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eK.M. received research funding support from Pfizer. K.M. and K.A. received collaborative research funding from Pfizer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThe Department of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University received financial support from Pfizer for this study. The funding source played no role in study design, or data collection, analysis, or interpretation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: K.N., M.A., H.M., A.S. Data curation: K.N., H.M., K.M. Formal analysis: H.M. Funding acquisition: K,M, K.A. Investigation: K.N., M.A., H.I., M.S., K.M. Methodology: K.N., H.M., A.S. Project administration: K.M, K.A. Resources: K.N., M.A., H.I., M.S., K.M., K.A. Software: H.M. Supervision: K.M., A.K. Validation: K.N. Visualization: K.N., H.M. Writing - original draft: K.N. Writing - review \u0026amp; editing: K.N., M.A., H.M., A.S., H.I, M.S., K.M, A.K.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe adult pneumonia study group Japan comprises Masahiko Abe\u003csup\u003e1\u003c/sup\u003e, Takao Wakabayashi\u003csup\u003e1\u003c/sup\u003e, Masahiro Aoshima\u003csup\u003e2\u003c/sup\u003e, Naoto Hosokawa\u003csup\u003e3\u003c/sup\u003e, Norihiro Kaneko\u003csup\u003e2\u003c/sup\u003e, Naoko Katsurada\u003csup\u003e2\u003c/sup\u003e, Kei Nakashima\u003csup\u003e2\u003c/sup\u003e, Yoshihito Otsuka\u003csup\u003e4\u003c/sup\u003e, Eiichiro Sando\u003csup\u003e5\u003c/sup\u003e, Kaori Shibui\u003csup\u003e5\u003c/sup\u003e, Daisuke Suzuki\u003csup\u003e3\u003c/sup\u003e, Kenzo Tanaka\u003csup\u003e6\u003c/sup\u003e, Kentaro Tochitani\u003csup\u003e3\u003c/sup\u003e, Makito Yaegashi\u003csup\u003e5\u003c/sup\u003e, Masayuki Chikamori\u003csup\u003e7\u003c/sup\u003e, Naohisa Hamashige\u003csup\u003e7\u003c/sup\u003e, Masayuki Ishida\u003csup\u003e7\u003c/sup\u003e, Hiroshi Nakaoka\u003csup\u003e7\u003c/sup\u003e, Norichika Aso\u003csup\u003e8\u003c/sup\u003e, Hiroyuki Ito\u003csup\u003e8\u003c/sup\u003e, Kei Matsuki\u003csup\u003e8\u003c/sup\u003e, Yoshiko Tsuchihashi\u003csup\u003e8\u003c/sup\u003e, Koya Ariyoshi\u003csup\u003e9\u003c/sup\u003e, Bhim G. Dhoubhadel\u003csup\u003e9\u003c/sup\u003e, Akitsugu Furumoto\u003csup\u003e9\u003c/sup\u003e, Sugihiro Hamaguchi\u003csup\u003e1, 9\u003c/sup\u003e, Tomoko Ishifuji\u003csup\u003e9\u003c/sup\u003e, Shungo Katoh\u003csup\u003e1,9\u003c/sup\u003e, Satoshi Kakiuchi\u003csup\u003e9\u003c/sup\u003e, Emi Kitashoji\u003csup\u003e9\u003c/sup\u003e, Takaharu Shimazaki\u003csup\u003e9\u003c/sup\u003e, Motoi Suzuki\u003csup\u003e9\u003c/sup\u003e, Masahiro Takaki\u003csup\u003e9\u003c/sup\u003e, Konosuke Morimoto\u003csup\u003e9\u003c/sup\u003e, Kiwao Watanabe\u003csup\u003e9\u003c/sup\u003e, and Lay-Myint Yoshida\u003csup\u003e10\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Department of General Internal Medicine, Ebetsu City Hospital, Hokkaido, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Department of Pulmonology, Kameda Medical Center, Chiba, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e Department of Infectious Diseases, Kameda Medical Center, Chiba, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003e Department of Laboratory Medicine, Kameda Medical Center, Chiba, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u003c/sup\u003e Department of General Internal Medicine, Kameda Medical Center, Chiba, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e6\u003c/sup\u003e Emergency and Trauma Center, Kameda Medical Center, Chiba, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e7\u003c/sup\u003e Department of Internal Medicine, Chikamori Hospital, Kochi, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e8\u003c/sup\u003e Department of Internal Medicine, Juzenkai Hospital, Nagasaki, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e9\u003c/sup\u003e Department of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e10\u003c/sup\u003e Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003cstrong\u003eWorld Health Organization. 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An individualised approach supported by machine learning\u003c/strong\u003e. \u003cem\u003eEur Respir J \u003c/em\u003e2019, \u003cstrong\u003e54\u003c/strong\u003e(6).\u003c/li\u003e\n\u003cli\u003eKim L, McGee L, Tomczyk S, Beall B: \u003cstrong\u003eBiological and Epidemiological Features of Antibiotic-Resistant Streptococcus pneumoniae in Pre- and Post-Conjugate Vaccine Eras: a United States Perspective\u003c/strong\u003e. \u003cem\u003eClinical Microbiology Reviews \u003c/em\u003e2016, \u003cstrong\u003e29\u003c/strong\u003e(3):525-552.\u003c/li\u003e\n\u003cli\u003eWanla W, Katip W, Supakul S, Apiwatnakorn P, Khamsarn S: \u003cstrong\u003eEffects of an antimicrobial restriction system on appropriate carbapenem use in a hospital without infectious diseases consultation\u003c/strong\u003e. \u003cem\u003eInt J Gen Med \u003c/em\u003e2017, \u003cstrong\u003e10\u003c/strong\u003e:443-449.\u003c/li\u003e\n\u003cli\u003eTessmer A, Welte T, Martus P, Schnoor M, Marre R, Suttorp N: \u003cstrong\u003eImpact of intravenous {beta}-lactam/macrolide versus {beta}-lactam monotherapy on mortality in hospitalized patients with community-acquired pneumonia\u003c/strong\u003e. \u003cem\u003eJ Antimicrob Chemother \u003c/em\u003e2009, \u003cstrong\u003e63\u003c/strong\u003e(5):1025-1033.\u003c/li\u003e\n\u003cli\u003eMartin-Loeches I, Lisboa T, Rodriguez A, Putensen C, Annane D, Garnacho-Montero J, Restrepo MI, Rello J: \u003cstrong\u003eCombination antibiotic therapy with macrolides improves survival in intubated patients with community-acquired pneumonia\u003c/strong\u003e. \u003cem\u003eIntensive care medicine \u003c/em\u003e2010, \u003cstrong\u003e36\u003c/strong\u003e(4):612-620.\u003c/li\u003e\n\u003cli\u003eEliakim-Raz N, Robenshtok E, Shefet D, Gafter-Gvili A, Vidal L, Paul M, Leibovici L: \u003cstrong\u003eEmpiric antibiotic coverage of atypical pathogens for community-acquired pneumonia in hospitalized adults\u003c/strong\u003e. \u003cem\u003eCochrane Database of Systematic Reviews \u003c/em\u003e2012.\u003c/li\u003e\n\u003cli\u003eKawaguchiya M, Urushibara N, Aung MS, Shinagawa M, Takahashi S, Kobayashi N: \u003cstrong\u003eSerotype distribution, antimicrobial resistance and prevalence of pilus islets in pneumococci following the use of conjugate vaccines\u003c/strong\u003e. \u003cem\u003eJ Med Microbiol \u003c/em\u003e2017, \u003cstrong\u003e66\u003c/strong\u003e(5):643-650.\u003c/li\u003e\n\u003cli\u003eHanada S, Morozumi M, Takahashi Y, Mochizuki S, Sato T, Suzuki S, Uruga H, Takaya H, Miyamoto A, Morokawa N\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eCommunity-acquired pneumonia caused by macrolide-resistant Mycoplasma pneumoniae in adults\u003c/strong\u003e. \u003cem\u003eIntern Med \u003c/em\u003e2014, \u003cstrong\u003e53\u003c/strong\u003e(15):1675-1678.\u003c/li\u003e\n\u003cli\u003eTanaka T, Oishi T, Miyata I, Wakabayashi S, Kono M, Ono S, Kato A, Fukuda Y, Saito A, Kondo E\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eMacrolide-Resistant Mycoplasma pneumoniae Infection, Japan, 2008-2015\u003c/strong\u003e. \u003cem\u003eEmerging infectious diseases \u003c/em\u003e2017, \u003cstrong\u003e23\u003c/strong\u003e(10):1703-1706.