High utility of BALF Metagenomic Next-Generation Sequencing Approach for Etiological Diagnosis of Pneumonia

High utility of BALF Metagenomic Next-Generation Sequencing Approach for Etiological Diagnosis of Pneumonia | 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 High utility of BALF Metagenomic Next-Generation Sequencing Approach for Etiological Diagnosis of Pneumonia Lingyu Jiang, Yonglong Zhong, Shulin Xiang, Lin Han, Meng Zhang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4175027/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Nov, 2024 Read the published version in BMC Infectious Diseases → Version 1 posted 4 You are reading this latest preprint version Abstract Background : For patients with pneumonia, rapid detection of pathogens is still a major global problem in clinical practice because traditional diagnostic techniques for infection are time-consuming and insensitive. Metagenomic next-generation sequencing (mNGS) is a novel technique that has the potential to improve pathogen diagnosis. In this study, we aimed to explore the microbiological diagnostic ability of mNGS compared with that of conventional culture in pneumonia patients and to explore the best opportunityto test. Methods: A prospective study from June 2020 to June 2021 was performed at a tertiary teaching hospital in China, and 56 pneumonia patients were included among all adult patients with a clinical diagnosis of pneumonia. Blood and bronchoalveolar lavage fluid (BALF) samples were taken for simultaneous mNGS and conventional culture testing. Results: All 56 patients underwent both conventional culture and mNGS, 37 of whom were diagnosed with severe pneumonia and 17 of whom were diagnosed with nonsevere pneumonia. The top three pathogenic bacteria detected by mNGS were Acinetobacter baumannii , Klebsiella pneumoniae and Pseudomonas aeruginosa . Enterococcus faecium was detected more frequently in the non-severepneumonia group (4 vs. 0, p<0.05). The findings revealed that the detection rate of mNGS (84%) was superior to that of conventional culture methods (48%). Notably, the percentage of mNGS-positive BALF samples (46/56, 82.14%) was significantly greater than that ofblood samples (27/56, 48.21%). The etiological comparison demonstrated that mNGS-positive samples for which clinical approval was obtained tended to be associated with a more normalized temperature, lower PCO2 levels, and a higher SOFA score thanmNGS-negative samples (p= 0.022, p = 0.0.028, and p = 0.038, respectively). Conclusions: In this study, we discovered that the etiology of lung infections frequently involves multiple pathogens. mNGS of BALF is instrumental for detecting nonviral pathogens associated with lung infections. Although the rate of positive blood NGS results is significantly influenced by various clinical factors, for patients suspected of having viral, Legionella, or tsutsugamushi infections, plasma mNGS could serve as a complementary diagnostic tool. Next-generation sequencing Diagnostic Pneumonia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Pulmonary infections are the most common and overwhelming infectious disease, and severe pneumonia is associated with severe morbidity and mortality among hospitalized patients, especially aged patients, despite advances in rapid diagnostic tests, newer treatment options and vaccine strategies(1, 2). The success of treating lung infections hinges on selecting the appropriate antimicrobial agent. Rapid, sensitive, and specific detection of the infectious pathogen is crucial for determining the clinical progression and outcome of a patient with sepsis. Furthermore, early failure to identify pathogens is one of the reasons for the high mortality rate of pneumonia(3). As a principal method of pathogen detection, microbiology laboratories play a vital role in detecting infections by means of microscopic examination, culture, identification, drug sensitivity and so on. However, most of these methods are time-consuming and are hyposensitive(4). This may be partly because of the frequent use of prior antibiotic therapy before pathogen detection test sampling. Hence, initial empirical antibiotic therapy is often empirical and nonspecific for severe pneumonia, which may lead to delays in targeted anti-infective treatment, increasing the prevalence of antibiotic-resistant microorganisms, and impeding effective therapy. These challenges have accelerated the exploration of accurate diagnostic strategies. As a new technique, metagenomic next-generation sequencing (mNGS) has been widely used in clinical practice in recent years (5–7). Since the application of mNGS, a greater variety of rapid etiological diagnoses of complex critical cases involving bacteria, viruses, fungi, and parasites have been reported simultaneously by untargeted sequencing of DNA/RNA than by conventional culture and blood culture methods(8, 9). Especially for severely ill patients, the mNGS diagnostic technique can aid in the identification of infectious agents and enhance diagnostic accuracy and therapeutic effectiveness, potentially resulting in favorable clinical outcomes (10) . As an evolving diagnostic tool, there are still deficiencies in some states. The value of BALF and blood mNGS in pulmonary infection remains to be further validated, and whether there are differences in their roles needs to be verified, which poses new challenges for clinical treatment. Hence, identifying the best opportunity and optimal specimens for etiological tests is crucial. However, at present, there is no exploration or research on the best timing for mNGS detection in pneumonia patients. Our study was undertaken to evaluate and compare the diagnostic performance of mNGS for detecting pathogens, including bacteria, fungi, and viruses, in pneumonia patients with that of conventional methods and to explore the best method for diagnosing pneumonia to avoid blindly performing expensive tests. 2. Materials and Methods 2.1. Patient Population and Study Design This single-center prospective observational study evaluated data on pneumonia patients admitted to the Peoples Hospital of Guangxi Zhuang Autonomous Region, which is a tertiary hospital with 28 beds in the Department of Critical Care Medicine, from June 2019 to June 2021. The inclusion criteria were (1) age ≥ 18 years, (2) ICU stay > 24 h, and (3) proven or suspected pneumonia. (4) A sampling interval of less than 24 hours was defined as paired mNGS results and conventional culture results in our study. The exclusion criteria were incomplete clinical data, including microbiological data. (2) Failure to acquire a enough sample for paired mNGS and conventional culture analysis during ICU admission. (3) Patients who failed to meet the inclusion criteria. Patient (4) refused to provide written consent. Informed consent was obtained from all patients involved. In addition, because only mNGS was used to sequence DNA in this study, RNA viruses were not detected for analysis. Informed consent was obtained from all patients involved. A positive test result was defined as a comparison with the final confirmed pathogen, including any of the final pathogens. In this study, the final pathogenic diagnosis and accuracy of the test results were determined according to the following standards based on clinical agreement: The criteria for etiological diagnosis and the determination of test results. clinical agreement • If the positive result of mNGS is consistent with the findings of conventional culture, the pathogen can be confirmed. • If the positive result of mNGS is consistent with part of the findings from conventional culture and receives clinical agreement. • When mNGS is positive while conventional culture results are negative, but the mNGS result is clinically agreed upon, it provides supportive evidence for the presence of the pathogen. • If the positive result of mNGS is inconsistent with the findings of conventional culture, but the NGS result is clinically agreed upon, it still serves as supportive evidence for the presence of a specific pathogen. • If both mNGS and conventional culture results are negative, but this is clinically agreed upon, indicating a reliable result. clinical ambiguity • The results of mNGS can be either negative or positive despite negative findings from conventional culture. However, the clinical significance of these results remains unclear. clinical disagreement • Despite a positive mNGS result in the absence of positive conventional culture findings, the result remains inconsistent with clinical considerations. • The positive result of mNGS was discordant with both conventional culture results and clinical considerations. • Despite both mNGS and conventional culture results being negative, neither finding was consistent with clinical considerations. • Negative of mNGS with positive of conventional culture results, neither finding was consistent with clinical considerations. 2.2 Data collection In this study, we gathered and documented the demographic and clinical profiles of the patients enrolled, including their age, initial symptoms, comorbid conditions, inflammatory biomarkers, duration of antibiotic therapy prior to the pathogen test, duration of ICU stay, Acute Physiology and Chronic Health Evaluation (APACHE) II score, Sequential Organ Failure Assessment (SOFA) score, and in-hospital mortality. Suspected infected samples were then collected for analysis via metagenomic next-generation sequencing (mNGS). In this study, conventional culture methods, including BALF and blood culture, were used for pneumonia patients. These cultures were performed within 24 hours prior to and following the corresponding mNGS test. Given that viruses are not typically the predominant pathogens in pneumonia, the detection of viruses through mNGS was not included in the clinical approval process of this study. 2.3 Statistical analysis Continuous variables are expressed as the means ± SDs, medians, interquartile ranges (IQRs), or proportions (absolute and relative frequencies), as appropriate. The t test or Mann–Whitney U test was used to compare continuous variables, and the χ2 test or Fisher’s exact test was used to compare categorical variables. The sensitivity, specificity, PPV, NPV, and consistency were also statistically significant. Two machine learning methods, Lasso and random forest, were used to find the clinically appropriate time to submit the test. A p value ≤ 0.05 was considered to indicate statistical significance. Statistical analysis was performed by using IBM SPSS Statistics, version 24 (IBM Corp., Armonk, NY, United States. 3. Results 3.1 Patient Characteristics During the study period, 77 pneumonia patients who underwent mNGS for infection at least two different sites were admitted to the ICU. Among these patients, five underwent repeated tests, and only the first test result for each of these patients was included in the final analysis. The following paired samples were excluded from this study: 2 blood and ascites samples, 2 blood and urine samples, 2 cerebrospinal fluid and BALF samples, 1 blood and tissue sample, 1 blood and cerebrospinal fluid sample, and 1 cerebrospinal fluid and BALF specimen. Thus, a total of 56 patients who had both blood and BALF samples tested using mNGS were included in the final analysis. These patients constituted our study cohort and were characterized by paired blood and BALF mNGS results ( Table 1 ) . The median age of these 56 patients, including 44 males, was 59 years, with the majority being over 40 years old (45/56). The common symptoms presented by these patients included dyspnea (46.4%), fever (46.4%), and cough (32.1%). Table 1 The baseline characteristics of the 56 patients enrolled in the study Characteristic Value (median or no.(%) ) Median Age 59 years distribution 19 ~ 40 years 11(19.6%) 40–60 years 19(32.2%) >60 years 26(46.4%) Male sex 44(78.6%) Onset symptoms Fever 26(46.4%) Dyspnea 26(46.4%) Cough 18(32.1%) Comorbidity Diabetes Mellitus 9(16.1%) Liver disease 4(7.1%) Cerebrovascular disease 9(16.1%) Hypertension 20(35.7%) Kidney disease 5(8.9%) Immunocompromised or 10(17.9%) Solid cancer 3(5.3%) Severity score APACHE II 23(19.5,28) SOFA 8(4,10) SOFA, Sequential Organ Failure Assessment. APACHE II, The Acute Physiology and Chronic Health Evaluation II 3.2 Evaluation of the performance of mNGS in different specimens In all 56 patients enrolled in the study, the percentage of positive mNGS results (84%, reaching 84%) was significantly greater than the percentage of positive culture results (only 48%). The mNGS method exclusively detected up to 23 positive cases, accounting for 41% of the total 56 patients. This significantly surpassed the culture results, which were only obtained for 3 patients, representing 5% of the patients. As illustrated in Fig. 1B. In the enrolled cohort, the clinical acceptance of mNGS for BALF samples (45/56, 80.36%) was obviously greater than that for blood samples (27/56, 48.21%). Furthermore, the combined use of mNGS from BALF and blood resulted in the highest clinical acceptance rate (83.93%, 47/56) compared to each individual sample type ( Table 2 and Fig. 2) . Moreover, there were fewer positive detection results from BALF and blood plasma culture than from BALF and blood mNGS for bacteria on the same day. The positive rate of BALF culture was also greater than that of blood culture (39.58% vs 25.00%). ( Table 3 and Fig. 3) . Table 2 comparative analysis of clinical acceptance of mNGS results from different testing samples Samples Clinical acceptance Clinical disapproval Equivocal Blood 48.21% (27/56) 41.07% (23/56) 10.71% (6/56) BALF 80.36% (45/56) 8.93% (5/56) 10.71% (6/56) Blood + BALF 83.93% (47/56) 5.36% (3/56) 10.71% (6/56) Table 3 comparison of the examination of efficacy between mNGS and culture samples mNGS Culture Culture(a week before and after NGS) Blood Pos 48.21% (27/56) 10.53% (2/19) 25.00% (7/28) Neg 51.79% (29/56) 89.47% (17/19) 75.00% (21/28) BALF Pos 82.14% (46/56) 30.77% (8/26) 39.58% (19/48) Neg 17.86% (10/56) 69.23% (18/26) 60.42% (29/48) 3.3 Microbiological diagnostic performance of mNGS Codetection of multiple pathogens was observed in 24 patients using both culture and mNGS methods. In accordance with microbiological and clinical protocols, the identified pathogens were categorized as illustrated in Fig. 4. The three predominant pathogenic bacteria identified by mNGS were Acinetobacter baumannii , Klebsiella pneumoniae , and Pseudomonas aeruginosa . Pathogen distribution and differences in blood samples between the severe pneumonia group and the non-severe pneumonia group Among the 56 patients, 37 were diagnosed with severe pneumonia and 14 with non-severe pneumonia; the remaining 5 patients were excluded from the study because their condition was complicated by infection at other sites. According to the results of blood mNGS, Enterococcus faecium was detected more frequently in the non-severe pneumonia group (4 vs. 0, p = 0.0040). Similarly, compared with the final etiological diagnosis, Enterococcus faecium was a common pathogen in the non-severe pneumonia group (4 vs. 1, p = 0.0167) after excluding the detected viruses. However, no significant differences were identified among the other pathogens, as shown in Fig. 5 . 3.4. The clinical significance of simultaneously detecting mNGS in BALF and blood samples for pathogen identification in severe pneumonia patients Among these paired patients, one or more pathogens were detected in the BALF specimens of 22 individuals at a higher frequency than in their blood samples. By comparing the NGS results from blood and BALF in the severe pneumonia group, we found that 39.28% (22/56) of the patients had the same pathogen detected in both the BALF and blood samples. From these samples, we extracted the common pathogens and their normalized read counts across the two specimens. Then, we compared the abundance of pathogens detected in different samples, aiming to identify the most suitable specimens for detecting specific pathogens. We observed a greater abundance of pathogenic bacteria, including Legionella and Tsutsugamushi, as well as viral reads, in the blood samples. Conversely, Klebsiella pneumoniae , Pseudomonas aeruginosa , Acinetobacter baumannii , and Jaegeri lung were more frequently detected in BALF samples. (Supplemental Table 4) 3.5 Exploring the best opportunity for mNGS in pneumonia patients To reduce the negative test rate, we investigated the optimal disease status for conducting mNGS. A comprehensive analysis of 26 serological indicators was performed on the clinically confirmed positive mNGS results. The findings revealed that positive blood mNGS results, which were clinically confirmed, were more likely to be associated with lower temperature, lower PCO2 and higher SOFA scores than negative results (p = 0.022, 0.028 and 0.038, respectively). However, there were no significant differences in the serological indicators detected by BALF mNGS. (Table 5 ) Table 5 The correlation between positive rate of NGS detection and clinical indicators serological indicators P_BALF mNGS P_Blood mNGS T max 0.06368 0.02235 Pro-BNP 0.07186 0.60840 CRP 0.10390 0.78880 PaO2/FiO2 0.10400 0.36020 CK 0.11430 1.00000 WBC 0.16750 1.00000 LYMPH 0.21340 0.07194 NEUT 0.24770 0.48430 HGB 0.39770 0.86330 FiO2 0.40310 0.30550 PLT 0.50100 0.26140 Urea 0.24950 0.19890 Cr 0.58430 0.25370 cTnI 0.54930 0.86920 CK-MB 0.95450 0.60390 pH 0.31840 0.50200 PO2 0.67840 0.34700 PCO2 0.71210 0.02751 LAC 0.72920 0.85860 ALT 0.80090 0.22850 AST 0.33380 0.89240 ALB 0.96350 0.10080 IL6 0.83170 0.19110 PCT 0.17340 0.36820 APACHE II 0.36090 0.78790 SOFA 0.57300 0.03750 4. Discussion Pneumonia is a common disease involving the alveoli and the distal bronchus of the lung tree in acute respiratory infection patients. Over the past few years, the widespread use of broad-spectrum antibiotics has increased the complexity of the drug resistance spectrum of CAP pathogens, rendering the diagnosis and treatment of CAP increasingly challenging. The pathogen diagnosis of severe pneumonia has always been a challenging issue that is especially common in patients with chronic diseases or who have been exposed to antibiotics and use ventilators. It has been demonstrated that the standard methods for detecting pathogenic microorganisms, which involve bacterial smears, cultures, or nucleic acid testing from pharyngeal swabs, sputum, or bronchoalveolar lavage fluid (BALF), exhibit restricted efficacy and are capable of identifying pathogenic microorganisms in only 25–40% of patients (11–13) . This means that up to 50% of pneumonia patients have an unknown etiological diagnosis according to traditional etiological methods. Therefore, timely, fast and accurate identification of multiple pathogens remains invaluable for successful management of these patients. Clinicians have been persistently endeavoring to secure positive etiological outcomes, exploring the efficacy and implications of various specimen tests. Research indicates that blood cultures are not advisable even in severe cases of pulmonary infections, as the positive rate is extremely low (14, 15) . The guidelines for pneumonia are continuously being updated. The new guidelines have established additional criteria for determining the necessity of conducting lower respiratory tract and blood specimen testing in cases of pulmonary infections. Specifically, the 2019 edition of the American IDSA/ATS guidelines advises against routine BALF and blood culture testing. Instead, it advocates for lower respiratory tract smear and culture, as well as blood culture pathogen detection, only in specific scenarios: for hospitalized patients with severe pneumonia, those at risk of MRSA and Pseudomonas aeruginosa infection (including those with past infections), and patients who have been hospitalized in the last 90 days and have undergone parenteral antimicrobial therapy (16) . The updated recommendations in the guidelines are primarily motivated by the fact that cultures fail to alter patient outcomes, the relatively low positive rate of cultures, the potential for contaminated bacteria to contribute to inappropriate antimicrobial use, and the likelihood of prolonged treatment durations due to positive blood cultures. These factors highlight the inherent limitations of traditional pathogen detection methods. Nevertheless, the guidelines on the potential value of mNGS testing are lacking. This study demonstrated that mNGS offers superior pathogen detection and significantly more positive results in BALF and blood mNGS than traditional cultures of corresponding specimens, which is in line with the findings of Fei Xie et a l(10) . Even compared with the combined detection methods employing traditional techniques such as BALF culture, PCR, and antibody detection, the pathogen detection rate achieved by mNGS in BALF stands notably higher at 84.5%, surpassing the rate of 26.8% (13) . In cases of pulmonary infection, the culture results of BALF have always been greater than those of blood cultures, indicating a significant difference (17). We simultaneously conducted NGS on both BALF and blood samples from 56 patients, and the comparison of the results showed that the percentage of positive BALF samples was significantly greater than that of positive blood samples (80.36% vs. 48.21%). The results of this study also confirm the findings of Xu Chen's research (11) . According to the published literature, the percentage of positive mNGS results was as high as 84%, which was greater than that of traditional culture methods for both BALF and blood, and antibiotic exposure did not affect the percentage of positive mNGS results, which was similar to the results of previous studies (18) . For patients with pulmonary infection, BALF NGS is an important clinical detection method for identifying pathogenic bacteria. Given the vast amount of sequence information obtained through mNGS and the diverse nature of pathogen species, the interpretation of these reports can be extremely difficult, increasing the risk of obtaining false positive results(19). To date, there have been no rigorous standards established to differentiate between pathogens detected by mNGS that are truly pathogenic, colonized, or merely false positives. To address this issue, we combined all pathogen detection results with potentially useful information that may aid in the diagnosis of pulmonary infection pathogens, such as serum immune tests, β-glucan tests, galactomannan antigen tests, and many other clinical examinations. Additionally, two deputy