\u003c/li\u003e\n\u003cli\u003eNakao T, Kosai K, Akamatsu N, Ota K, Mitsumoto-Kaseida F, Hasegawa H, Izumikawa K, Mukae H, Yanagihara K: \u003cstrong\u003eMolecular and phenotypic characterization of Streptococcus pneumoniae isolates in a Japanese tertiary care hospital\u003c/strong\u003e. \u003cem\u003eFront Cell Infect Microbiol \u003c/em\u003e2024, \u003cstrong\u003e14\u003c/strong\u003e:1391879.\u003c/li\u003e\n\u003cli\u003eMiyashita N, Ogata M, Fukuda N, Yamura A, Ito T: \u003cstrong\u003eMacrolide-resistant Mycoplasma pneumoniae infection prevalence increases again in Osaka\u003c/strong\u003e. \u003cem\u003eRespir Investig \u003c/em\u003e2025, \u003cstrong\u003e63\u003c/strong\u003e(4):517-520.\u003c/li\u003e\n\u003cli\u003eSchweitzer VA, van Heijl I, Boersma WG, Rozemeijer W, Verduin K, Grootenboers MJ, Sankatsing SUC, van der Bij AK, de Bruijn W, Ammerlaan HSM\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eNarrow-spectrum antibiotics for community-acquired pneumonia in Dutch adults (CAP-PACT): a cross-sectional, stepped-wedge, cluster-randomised, non-inferiority, antimicrobial stewardship intervention trial\u003c/strong\u003e. \u003cem\u003eLancet Infect Dis \u003c/em\u003e2022, \u003cstrong\u003e22\u003c/strong\u003e(2):274-283.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Pretreatment variables of patients with community-acquired pneumonia in one of the datasets generated through bootstrapping of imputed datasets,\u0026nbsp;before and after propensity score matching\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"971\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 358px;\"\u003e\n \u003cp\u003eBefore matching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 384px;\"\u003e\n \u003cp\u003eAfter matching\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eBLM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eBL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eSMD\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eBLM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eBL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eSMD\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eN = 311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003eN = 2473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eN = 298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003eN = 298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eAge, year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e64.51 (20.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e76.04 (15.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e66.03 (19.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e66.82 (19.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eFemale sex\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e142 (45.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e952 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e134 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e117 (39.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eHospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Chikamori Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e6 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e484 (19.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e6 (2.0) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e44 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Ebetsu City Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e25 (8.0) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e344 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e24 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e34 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Juzenkai Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e0 (0.0) \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e339 (13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e0 (0.0) \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e24 (8.1) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Kameda Medical Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e280 (90.0) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e1306 (52.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e268 (89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e196 (65.8) \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eTreatment setting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Outpatient\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e134 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e442 (17.9) \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.570\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e122 (40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e122 (40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRisk of bacterial resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eHospitalization for more than 2 days within 3 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e29 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e500 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e29 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e26 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eResiding in a nursing home or convalescent facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e15 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e443 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e15 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e13 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eDialysis (within 30 days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e8 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e40 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e8 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e9 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eComorbidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Diabetes mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e51 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e523 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e51 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e46 (15.4) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.045\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Heart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e27 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e404 (16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e27 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e23 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eLiver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e4 (1.3) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e155 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Renal disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e27 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e282 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e26 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e26 (8.7) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Dementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e10 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e424 (17.