directors or higher-ranking doctors have conducted a comprehensive clinical interpretation of all test results to determine the authenticity and reliability of the final pathogen detection results, thereby avoiding false positive rates. To our knowledge, this study is the first to evaluate the diagnostic value of NGS using clinically accepted criteria as the gold standard. In our study cohort, the clinical acceptance rate of mNGS for BALF samples (45/56, 80.36%) was significantly greater than that for blood samples (27/56, 48.21%). Ten patients had negative BALF test results, which was inconsistent with the clinical findings. In one patient, Acinetobacter baumannii was detected but was colonized based on clinical evaluation. When the BALF and blood mNGS results were combined, the clinical acceptance rate (83.93%, 47/56) was greater than that of either method alone. For patients with respiratory infections, the positive rate and clinical acceptance of BALF culture are greater, making it more suitable for the clinical diagnosis of pneumonia. Additionally, this underscores the need for promptly identifying the source of infection in various locations and promptly collecting pathogens from the infected site for corresponding testing in patients with infection. Interestingly, our data revealed for the first time that the rate of positive blood NGS results was greater than that of traditional BALF pathogen detection (48.21% vs 39.58%). Patients with severe pneumonia are prone to bloodstream infections. Blood NGS is an alternative test when BALF specimens are not available. As bronchoscopy for collecting BALF samples is an invasive procedure, we recommend that patients with compromised cardiopulmonary function who may not tolerate this procedure should consider blood NGS testing as an alternative to promptly determine the etiology and minimize the risk of serious complications. With the increasing clinical application of metagenomic testing, our understanding of the etiology of infectious diseases is likely to include a more comprehensive range of unculturable infectious agents and coinfections. A significant advantage of the metagenomic NGS method lies in its ability to identify numerous potential infectious agents in a single test, leading to improved clinical outcomes. In this study, 24 patients (42.86%) had mixed infections, and the optimal anti-infective treatment plan was adjusted based on these findings. Among the mixed infections, bacterial-fungal infections (44.3%) and bacterial-fungal-viral infections (35.7%) were relatively common (10) . This finding suggests that a significant proportion of patients with pneumonia may have complex microbial infections involving the presence of multiple pathogens. Such codetections can provide valuable insights into the pathogenesis of the disease and may inform more targeted therapeutic strategies. Simultaneously, we observed that Legionella, tsutsugamushi disease, and viral reads are more prevalent in blood samples. Conversely, Klebsiella pneumoniae , Pseudomonas aeruginosa , and Acinetobacter baumannii are more readily detectable in BALF. mNGS still has several limitations. Similar to traditional blood cultures, the yield of mNGS may be affected by the time of sample acquisition. A previous study by Grumaz et al (20) . showed that the positive rate of mNGS results remained constant at different time points after sepsis onset, while the positive rate of blood cultures decreased at later time points. Another study also indicated that mNGS is less affected by prior antibiotic exposure. A study by Wang et al (21) demonstrated that mNGS exhibited greater sensitivity than traditional methods in individuals with a higher cumulative steroid dosage, but the positive rate gradually decreased with increasing cumulative steroid dosage. This leads us to speculate that the percentage of positive blood samples may be related to the patient's immune and inflammatory status. The length of hospital stay is also a factor that influences the positive detection rate(22). The results showed that compared to patients with negative blood NGS results, patients with positive blood mNGS results had lower body temperature, lower PCO2, and higher SOFA scores (p = 0.022, 0.028, and 0.038, respectively). These findings suggest that the internal environmental status of patients is affected by blood NGS and that blood NGS should be performed as soon as possible when there is significant organ dysfunction to clarify the etiology. However, there were no significant changes in the serological indicators detected by mNGS of the BALF specimens. This may be related to the fact that this study focused on lung infections, which primarily occur through respiratory tract transmission. The results of BALF may be influenced by factors such as specimen collection. However, because of the low number of reported cases in the literature and the limited number of available studies, further investigations are needed in the future. This study has the following limitations. First, the sample size was relatively small. To ensure the consistency of paired blood and BALF samples, we excluded patients whose mNGS blood and BALF samples were collected on different days. Second, we did not distinguish between hospital-acquired and community-acquired pneumonia. For hospital-acquired pneumonia, the use of anti-infective agents often reduces the positive rates of both routine testing and mNGS to some extent. Third, considering that it is difficult to determine mixed viral infections, our study analyzed only bacteria and fungi, meaning that viruses that can also cause pneumonia were excluded, which may have affected the sensitivity of NGS. Fourth, as this study was retrospective, we analyzed only the impact of clinical laboratory indicators on NGS results and were unable to delve deeply into the operational impact of specimen collection. Overall, by comparing and analyzing the etiological test results of blood and BALF samples from patients with lung infections, this study revealed that the etiologies of lung infections are often mixed. Among the current detection methods, BALF mNGS has the highest sensitivity for identifying nonviral pathogens in lung infections. At the same time, we suggest that when BALF samples cannot be obtained, blood NGS can also be a valuable detection method for identifying the etiology, especially when Legionella, tsutsugamushi disease, and viruses are suspected to be the causative agents. Additionally, although we analyzed clinical indicators that may affect negative NGS results, there are certain limitations, and further large-sample studies are needed to increase the rate of positive mNGS results. Declarations Acknowledgements We thank the patients for cooperating with our investigation and acknowledge the professionalism and compassion demonstrated by all the healthcare workers involved in patients’ care. Funding The Guangxi Science and Technology Base and Talent Special Project (grant no. 2021AC04001), the Youth Science Foundation Project of Guangxi (grant no. 2023GXNSFBA026096) and the Guangxi Health and Wellness Commission Self-funded Project (grant no. Z- A20220085) provided funding for this study. Competing interests The authors declare that they have no conflict of interest. Ethics approval and consent to participate All procedures performed in studies involving human participants were performed in accordance with the ethical standards of the Ethics Committee of the People’s Hospital of Guangxi Zhuang Autonomous Region and the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Informed consent was obtained from the patient. Availability of data and material (data transparency) Not applicable Informed Consent All authors approved the final version submitted for publication. Authors’ contribution All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work. Jiang, Ling Yu: Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing – original draft. Zhong, Yong Long: Software, Validation, Visualization, Formal analysis Xiang, Shu Lin: Supervision, Validation, Writing – review & editing. Han, Lin: Conceptualization, Project administration, Methodology, Project administration, Supervision Meng Zhang: Acquisition of data, Data curation, Resources, Investigation Jianliang Li: Acquisition of data, Data curation, Resources, Investigation Guanhua Rao: Software, drafting, Formal analysis References Anderson R, Feldman C. The Global Burden of Community-Acquired Pneumonia in Adults, Encompassing Invasive Pneumococcal Disease and the Prevalence of Its Associated Cardiovascular Events, with a Focus on Pneumolysin and Macrolide Antibiotics in Pathogenesis and Therapy. International Journal of Molecular Sciences. 2023; 24(13). Tufa, Denning. The Burden of Fungal Infections in Ethiopia. Journal of Fungi. 2019; 5(4). Garcia-Vidal C, Carratalà J. Early and Late Treatment Failure in Community-Acquired Pneumonia. Seminars in Respiratory and Critical Care Medicine. 2009; 30(02):154-60. Afshari A, Schrenzel J, Ieven M, et al. 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The American Journal of Medicine. 2019; 132(10):1233-8. Afshar N, Tabas J, Afshar K, et al. Blood cultures for community‐acquired pneumonia: Are they worthy of two quality measures? A systematic review. Journal of Hospital Medicine. 2009; 4(2):112-23. Metlay JP, Waterer GW, Long AC, et al. Diagnosis and Treatment of Adults with Community-acquired Pneumonia. An Official Clinical Practice Guideline of the American Thoracic Society and Infectious Diseases Society of America. American Journal of Respiratory and Critical Care Medicine. 2019; 200(7):e45-e67. Mandell LA, Wunderink RG, Anzueto A, et al. Infectious Diseases Society of America/American Thoracic Society Consensus Guidelines on the Management of Community-Acquired Pneumonia in Adults. Clinical Infectious Diseases. 2007; 44(Supplement_2):S27-S72. Chen T, Zhang L, Huang W, et al. Detection of Pathogens and Antimicrobial Resistance Genes in Ventilator-Associated Pneumonia by Metagenomic Next-Generation Sequencing Approach. Infection and Drug Resistance. 2023; Volume 16:923-36. Gaston DC, Miller HB, Fissel JA, et al. Evaluation of Metagenomic and Targeted Next-Generation Sequencing Workflows for Detection of Respiratory Pathogens from Bronchoalveolar Lavage Fluid Specimens. J Clin Microbiol. 2022 Jul 20; 60(7):e0052622. Grumaz S, Grumaz C, Vainshtein Y, et al. Enhanced Performance of Next-Generation Sequencing Diagnostics Compared With Standard of Care Microbiological Diagnostics in Patients Suffering From Septic Shock. Critical Care Medicine. 2019; 47(5):e394-e402. Wang S, Ai J, Cui P, et al. Diagnostic value and clinical application of next-generation sequencing for infections in immunosuppressed patients with corticosteroid therapy. Annals of Translational Medicine. 2020; 8(5):227-. Sun T, Liu Y, Cai Y, et al. A Paired Comparison of Plasma and Bronchoalveolar Lavage Fluid for Metagenomic Next-Generation Sequencing in Critically Ill Patients with Suspected Severe Pneumonia. Infection and Drug Resistance. 2022; Volume 15:4369-79. Additional Declarations No competing interests reported. Supplementary Files Supplementtable4.xls Cite Share Download PDF Status: Published Journal Publication published 02 Nov, 2024 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 04 Apr, 2024 Editor assigned by journal 04 Apr, 2024 Submission checks completed at journal 04 Apr, 2024 First submitted to journal 27 Mar, 2024 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4175027","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":287362372,"identity":"db060dfe-29ab-4e79-ba6e-ab7fbe3dedea","order_by":0,"name":"Lingyu Jiang","email":"","orcid":"","institution":"The People's Hospital of Guangxi Zhuang Autonomous Region","correspondingAuthor":false,"prefix":"","firstName":"Lingyu","middleName":"","lastName":"Jiang","suffix":""},{"id":287362374,"identity":"41efbfe2-f829-4138-8087-4aa50ec9c491","order_by":1,"name":"Yonglong Zhong","email":"","orcid":"","institution":"The People's Hospital of Guangxi Zhuang Autonomous Region","correspondingAuthor":false,"prefix":"","firstName":"Yonglong","middleName":"","lastName":"Zhong","suffix":""},{"id":287362376,"identity":"e63e3726-079d-464e-9572-db9e99298ec9","order_by":2,"name":"Shulin Xiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYBACAxDxgIFBjo29+QAJWhIYGIz5eI4lkKYlcZ5EjgJxWszZe59JJDAcTm9jyGFg+FGxjbAWy57jZkAtabltDGcPMPacuU2Ew26ksQG12OS2MfYlMDO2EaPl/jOQFol0NmYeAyK13GAD25LAxkasFsueNGYLoF8M23jYEg4S5Rdz9mOMNz4wHJaXn//44IMfFURoAQIWCcZ/ENYBotQDAfMHYlWOglEwCkbBCAUAaaM0p6+hrakAAAAASUVORK5CYII=","orcid":"","institution":"The People's Hospital of Guangxi Zhuang Autonomous Region","correspondingAuthor":true,"prefix":"","firstName":"Shulin","middleName":"","lastName":"Xiang","suffix":""},{"id":287362377,"identity":"7a48954f-d1e9-4779-acd6-524507d0a7c4","order_by":3,"name":"Lin Han","email":"","orcid":"","institution":"The People's Hospital of Guangxi Zhuang Autonomous Region","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Han","suffix":""},{"id":287362379,"identity":"b3feb6e5-408c-4e78-a274-5719de0bd53d","order_by":4,"name":"Meng Zhang","email":"","orcid":"","institution":"The People's Hospital of Guangxi Zhuang Autonomous Region","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Zhang","suffix":""},{"id":287362380,"identity":"e3632ff7-ac6e-43a7-a779-1d7584745f99","order_by":5,"name":"Jianliang Li","email":"","orcid":"","institution":"The People's Hospital of Guangxi Zhuang Autonomous Region","correspondingAuthor":false,"prefix":"","firstName":"Jianliang","middleName":"","lastName":"Li","suffix":""},{"id":287362382,"identity":"c6239515-2401-4800-babf-78518c84cda5","order_by":6,"name":"Guanhua Rao","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Guanhua","middleName":"","lastName":"Rao","suffix":""}],"badges":[],"createdAt":"2024-03-27 09:43:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4175027/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4175027/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-024-10108-6","type":"published","date":"2024-11-02T16:12:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54393653,"identity":"4a64065f-7302-4e5f-8f04-03712cbe9e72","added_by":"auto","created_at":"2024-04-09 21:08:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":112485,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the final diagnosis of pathogen based on two paired samples of 56 patients. (A) Proportions of based on mNGS detection or culture results. In orange, only mNGS positive was used to diagnose the final pathogen, yellow for reference culture diagnosis, blue for reference to both mNGS and culture. Green represents mNGS and culture of unknown significance. (B) Proportions of plasma mNGS detection and PD culture results.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4175027/v1/e4d08ba633c01d81719dc50a.png"},{"id":54393652,"identity":"cea46341-a0b5-45ca-be8b-8310d0ce6622","added_by":"auto","created_at":"2024-04-09 21:08:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":46227,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of clinical acceptance for Blood and BALF mNGS. Blood mNGS results shown in blue, as BALF results shown in orange, and BALF combine with blood mNGS is gray.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4175027/v1/1e8fa718caac9f63fa47c67e.png"},{"id":54393655,"identity":"dadac3f5-cd5f-40cc-8d3a-524bce586dd1","added_by":"auto","created_at":"2024-04-09 21:08:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":98584,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of clinical acceptance for Blood and BALF mNGS. Positive results shown in blue, as negative results shown in orange.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4175027/v1/fba4ba15fd58acb11318a6ff.png"},{"id":54393656,"identity":"1db3eb3f-aea1-4a87-9c8e-40884aea3397","added_by":"auto","created_at":"2024-04-09 21:08:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":171226,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of positive and matched results of mNGS and culture according to the detected pathogenic strains. X-axis represents the counts of detected pathogenic strains.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4175027/v1/d733e91850069b2632774c21.png"},{"id":54393657,"identity":"8218c394-102d-4a8e-9606-53c65e1266c4","added_by":"auto","created_at":"2024-04-09 21:08:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":463805,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A\u003c/strong\u003e) the difference in etiology of blood mNGS between groups of patients with different severities of pneumonia. (B) the difference in clinically confirmed pathogenic bacteria detected through blood NGS testing between the two groups.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4175027/v1/73263ffe1f58053b598c4a9b.png"},{"id":68206416,"identity":"c554912f-cc15-47c9-a95d-1c8206ac34a5","added_by":"auto","created_at":"2024-11-04 16:32:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1391435,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4175027/v1/8e6a6147-fb88-43a3-8add-e7af9ca3ba74.pdf"},{"id":54395073,"identity":"89d5253a-4087-4bb4-af77-731ce5ba831d","added_by":"auto","created_at":"2024-04-09 21:16:12","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":31744,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementtable4.xls","url":"https://assets-eu.researchsquare.com/files/rs-4175027/v1/88169d733d993b04ae66012d.xls"}],"financialInterests":"No competing interests reported.","formattedTitle":"High utility of BALF Metagenomic Next-Generation Sequencing Approach for Etiological Diagnosis of Pneumonia","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePulmonary infections are the most common and overwhelming infectious disease, and severe pneumonia is associated with severe morbidity and mortality among hospitalized patients, especially aged patients, despite advances in rapid diagnostic tests, newer treatment options and vaccine strategies(1, 2). The success of treating lung infections hinges on selecting the appropriate antimicrobial agent. Rapid, sensitive, and specific detection of the infectious pathogen is crucial for determining the clinical progression and outcome of a patient with sepsis. Furthermore, early failure to identify pathogens is one of the reasons for the high mortality rate of pneumonia(3). As a principal method of pathogen detection, microbiology laboratories play a vital role in detecting infections by means of microscopic examination, culture, identification, drug sensitivity and so on. However, most of these methods are time-consuming and are hyposensitive(4). This may be partly because of the frequent use of prior antibiotic therapy before pathogen detection test sampling. Hence, initial empirical antibiotic therapy is often empirical and nonspecific for severe pneumonia, which may lead to delays in targeted anti-infective treatment, increasing the prevalence of antibiotic-resistant microorganisms, and impeding effective therapy. These challenges have accelerated the exploration of accurate diagnostic strategies.\u003c/p\u003e \u003cp\u003eAs a new technique, metagenomic next-generation sequencing (mNGS) has been widely used in clinical practice in recent years\u003cb\u003e(5\u0026ndash;7).\u003c/b\u003e Since the application of mNGS, a greater variety of rapid etiological diagnoses of complex critical cases involving bacteria, viruses, fungi, and parasites have been reported simultaneously by untargeted sequencing of DNA/RNA than by conventional culture and blood culture methods(8, 9). Especially for severely ill patients, the mNGS diagnostic technique can aid in the identification of infectious agents and enhance diagnostic accuracy and therapeutic effectiveness, potentially resulting in favorable clinical outcomes\u003cb\u003e(10)\u003c/b\u003e. As an evolving diagnostic tool, there are still deficiencies in some states. The value of BALF and blood mNGS in pulmonary infection remains to be further validated, and whether there are differences in their roles needs to be verified, which poses new challenges for clinical treatment. Hence, identifying the best opportunity and optimal specimens for etiological tests is crucial. However, at present, there is no exploration or research on the best timing for mNGS detection in pneumonia patients. Our study was undertaken to evaluate and compare the diagnostic performance of mNGS for detecting pathogens, including bacteria, fungi, and viruses, in pneumonia patients with that of conventional methods and to explore the best method for diagnosing pneumonia to avoid blindly performing expensive tests.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. \u003cem\u003ePatient Population and Study Design\u003c/em\u003e\u003c/h2\u003e \u003cp\u003e This single-center prospective observational study evaluated data on pneumonia patients admitted to the Peoples Hospital of Guangxi Zhuang Autonomous Region, which is a tertiary hospital with 28 beds in the Department of Critical Care Medicine, from June 2019 to June 2021.\u003c/p\u003e \u003cp\u003e\u003cb\u003eThe inclusion criteria\u003c/b\u003e were (1) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years, (2) ICU stay\u0026thinsp;\u0026gt;\u0026thinsp;24 h, and (3) proven or suspected pneumonia. (4) A sampling interval of less than 24 hours was defined as paired mNGS results and conventional culture results in our study. \u003cb\u003eThe exclusion\u003c/b\u003e criteria were incomplete clinical data, including microbiological data. (2) Failure to acquire a enough sample for paired mNGS and conventional culture analysis during ICU admission. (3) Patients who failed to meet the inclusion criteria. Patient (4) refused to provide written consent. Informed consent was obtained from all patients involved. In addition, because only mNGS was used to sequence DNA in this study, RNA viruses were not detected for analysis. Informed consent was obtained from all patients involved. A positive test result was defined as a comparison with the final confirmed pathogen, including any of the final pathogens.\u003c/p\u003e \u003cp\u003eIn this study, the final pathogenic diagnosis and accuracy of the test results were determined according to the following standards based on clinical agreement:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eThe criteria for etiological diagnosis and the determination of test results.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eclinical agreement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; If the positive result of mNGS is consistent with the findings of conventional culture, the pathogen can be confirmed.