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e9 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Malignancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e35 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e510 (20.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e35 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e35 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eAsthma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e26 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e258 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e21 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e20 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;COPD or\u0026nbsp;\u003cbr\u003e\u0026nbsp; \u0026nbsp; bronchiectasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e50 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e600 (24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e39 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e48 (16.1) \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eMedication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Oral steroids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e38 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e201 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e28 (9.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e24 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Antacids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e82 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e746 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e79 (26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e83 (27.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Sleep-inducing drugs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e29 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e315 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e29 (9.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e17 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eAspiration-associated risk factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Aspiration episodes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e39 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e708 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e39 (13.1) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e36 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Impaired consciousness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e9 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e159 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e9 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Neuromuscular diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e8 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e199 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.246\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e8 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e7 (2.3) \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eInsertion or placement of devices (e.g., nasogastric tubes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e64 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e2 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Cerebrovascular\u0026nbsp;\u003cbr\u003e\u0026nbsp; \u0026nbsp; diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e25 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e608 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e25 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e26 (8.7) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eLong-term bedridden status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e25 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e332 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e25 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e18 (6.0) \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eVital signs at diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Impaired consciousness\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e30 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e499 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e30 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e22 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Heart rate,\u0026nbsp;\u003cbr\u003e\u0026nbsp; \u0026nbsp; beats/minute\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e97.26 (17.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e96.11 (20.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e96.90 (17.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e97.65 (19.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Respiratory rate,\u0026nbsp;\u003cbr\u003e\u0026nbsp; \u0026nbsp; breaths/minute\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e21.91 (5.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e22.52 (6.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e21.96 (5.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e22.49 (6.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Systolic blood\u0026nbsp;\u003cbr\u003e\u0026nbsp; \u0026nbsp; pressure, mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e127.08 (23.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e130.18 (25.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e127.42 (23.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e128.14 (19.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Body temperature\u0026nbsp;\u003cbr\u003e\u0026nbsp; \u0026nbsp; Celsius\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e37.50 (1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e37.45 (1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e37.50 (1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e37.47 (1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eLaboratory data\u0026nbsp;\u003cbr\u003e\u0026nbsp; \u0026nbsp; at diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hematocrit, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e38.02 (5.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e36.59 (5.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e37.92 (5.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e37.88 (5.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;BUN, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e17.54 (12.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e22.39 (15.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e17.91 (13.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e17.74 (10.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Na, mEq/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e137.80 (3.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e137.62 (4.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e137.76 (3.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e137.73 (4.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Glucose, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e135.20 (59.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e139.67 (59.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e136.19 (60.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e138.73 (60.