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; If the positive result of mNGS is consistent with part of the findings from conventional culture and receives clinical agreement.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; When mNGS is positive while conventional culture results are negative, but the mNGS result is clinically agreed upon, it provides supportive evidence for the presence of the pathogen.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; If the positive result of mNGS is inconsistent with the findings of conventional culture, but the NGS result is clinically agreed upon, it still serves as supportive evidence for the presence of a specific pathogen.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; If both mNGS and conventional culture results are negative, but this is clinically agreed upon, indicating a reliable result.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eclinical ambiguity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; The results of mNGS can be either negative or positive despite negative findings from conventional culture. However, the clinical significance of these results remains unclear.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eclinical disagreement\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Despite a positive mNGS result in the absence of positive conventional culture findings, the result remains inconsistent with clinical considerations.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; The positive result of mNGS was discordant with both conventional culture results and clinical considerations.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Despite both mNGS and conventional culture results being negative, neither finding was consistent with clinical considerations.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026bull; Negative of mNGS with positive of conventional culture results, neither finding was consistent\u0026nbsp;with clinical considerations.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data collection\u003c/h2\u003e \u003cp\u003eIn this study, we gathered and documented the demographic and clinical profiles of the patients enrolled, including their age, initial symptoms, comorbid conditions, inflammatory biomarkers, duration of antibiotic therapy prior to the pathogen test, duration of ICU stay, Acute Physiology and Chronic Health Evaluation (APACHE) II score, Sequential Organ Failure Assessment (SOFA) score, and in-hospital mortality. Suspected infected samples were then collected for analysis via metagenomic next-generation sequencing (mNGS). In this study, conventional culture methods, including BALF and blood culture, were used for pneumonia patients. These cultures were performed within 24 hours prior to and following the corresponding mNGS test. Given that viruses are not typically the predominant pathogens in pneumonia, the detection of viruses through mNGS was not included in the clinical approval process of this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables are expressed as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SDs, medians, interquartile ranges (IQRs), or proportions (absolute and relative frequencies), as appropriate. The t test or Mann\u0026ndash;Whitney U test was used to compare continuous variables, and the χ2 test or Fisher\u0026rsquo;s exact test was used to compare categorical variables. The sensitivity, specificity, PPV, NPV, and consistency were also statistically significant. Two machine learning methods, Lasso and random forest, were used to find the clinically appropriate time to submit the test. A p value\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered to indicate statistical significance. Statistical analysis was performed by using IBM SPSS Statistics, version 24 (IBM Corp., Armonk, NY, United States.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1 Patient Characteristics\u003c/h2\u003e\n\u003cp\u003eDuring the study period, 77 pneumonia patients who underwent mNGS for infection at least two different sites were admitted to the ICU. Among these patients, five underwent repeated tests, and only the first test result for each of these patients was included in the final analysis. The following paired samples were excluded from this study: 2 blood and ascites samples, 2 blood and urine samples, 2 cerebrospinal fluid and BALF samples, 1 blood and tissue sample, 1 blood and cerebrospinal fluid sample, and 1 cerebrospinal fluid and BALF specimen. Thus, a total of 56 patients who had both blood and BALF samples tested using mNGS were included in the final analysis. These patients constituted our study cohort and were characterized by paired blood and BALF mNGS results \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e. The median age of these 56 patients, including 44 males, was 59 years, with the majority being over 40 years old (45/56). The common symptoms presented by these patients included dyspnea (46.4%), fever (46.4%), and cough (32.1%).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe baseline characteristics of the 56 patients enrolled in the study\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCharacteristic\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eValue (median or no.(%) )\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedian Age\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e59 years\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003edistribution\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u0026thinsp;~\u0026thinsp;40 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11(19.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40\u0026ndash;60 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19(32.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026gt;60 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26(46.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale sex\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44(78.6%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOnset symptoms\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFever\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26(46.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDyspnea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26(46.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCough\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18(32.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eComorbidity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9(16.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLiver disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4(7.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCerebrovascular disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9(16.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20(35.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKidney disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5(8.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eImmunocompromised or\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10(17.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSolid cancer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3(5.3%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSeverity score\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAPACHE II\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23(19.5,28)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSOFA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8(4,10)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eSOFA, \u0026nbsp;Sequential Organ Failure Assessment. APACHE II, The Acute Physiology and Chronic Health Evaluation\u0026nbsp;II\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2 Evaluation of the performance of mNGS in different specimens\u003c/h2\u003e\n\u003cp\u003eIn all 56 patients enrolled in the study, the percentage of positive mNGS results (84%, reaching 84%) was significantly greater than the percentage of positive culture results (only 48%). The mNGS method exclusively detected up to 23 positive cases, accounting for 41% of the total 56 patients. This significantly surpassed the culture results, which were only obtained for 3 patients, representing 5% of the patients. As illustrated in \u003cstrong\u003eFig.\u0026nbsp;1B.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the enrolled cohort, the clinical acceptance of mNGS for BALF samples (45/56, 80.36%) was obviously greater than that for blood samples (27/56, 48.21%). Furthermore, the combined use of mNGS from BALF and blood resulted in the highest clinical acceptance rate (83.93%, 47/56) compared to each individual sample type (\u003cstrong\u003eTable\u0026nbsp;2\u003c/strong\u003e and \u003cstrong\u003eFig.\u0026nbsp;2)\u003c/strong\u003e. Moreover, there were fewer positive detection results from BALF and blood plasma culture than from BALF and blood mNGS for bacteria on the same day. The positive rate of BALF culture was also greater than that of blood culture (39.58% vs 25.00%). (\u003cstrong\u003eTable\u0026nbsp;3\u003c/strong\u003e and \u003cstrong\u003eFig.\u0026nbsp;3)\u003c/strong\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\n\u003cp\u003eTable\u0026nbsp;2 comparative analysis of clinical acceptance of mNGS results from different testing samples\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tabd\" border=\"1\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSamples\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eClinical\u003c/p\u003e\n\u003cp\u003eacceptance\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eClinical\u003c/p\u003e\n\u003cp\u003edisapproval\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eEquivocal\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlood\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48.21%\u003c/p\u003e\n\u003cp\u003e(27/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41.07%\u003c/p\u003e\n\u003cp\u003e(23/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.71%\u003c/p\u003e\n\u003cp\u003e(6/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBALF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e80.36%\u003c/p\u003e\n\u003cp\u003e(45/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.93%\u003c/p\u003e\n\u003cp\u003e(5/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.71%\u003c/p\u003e\n\u003cp\u003e(6/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlood\u0026thinsp;+\u0026thinsp;BALF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e83.93%\u003c/p\u003e\n\u003cp\u003e(47/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.36%\u003c/p\u003e\n\u003cp\u003e(3/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.71%\u003c/p\u003e\n\u003cp\u003e(6/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\n\u003cp\u003eTable\u0026nbsp;3 comparison of the examination of efficacy between mNGS and culture\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\n\u003ctable border=\"1\" width=\"386\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"52\"\u003e\n\u003cp\u003esamples\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003emNGS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eCulture\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"126\"\u003e\n\u003cp\u003eCulture(a