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Albumin, g/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e3.52 (0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e3.41 (0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e3.49 (0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e3.48 (0.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Pleural effusion\u0026nbsp;\u003cbr\u003e\u0026nbsp; \u0026nbsp; on chest X-ray\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e11 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e186 (7.5) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e11 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e6 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eCURB-65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e \u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e52 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e621 (25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e52 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e53 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e \u0026ge;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e15 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e129 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e15 (5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 128px;\"\u003e\n \u003cp\u003e11 (3.7) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as number (%) or mean (standard deviation).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003ePropensity score matching was conducted using 34 variables: age, sex, treatment setting (outpatient or inpatient), history of hospitalization (hospitalization for more than 2 days within 3 months before the diagnosis of CAP), residing in a nursing home or convalescent facility, dialysis (within 30 days before diagnosis), preexisting comorbidities (diabetes, heart failure, liver disease, renal disease, dementia, malignancy, asthma, and chronic respiratory disease [COPD and bronchiectasis]), prescribed drugs before admission (oral steroids, antacids, and sleeping drugs), aspiration-associated factors (aspiration episodes, impaired consciousness, neuromuscular disease, insertion or placement of devices (e.g., nasogastric tubes), cerebrovascular disease, and long-term bedridden status), vital signs at diagnosis (consciousness, heart rate, respiratory rate, systolic blood pressure, and body temperature), laboratory data at diagnosis (hematocrit, BUN, sodium, glucose, and albumin), and findings of chest X-ray (pleural effusion). An SMD of \u0026lt;0.1 among the covariates was considered an appropriate match balance.\u003c/p\u003e\n\u003cp\u003eBL, beta-lactam monotherapy; BLM, beta-lactam plus macrolide; BUN, blood urea nitrogen; CAP; community-acquired pneumonia; COPD, chronic obstructive pulmonary disease; SMD, standardized mean difference\u003c/p\u003e\n\u003cp\u003eTable 2. Microbiological test findings, including culture and polymerase chain reaction analysis results, in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"842\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eCausative pathogen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eBefore matching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eAfter matching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eBLM\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N = 311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eBL\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eN = 2473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eBLM\u003c/p\u003e\n \u003cp\u003eN = 298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003eBL\u003c/p\u003e\n \u003cp\u003eN = 298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eSputum culture performed\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e275 (88.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2305 (93.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e267 (89.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e268 (89.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e25 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e274 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e25 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e40 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eHaemophilus influenzae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e32 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e246 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e31 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e35 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eMethicillin-sensitive \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e9 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e153 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e9 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e17 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e164 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e17 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eMoraxella catarrhalis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e15 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e159 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e14 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e20 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e141 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eMethicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e78 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e6 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e72 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella oxytoca\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e14 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eSerratia marcescens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e24 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u0026nbsp;\u003c/em\u003e(ESBL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e12 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eLegionella\u003c/em\u003e \u003cem\u003epneumophila\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eUrinary antigen of \u003cem\u003eStreptococcus pneumoniae\u0026nbsp;\u003c/em\u003eperformed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e194 (62.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1446 (78.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e188 (63.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e152 (51.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e22 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e235 (9.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e22 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e25 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eUrinary antigen of\u003cem\u003e\u0026nbsp;Legionella pneumophila\u0026nbsp;\u003c/em\u003eperformed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e180 (57.9)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1109 (48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e176 (59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e123 (41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003ePrompt antigen\u003cem\u003e\u0026nbsp;\u003c/em\u003eof influenza virus performed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e39 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e467 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e39 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e53 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003epositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e6 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e19 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e6 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eSputum bacterial PCR performed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e209 (67.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1943 (78.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e205 (68.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e206 (69.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e44 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e394 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e44 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e53 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eHaemophilus influenzae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e51 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e280 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e50 (16.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e46 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eMoraxella catarrhalis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e47 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e222 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e46 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e21 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eMycoplasma pneumoniae\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e22 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e31 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e20 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e8 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eChlamydia pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e4 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eLegionella pneumophila\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eSputum viral PCR performed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e211 (67.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1943 (78.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e207 (69.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e205 (68.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHuman rhinovirus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e15 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e197 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e14 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e20 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eRespiratory syncytial virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e6 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e73 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e6 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e6 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eInfluenza A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e7 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e58 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e7 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e12 (4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHuman parainfluenza virus type 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e40 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e6 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHuman metapneumovirus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e7 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e30 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e7 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHuman parainfluenza virus type 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e21 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eInfluenza B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e15 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHuman parainfluenza virus type 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e7 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHuman coronavirus (229E/OC43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e22 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHuman adenovirus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eHuman bocavirus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e2 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eBlood culture performed\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e193 (62.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1556 (62.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e187 (62.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e173 (58.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e15 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e13 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eMethicillin-sensitive \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e14 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e12 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eHaemophilus influenzae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e3 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e3 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia coli\u0026nbsp;\u003c/em\u003e(ESBL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e2 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003e\u003cem\u003eMoraxella catarrhalis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e1 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 263px;\"\u003e\n \u003cp\u003eMethicillin-resistant \u003cem\u003eStaphylococcus aureus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e2 (0.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 263px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 133px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 130px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 15px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as number (%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eIn the analysis of sputum and blood cultures, only pathogens assessed as clinically pertinent to pneumonia were reported. Bacteria of ambiguous clinical significance, uncommon bacteria, and organisms recognized as normal flora were excluded from the report.\u003c/p\u003e\n\u003cp\u003eBLM, beta-lactam plus macrolide; BL, beta-lactam monotherapy; ESBL, extended spectrum beta-lactamase; PCR, polymerase chain reaction\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3 Antibiotics used in this study participants in one of the datasets generated through bootstrapping of imputed datasets, before and after propensity score matching\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eAntibiotics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eBefore matching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eAfter matching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eBLM\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N = 311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eBL\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N = 2473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eBLM\u003c/p\u003e\n \u003cp\u003eN = 298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eBL\u003c/p\u003e\n \u003cp\u003eN = 298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eBeta-lactam\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Ceftriaxone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e139 (44.