week before and after NGS)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" width=\"52\"\u003e\n\u003cp\u003eBlood\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003ePos\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e48.21%\u003c/p\u003e\n\u003cp\u003e(27/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e10.53%\u003c/p\u003e\n\u003cp\u003e(2/19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"126\"\u003e\n\u003cp\u003e25.00%\u003c/p\u003e\n\u003cp\u003e(7/28)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003eNeg\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e51.79%\u003c/p\u003e\n\u003cp\u003e(29/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e89.47%\u003c/p\u003e\n\u003cp\u003e(17/19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"126\"\u003e\n\u003cp\u003e75.00%\u003c/p\u003e\n\u003cp\u003e(21/28)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" width=\"52\"\u003e\n\u003cp\u003eBALF\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003ePos\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e82.14%\u003c/p\u003e\n\u003cp\u003e(46/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e30.77%\u003c/p\u003e\n\u003cp\u003e(8/26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"126\"\u003e\n\u003cp\u003e39.58%\u003c/p\u003e\n\u003cp\u003e(19/48)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"38\"\u003e\n\u003cp\u003eNeg\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"94\"\u003e\n\u003cp\u003e17.86%\u003c/p\u003e\n\u003cp\u003e(10/56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e69.23%\u003c/p\u003e\n\u003cp\u003e(18/26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"126\"\u003e\n\u003cp\u003e60.42%\u003c/p\u003e\n\u003cp\u003e(29/48)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u0026nbsp;\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3 Microbiological diagnostic performance of mNGS\u003c/h2\u003e\n\u003cp\u003eCodetection of multiple pathogens was observed in 24 patients using both culture and mNGS methods. In accordance with microbiological and clinical protocols, the identified pathogens were categorized as illustrated in \u003cstrong\u003eFig.\u0026nbsp;4.\u003c/strong\u003e The three predominant pathogenic bacteria identified by mNGS were \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003ePathogen distribution and differences in blood samples between the severe pneumonia group and the non-severe pneumonia group\u003c/p\u003e\n\u003cp\u003eAmong the 56 patients, 37 were diagnosed with severe pneumonia and 14 with non-severe pneumonia; the remaining 5 patients were excluded from the study because their condition was complicated by infection at other sites. According to the results of blood mNGS, \u003cem\u003eEnterococcus faecium\u003c/em\u003e was detected more frequently in the non-severe pneumonia group (4 vs. 0, p\u0026thinsp;=\u0026thinsp;0.0040). Similarly, compared with the final etiological diagnosis, \u003cem\u003eEnterococcus faecium\u003c/em\u003e was a common pathogen in the non-severe pneumonia group (4 vs. 1, p\u0026thinsp;=\u0026thinsp;0.0167) after excluding the detected viruses. However, no significant differences were identified among the other pathogens, as shown in \u003cstrong\u003eFig.\u0026nbsp;5\u003c/strong\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e3.4.\u0026nbsp;\u003cstrong\u003eThe clinical significance of simultaneously detecting mNGS in BALF and blood samples for pathogen identification in severe pneumonia patients\u003c/strong\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eAmong these paired patients, one or more pathogens were detected in the BALF specimens of 22 individuals at a higher frequency than in their blood samples. By comparing the NGS results from blood and BALF in the severe pneumonia group, we found that 39.28% (22/56) of the patients had the same pathogen detected in both the BALF and blood samples. From these samples, we extracted the common pathogens and their normalized read counts across the two specimens. Then, we compared the abundance of pathogens detected in different samples, aiming to identify the most suitable specimens for detecting specific pathogens. We observed a greater abundance of pathogenic bacteria, including Legionella and Tsutsugamushi, as well as viral reads, in the blood samples. Conversely, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, and Jaegeri lung were more frequently detected in BALF samples. (Supplemental Table\u0026nbsp;4)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.5 Exploring the best opportunity for mNGS in pneumonia patients\u003c/h2\u003e\n\u003cp\u003eTo reduce the negative test rate, we investigated the optimal disease status for conducting mNGS. A comprehensive analysis of 26 serological indicators was performed on the clinically confirmed positive mNGS results. The findings revealed that positive blood mNGS results, which were clinically confirmed, were more likely to be associated with lower temperature, lower PCO2 and higher SOFA scores than negative results (p\u0026thinsp;=\u0026thinsp;0.022, 0.028 and 0.038, respectively). However, there were no significant differences in the serological indicators detected by BALF mNGS. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe correlation between positive rate of NGS detection and clinical indicators\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eserological indicators\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP_BALF mNGS\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP_Blood mNGS\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eT max\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.06368\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02235\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePro-BNP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.07186\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.60840\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCRP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.10390\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.78880\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePaO2/FiO2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.10400\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.36020\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCK\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.11430\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.00000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWBC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.16750\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.00000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLYMPH\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.21340\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.07194\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNEUT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.24770\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.48430\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHGB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.39770\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.86330\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFiO2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.40310\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.30550\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePLT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.50100\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.26140\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUrea\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.24950\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.19890\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCr\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.58430\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.25370\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ecTnI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.54930\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.86920\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCK-MB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.95450\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.60390\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003epH\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.31840\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.50200\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePO2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.67840\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.34700\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePCO2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.71210\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.02751\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLAC\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.72920\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.85860\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eALT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.80090\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.22850\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAST\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.33380\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.89240\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eALB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.96350\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.10080\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIL6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.83170\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.19110\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePCT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.17340\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.36820\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAPACHE II\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.36090\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.78790\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSOFA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.57300\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.03750\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003ePneumonia is a common disease involving the alveoli and the distal bronchus of the lung tree in acute respiratory infection patients. Over the past few years, the widespread use of broad-spectrum antibiotics has increased the complexity of the drug resistance spectrum of CAP pathogens, rendering the diagnosis and treatment of CAP increasingly challenging. The pathogen diagnosis of severe pneumonia has always been a challenging issue that is especially common in patients with chronic diseases or who have been exposed to antibiotics and use ventilators. It has been demonstrated that the standard methods for detecting pathogenic microorganisms, which involve bacterial smears, cultures, or nucleic acid testing from pharyngeal swabs, sputum, or bronchoalveolar lavage fluid (BALF), exhibit restricted efficacy and are capable of identifying pathogenic microorganisms in only 25\u0026ndash;40% of patients\u003cb\u003e(11\u0026ndash;13)\u003c/b\u003e. This means that up to 50% of pneumonia patients have an unknown etiological diagnosis according to traditional etiological methods. Therefore, timely, fast and accurate identification of multiple pathogens remains invaluable for successful management of these patients. Clinicians have been persistently endeavoring to secure positive etiological outcomes, exploring the efficacy and implications of various specimen tests. Research indicates that blood cultures are not advisable even in severe cases of pulmonary infections, as the positive rate is extremely low \u003cb\u003e(14, 15)\u003c/b\u003e. The guidelines for pneumonia are continuously being updated. The new guidelines have established additional criteria for determining the necessity of conducting lower respiratory tract and blood specimen testing in cases of pulmonary infections. Specifically, the 2019 edition of the American IDSA/ATS guidelines advises against routine BALF and blood culture testing. Instead, it advocates for lower respiratory tract smear and culture, as well as blood culture pathogen detection, only in specific scenarios: for hospitalized patients with severe pneumonia, those at risk of MRSA and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e infection (including those with past infections), and patients who have been hospitalized in the last 90 days and have undergone parenteral antimicrobial therapy\u003cb\u003e(16)\u003c/b\u003e. The updated recommendations in the guidelines are primarily motivated by the fact that cultures fail to alter patient outcomes, the relatively low positive rate of cultures, the potential for contaminated bacteria to contribute to inappropriate antimicrobial use, and the likelihood of prolonged treatment durations due to positive blood cultures. These factors highlight the inherent limitations of traditional pathogen detection methods. Nevertheless, the guidelines on the potential value of mNGS testing are lacking.\u003c/p\u003e \u003cp\u003eThis study demonstrated that mNGS offers superior pathogen detection and significantly more positive results in BALF and blood mNGS than traditional cultures of corresponding specimens, which is in line with the findings of Fei Xie et a\u003cb\u003el(10)\u003c/b\u003e. Even compared with the combined detection methods employing traditional techniques such as BALF culture, PCR, and antibody detection, the pathogen detection rate achieved by mNGS in BALF stands notably higher at 84.5%, surpassing the rate of 26.8%\u003cb\u003e(13)\u003c/b\u003e. In cases of pulmonary infection, the culture results of BALF have always been greater than those of blood cultures, indicating a significant difference\u003cb\u003e(17).\u003c/b\u003e We simultaneously conducted NGS on both BALF and blood samples from 56 patients, and the comparison of the results showed that the percentage of positive BALF samples was significantly greater than that of positive blood samples (80.36% vs. 48.21%). The results of this study also confirm the findings of Xu Chen's research\u003cb\u003e(11)\u003c/b\u003e. According to the published literature, the percentage of positive mNGS results was as high as 84%, which was greater than that of traditional culture methods for both BALF and blood, and antibiotic exposure did not affect the percentage of positive mNGS results, which was similar to the results of previous studies\u003cb\u003e(18)\u003c/b\u003e. For patients with pulmonary infection, BALF NGS is an important clinical detection method for identifying pathogenic bacteria.\u003c/p\u003e \u003cp\u003eGiven the vast amount of sequence information obtained through mNGS and the diverse nature of pathogen species, the interpretation of these reports can be extremely difficult, increasing the risk of obtaining false positive results(19). To date, there have been no rigorous standards established to differentiate between pathogens detected by mNGS that are truly pathogenic, colonized, or merely false positives. To address this issue, we combined all pathogen detection results with potentially useful information that may aid in the diagnosis of pulmonary infection pathogens, such as serum immune tests, β-glucan tests, galactomannan antigen tests, and many other clinical examinations. Additionally, two deputy directors or higher-ranking doctors have conducted a comprehensive clinical interpretation of all test results to determine the authenticity and reliability of the final pathogen detection results, thereby avoiding false positive rates. To our knowledge, this study is the first to evaluate the diagnostic value of NGS using clinically accepted criteria as the gold standard. In our study cohort, the clinical acceptance rate of mNGS for BALF samples (45/56, 80.36%) was significantly greater than that for blood samples (27/56, 48.21%). Ten patients had negative BALF test results, which was inconsistent with the clinical findings. In one patient, \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e was detected but was colonized based on clinical evaluation. When the BALF and blood mNGS results were combined, the clinical acceptance rate (83.93%, 47/56) was greater than that of either method alone. For patients with respiratory infections, the positive rate and clinical acceptance of BALF culture are greater, making it more suitable for the clinical diagnosis of pneumonia. Additionally, this underscores the need for promptly identifying the source of infection in various locations and promptly collecting pathogens from the infected site for corresponding testing in patients with infection. Interestingly, our data revealed for the first time that the rate of positive blood NGS results was greater than that of traditional BALF pathogen detection (48.21% vs 39.58%). Patients with severe pneumonia are prone to bloodstream infections. Blood NGS is an alternative test when BALF specimens are not available. As bronchoscopy for collecting BALF samples is an invasive procedure, we recommend that patients with compromised cardiopulmonary function who may not tolerate this procedure should consider blood NGS testing as an alternative to promptly determine the etiology and minimize the risk of serious complications.\u003c/p\u003e \u003cp\u003eWith the increasing clinical application of metagenomic testing, our understanding of the etiology of infectious diseases is likely to include a more comprehensive range of unculturable infectious agents and coinfections. A significant advantage of the metagenomic NGS method lies in its ability to identify numerous potential infectious agents in a single test, leading to improved clinical outcomes. In this study, 24 patients (42.86%) had mixed infections, and the optimal anti-infective treatment plan was adjusted based on these findings. Among the mixed infections, bacterial-fungal infections (44.3%) and bacterial-fungal-viral infections (35.7%) were relatively common\u003cb\u003e(10)\u003c/b\u003e. This finding suggests that a significant proportion of patients with pneumonia may have complex microbial infections involving the presence of multiple pathogens. Such codetections can provide valuable insights into the pathogenesis of the disease and may inform more targeted therapeutic strategies. Simultaneously, we observed that Legionella, tsutsugamushi disease, and viral reads are more prevalent in blood samples. Conversely, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, and \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e are more readily detectable in BALF.\u003c/p\u003e \u003cp\u003emNGS still has several limitations. Similar to traditional blood cultures, the yield of mNGS may be affected by the time of sample acquisition. A previous study by Grumaz et al\u003cb\u003e(20)\u003c/b\u003e. showed that the positive rate of mNGS results remained constant at different time points after sepsis onset, while the positive rate of blood cultures decreased at later time points. Another study also indicated that mNGS is less affected by prior antibiotic exposure. A study by Wang et al\u003cb\u003e(21)\u003c/b\u003e demonstrated that mNGS exhibited greater sensitivity than traditional methods in individuals with a higher cumulative steroid dosage, but the positive rate gradually decreased with increasing cumulative steroid dosage. This leads us to speculate that the percentage of positive blood samples may be related to the patient's immune and inflammatory status. The length of hospital stay is also a factor that influences the positive detection rate(22). The results showed that compared to patients with negative blood NGS results, patients with positive blood mNGS results had lower body temperature, lower PCO2, and higher SOFA scores (p\u0026thinsp;=\u0026thinsp;0.022, 0.028, and 0.038, respectively). These findings suggest that the internal environmental status of patients is affected by blood NGS and that blood NGS should be performed as soon as possible when there is significant organ dysfunction to clarify the etiology. However, there were no significant changes in the serological indicators detected by mNGS of the BALF specimens. This may be related to the fact that this study focused on lung infections, which primarily occur through respiratory tract transmission. The results of BALF may be influenced by factors such as specimen collection. However, because of the low number of reported cases in the literature and the limited number of available studies, further investigations are needed in the future.\u003c/p\u003e \u003cp\u003eThis study has the following limitations. First, the sample size was relatively small. To ensure the consistency of paired blood and BALF samples, we excluded patients whose mNGS blood and BALF samples were collected on different days. Second, we did not distinguish between hospital-acquired and community-acquired pneumonia. For hospital-acquired pneumonia, the use of anti-infective agents often reduces the positive rates of both routine testing and mNGS to some extent. Third, considering that it is difficult to determine mixed viral infections, our study analyzed only bacteria and fungi, meaning that viruses that can also cause pneumonia were excluded, which may have affected the sensitivity of NGS. Fourth, as this study was retrospective, we analyzed only the impact of clinical laboratory indicators on NGS results and were unable to delve deeply into the operational impact of specimen collection.\u003c/p\u003e \u003cp\u003eOverall, by comparing and analyzing the etiological test results of blood and BALF samples from patients with lung infections, this study revealed that the etiologies of lung infections are often mixed. Among the current detection methods, BALF mNGS has the highest sensitivity for identifying nonviral pathogens in lung infections. At the same time, we suggest that when BALF samples cannot be obtained, blood NGS can also be a valuable detection method for identifying the etiology, especially when Legionella, tsutsugamushi disease, and viruses are suspected to be the causative agents. Additionally, although we analyzed clinical indicators that may affect negative NGS results, there are certain limitations, and further large-sample studies are needed to increase the rate of positive mNGS results.