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e794 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e132 (44.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e102 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Ampicillin-sulbactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e13 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e715 (28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e13 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e64 (21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Piperacillin-tazobactam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e46 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e450 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e46 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e35 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Amoxicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e62 (19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e207 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e58 (19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e45 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Amoxicillin-clavulanate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e57 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e204 (8.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e53 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e45 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Cefotaxime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e10 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e79 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e11 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Meropenem\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e45 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Cefditoren-pivoxil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e36 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e141 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e35 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e36 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Cefepime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e6 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e34 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e6 (2.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e4 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Ampicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e19 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Benzylpenicillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e5 (0.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eCefotiam\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e2 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e12 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e2 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003ePiperacillin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e9 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e1 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Others\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e11 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e87 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e10 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003eMacrolide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Azithromycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e300 (96.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e287 (96.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Clarithromycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e8 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e8 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 233px;\"\u003e\n \u003cp\u003e\u0026nbsp; Erythromycin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e3 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as number (%).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eOwing to duplications, the total number of each column exceeded the number of patients in each group.\u003c/p\u003e\n\u003cp\u003eBLM, beta-lactam plus macrolide; BL, beta-lactam monotherapy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 Primary and secondary endpoints for the patients with community-acquired pneumonia treated with beta-lactam plus macrolide dual therapy and beta-lactam monotherapy\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eBLM (N = 285)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eBL (N = 285)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eAbsolute difference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePrimary endpoints\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eDeath, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e5.06 (2.73 \u0026ndash; 7.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e4.98 (2.36 \u0026ndash; 8.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.00 (\u0026minus;3.73 to 3.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Recovery, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e91.79 (88.43 \u0026ndash; 94.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e91.69 (87.73 \u0026ndash; 95.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.00 (\u0026minus;4.48 to 4.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eSecondary endpoints\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Duration of antibiotic treatment (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e8.97 (8.46 \u0026ndash; 9.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e9.93 (9.01 \u0026ndash; 17.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026minus;0.99 (\u0026minus;8.20 to 0.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eLength of hospital stay (days)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e17.72 (15.29 \u0026ndash; 20.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e20.30 (17.31 \u0026ndash; 24.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026minus;2.59 (\u0026minus;6.99 to 1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues in parentheses indicate the 95% CI. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eN represents the point estimates derived from the median of the bootstrap results. The median and the 95% CI for N are 285 (253\u0026ndash;318).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eRegarding the length of hospital stay, the number of cases was 166 (95%CI 140\u0026ndash;192) in both the BLM and BL groups, as these endpoints were assessed exclusively in hospitalized patients.