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank the patients for cooperating with our investigation and acknowledge the professionalism and compassion demonstrated by all the healthcare workers involved in patients\u0026rsquo; care.\u003c/p\u003e\n\u003ch2\u003eFunding\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe Guangxi Science and Technology Base and Talent Special Project (grant no. 2021AC04001), the Youth Science Foundation Project of Guangxi (grant no. 2023GXNSFBA026096) and the Guangxi Health and Wellness Commission Self-funded Project (grant no. Z- A20220085) provided funding for this study.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were performed in accordance with the ethical standards of the Ethics Committee of the People\u0026rsquo;s Hospital of Guangxi Zhuang Autonomous Region and the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Informed consent was obtained from the patient.\u003c/p\u003e\n\u003cp\u003eAvailability of data and material (data transparency)\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003eInformed Consent\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors approved the final version submitted for publication.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contribution\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAll authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically \u0026nbsp; reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eJiang, Ling Yu: Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Writing \u0026ndash; original draft. \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eZhong, Yong Long: Software, Validation, Visualization, Formal analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eXiang, Shu Lin: Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;Han, Lin: Conceptualization, Project administration, Methodology, Project administration, Supervision\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMeng Zhang: Acquisition of data, Data curation, Resources, Investigation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eJianliang Li: Acquisition of data, Data curation, Resources, Investigation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGuanhua Rao: Software, drafting, Formal analysis\u003c/em\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnderson R, Feldman C. The Global Burden of Community-Acquired Pneumonia in Adults, Encompassing Invasive Pneumococcal Disease and the Prevalence of Its Associated Cardiovascular Events, with a Focus on Pneumolysin and Macrolide Antibiotics in Pathogenesis and Therapy. International Journal of Molecular Sciences. 2023; 24(13).\u003c/li\u003e\n\u003cli\u003eTufa, Denning. The Burden of Fungal Infections in Ethiopia. Journal of Fungi. 2019; 5(4).\u003c/li\u003e\n\u003cli\u003eGarcia-Vidal C, Carratal\u0026agrave; J. Early and Late Treatment Failure in Community-Acquired Pneumonia. Seminars in Respiratory and Critical Care Medicine. 2009; 30(02):154-60.\u003c/li\u003e\n\u003cli\u003eAfshari A, Schrenzel J, Ieven M, et al. Bench-to-bedside review: Rapid molecular diagnostics for bloodstream infection -- a new frontier? Crit Care 2012 May 29; 16(3):222.\u003c/li\u003e\n\u003cli\u003eHe Y, Geng S, Mei Q, et al. Diagnostic Value and Clinical Application of Metagenomic Next-Generation Sequencing for Infections in Critically Ill Patients. Infection and Drug Resistance. 2023; Volume 16:6309-22.\u003c/li\u003e\n\u003cli\u003eDuan H, Li X, Mei A, et al. The diagnostic value of metagenomic next⁃generation sequencing in infectious diseases. BMC Infectious Diseases. 2021; 21(1).\u003c/li\u003e\n\u003cli\u003eHuang C, Chen H, Ding Y, et al. A Microbial World: Could Metagenomic Next-Generation Sequencing Be Involved in Acute Respiratory Failure? Frontiers in Cellular and Infection Microbiology. 2021; 11.\u003c/li\u003e\n\u003cli\u003ePham J, Su LD, Hanson KE, et al. Sequence-based diagnostics and precision medicine in bacterial and viral infections: from bench to bedside. Curr Opin Infect Dis. 2023 Aug 1; 36(4):228-34. .\u003c/li\u003e\n\u003cli\u003eJerome H, Taylor C, Sreenu VB, et al. Metagenomic next-generation sequencing aids the diagnosis of viral infections in febrile returning travellers. J Infect. 2019 Oct; 79(4):383-8.\u003c/li\u003e\n\u003cli\u003e Xie F, Duan Z, Zeng W, et al. Clinical metagenomics assessments improve diagnosis and outcomes in community-acquired pneumonia. BMC Infectious Diseases. 2021; 21(1).\u003c/li\u003e\n\u003cli\u003e Chen X, Ding S, Lei C, et al. Blood and Bronchoalveolar Lavage Fluid Metagenomic Next-Generation Sequencing in Pneumonia. Canadian Journal of Infectious Diseases and Medical Microbiology. 2020; 2020:1-9.\u003c/li\u003e\n\u003cli\u003e Torres A, Chalmers JD, Dela Cruz CS, et al. Challenges in severe community-acquired pneumonia: a point-of-view review. Intensive Care Medicine. 2019; 45(2):159-71.\u003c/li\u003e\n\u003cli\u003e Yang Y, Zhu X, Sun Y, et al. Comparison of next-generation sequencing with traditional methods for pathogen detection in cases of lower respiratory tract infection at a community hospital in Eastern China. Medicine. 2022; 101(51).\u003c/li\u003e\n\u003cli\u003e Zhang D, Yang D, Makam AN. Utility of Blood Cultures in Pneumonia. The American Journal of Medicine. 2019; 132(10):1233-8.\u003c/li\u003e\n\u003cli\u003e Afshar N, Tabas J, Afshar K, et al. Blood cultures for community‐acquired pneumonia: Are they worthy of two quality measures? A systematic review. Journal of Hospital Medicine. 2009; 4(2):112-23.\u003c/li\u003e\n\u003cli\u003e Metlay JP, Waterer GW, Long AC, et al. Diagnosis and Treatment of Adults with Community-acquired Pneumonia. An Official Clinical Practice Guideline of the American Thoracic Society and Infectious Diseases Society of America. American Journal of Respiratory and Critical Care Medicine. 2019; 200(7):e45-e67.\u003c/li\u003e\n\u003cli\u003e Mandell LA, Wunderink RG, Anzueto A, et al. Infectious Diseases Society of America/American Thoracic Society Consensus Guidelines on the Management of Community-Acquired Pneumonia in Adults. Clinical Infectious Diseases. 2007; 44(Supplement_2):S27-S72.\u003c/li\u003e\n\u003cli\u003e Chen T, Zhang L, Huang W, et al. Detection of Pathogens and Antimicrobial Resistance Genes in Ventilator-Associated Pneumonia by Metagenomic Next-Generation Sequencing Approach. Infection and Drug Resistance. 2023; Volume 16:923-36.\u003c/li\u003e\n\u003cli\u003e Gaston DC, Miller HB, Fissel JA, et al. Evaluation of Metagenomic and Targeted Next-Generation Sequencing Workflows for Detection of Respiratory Pathogens from Bronchoalveolar Lavage Fluid Specimens. J Clin Microbiol. 2022 Jul 20; 60(7):e0052622.\u003c/li\u003e\n\u003cli\u003e Grumaz S, Grumaz C, Vainshtein Y, et al. Enhanced Performance of Next-Generation Sequencing Diagnostics Compared With Standard of Care Microbiological Diagnostics in Patients Suffering From Septic Shock. Critical Care Medicine. 2019; 47(5):e394-e402.\u003c/li\u003e\n\u003cli\u003e Wang S, Ai J, Cui P, et al. Diagnostic value and clinical application of next-generation sequencing for infections in immunosuppressed patients with corticosteroid therapy. Annals of Translational Medicine. 2020; 8(5):227-.\u003c/li\u003e\n\u003cli\u003e Sun T, Liu Y, Cai Y, et al. A Paired Comparison of Plasma and Bronchoalveolar Lavage Fluid for Metagenomic Next-Generation Sequencing in Critically Ill Patients with Suspected Severe Pneumonia. Infection and Drug Resistance. 2022; Volume 15:4369-79.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Next-generation sequencing, Diagnostic, Pneumonia","lastPublishedDoi":"10.21203/rs.3.rs-4175027/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4175027/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: For patients with pneumonia, rapid detection of pathogens is still a major global problem in clinical practice because traditional diagnostic techniques for infection are time-consuming and insensitive. Metagenomic next-generation sequencing (mNGS) is a novel technique that has the potential to improve pathogen diagnosis. In this study, we aimed to explore the microbiological diagnostic ability of mNGS compared with that of conventional culture in pneumonia patients and to explore the best opportunityto test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A prospective study from June 2020 to June 2021 was performed at a tertiary teaching hospital in China, and 56 pneumonia patients were included among all adult patients with a clinical diagnosis of pneumonia. Blood and bronchoalveolar lavage fluid (BALF) samples were taken for simultaneous mNGS and conventional culture testing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e All 56 patients underwent both conventional culture and mNGS, 37 of whom were diagnosed with severe pneumonia and 17 of whom were diagnosed with nonsevere pneumonia. The top three pathogenic bacteria detected by mNGS were \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e. \u003cem\u003eEnterococcus faecium\u003c/em\u003e was detected more frequently in the non-severepneumonia group (4 vs. 0, p\u0026lt;0.05). The findings revealed that the detection rate of mNGS (84%) was superior to that of conventional culture methods (48%). Notably, the percentage of mNGS-positive BALF samples (46/56, 82.14%) was significantly greater than that ofblood samples (27/56, 48.21%). The etiological comparison demonstrated that mNGS-positive samples for which clinical approval was obtained tended to be associated with a more normalized temperature, lower PCO2 levels, and a higher SOFA score thanmNGS-negative samples (p= 0.022, p = 0.0.028, and p = 0.038, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eIn this study, we discovered that the etiology of lung infections frequently involves multiple pathogens. mNGS of BALF is instrumental for detecting nonviral pathogens associated with lung infections. Although the rate of positive blood NGS results is significantly influenced by various clinical factors, for patients suspected of having viral, Legionella, or tsutsugamushi infections, plasma mNGS could serve as a complementary diagnostic tool.\u003c/p\u003e","manuscriptTitle":"High utility of BALF Metagenomic Next-Generation Sequencing Approach for Etiological Diagnosis of Pneumonia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-09 21:08:07","doi":"10.21203/rs.3.rs-4175027/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-04T06:07:09+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-04T05:51:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-04T05:47:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2024-03-27T09:42:15+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":"25ec5ef1-99f0-45c6-8e31-91653446d392","owner":[],"postedDate":"April 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-04T16:21:58+00:00","versionOfRecord":{"articleIdentity":"rs-4175027","link":"https://doi.org/10.1186/s12879-024-10108-6","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2024-11-02 16:12:57","publishedOnDateReadable":"November 2nd, 2024"},"versionCreatedAt":"2024-04-09 21:08:07","video":"","vorDoi":"10.1186/s12879-024-10108-6","vorDoiUrl":"https://doi.org/10.1186/s12879-024-10108-6","workflowStages":[]},"version":"v1","identity":"rs-4175027","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4175027","identity":"rs-4175027","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}