\u003c/p\u003e\n\u003cp\u003eBLM, beta-lactam plus macrolide; BL, beta-lactam monotherapy; CI, confidence interval\u003c/p\u003e\n\u003cp\u003eTable 5 Primary and secondary endpoints for patients with a CURB-65 score of 3 or above who were treated for community-acquired pneumonia with beta-lactam plus macrolide dual therapy and beta-lactam monotherapy\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eBLM (N = 29)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eBL (N = 29)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003eAbsolute difference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePrimary endpoints\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eDeath, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e12.00 (0.00 \u0026ndash; 25.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e13.33 (0.00\u0026ndash;29.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.00 (\u0026minus;20.00 to 16.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Recovery, %\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e82.86 (68.00\u0026ndash;95.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e83.33 (66.67\u0026ndash;96.42)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.00 (\u0026minus;20.00 to 20.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eSecondary endpoints\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Duration of antibiotic treatment (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e9.62 (7.82\u0026ndash;11.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e10.52 (8.14\u0026ndash;14.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026minus;0.92 (\u0026minus;5.07 to 2.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eLength of hospital stay (days)\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e24.06 (14.72\u0026ndash;35.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e23.57 (14.93\u0026ndash;36.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.28 (\u0026minus;15.11 to 14.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues in parentheses indicate the 95% CI.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eN represents the point estimates derived from the median of the bootstrap results. The median and the 95% CI for N are 29 (16\u0026ndash;44).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eRegarding the length of hospital stay, the number of cases was 21 (95%CI 10\u0026ndash;34) in both the BLM and BL groups because these endpoints were assessed exclusively in hospitalized patients.\u003c/p\u003e\n\u003cp\u003eBLM, beta-lactam plus macrolide; BL, beta-lactam monotherapy; CI, confidence interval\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anti-Bacterial Agents, beta-Lactams, Macrolides, Pneumonia, Propensity score","lastPublishedDoi":"10.21203/rs.3.rs-5738269/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5738269/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eCommunity-acquired pneumonia (CAP) substantially contributes to mortality and morbidity globally, with beta-lactams being a primary therapeutic agent. The efficacy of adding macrolides to beta-lactams in CAP treatment remains controversial. Here, we evaluated whether beta-lactam plus macrolide treatment (BLM) is more effective than beta-lactam monotherapy (BL) for preventing CAP mortality.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe performed a secondary data analysis of a multicenter prospective cohort study involving patients diagnosed with CAP at four institutions. We selected patients treated with either BLM or BL. The primary endpoint was the outcome at the end of the observation period (death or recovery). The secondary endpoints were the length of hospital stay and duration of antibiotic use. Multiple imputations with bootstrapping were used to address missing data. Background characteristics were adjusted via propensity score matching.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOf the 3,470 patients initially included in the study, 2,784 were analyzed; 306 received BLM and 2,478 received BL. The average observation period for the groups was 17.0 (\u0026plusmn;\u0026thinsp;18.4) and 24.0 days (\u0026plusmn;\u0026thinsp;24.6), respectively. After propensity score matching, mortality was similar between the groups (5.06% for BLM vs. 4.98% for BL; difference 0.00, 95% confidence interval [CI]\u0026thinsp;\u0026minus;\u0026thinsp;3.73 to 3.71), as were recovery rates (91.79% for BLM vs. 91.69% for BL; difference 0.00, 95% CI \u0026minus;\u0026thinsp;4.48 to 4.82). In the subgroup analysis of patients with severe CAP, mortality was 12.00% for BLM vs. 13.33% for BL (difference 0.00, 95% CI \u0026minus;\u0026thinsp;20.00 to 16.13), and recovery rates were 82.86% vs. 83.33% (difference 0.00, 95% CI \u0026minus;\u0026thinsp;20.00 to 20.00).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eSimilar outcomes were observed in the mortality and recovery rates between the BLM and BL groups among patients with CAP. Clinicians should thoughtfully weigh the benefits of BLM against the potential risks, including adverse effects and antimicrobial resistance, when managing patients with CAP.\u003c/p\u003e\u003ch2\u003eTrial registration:\u003c/h2\u003e\u003cp\u003eThis study protocol was registered with the University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR), identifier UMIN000006909, on December 19, 2011.\u003c/p\u003e","manuscriptTitle":"Beta-lactam plus macrolide treatment versus beta-lactam monotherapy for community-acquired pneumonia: a propensity score analysis using data from a multicenter prospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-12 14:45:14","doi":"10.21203/rs.3.rs-5738269/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-16T11:48:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-16T01:26:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-10T14:25:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263877666754733380067477752895089041457","date":"2025-10-10T01:02:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300766308982601199045906274341040007558","date":"2025-10-09T20:49:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-09T17:36:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12857544018412180603443955652331698247","date":"2025-10-09T17:26:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-09T15:58:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-15T19:31:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-01T22:31:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-06-29T07:53:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6f3c51ee-1ecc-47cb-bc22-5894a790ede4","owner":[],"postedDate":"October 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T16:04:52+00:00","versionOfRecord":{"articleIdentity":"rs-5738269","link":"https://doi.org/10.1186/s12879-025-12408-x","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2025-12-29 15:57:03","publishedOnDateReadable":"December 29th, 2025"},"versionCreatedAt":"2025-10-12 14:45:14","video":"","vorDoi":"10.1186/s12879-025-12408-x","vorDoiUrl":"https://doi.org/10.1186/s12879-025-12408-x","workflowStages":[]},"version":"v1","identity":"rs-5738269","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5738269","identity":"rs-5738269","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}