The Associations of Gram-Positive Cocci and Gram-Negative Rods with Disease Severity and Mortality in Critically Ill Patients: A Retrospective Cohort Study

The Associations of Gram-Positive Cocci and Gram-Negative Rods with Disease Severity and Mortality in Critically Ill Patients: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Associations of Gram-Positive Cocci and Gram-Negative Rods with Disease Severity and Mortality in Critically Ill Patients: A Retrospective Cohort Study Takaya Nakashima, Shuntaro Sato, Motohiro Sekino, Takeshi Tanaka, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6632548/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Despite advances in intensive care medicine, the mortality rate of patients with sepsis remains high. The differences in pathogenic mechanisms between gram-positive cocci (GPC) and gram-negative rod (GNR) bacteremia are well-documented, but the relationship between bacterial types and clinical outcomes remains unclear, particularly regarding the discrepancy between severity at emergency department (ED) / intensive care unit (ICU) presentation and subsequent mortality. Patients and Methods: Of the adult patients who presented to two Japanese tertiary hospitals' EDs with suspected infections in 2018–2022, we included those with positive blood cultures who were admitted to the ICU or emergency ward. The primary outcomes were 7-day and 28-day mortality. The secondary outcomes were diagnoses of sepsis and septic shock. We calculated adjusted risk differences (aRDs) and adjusted risk ratios (aRRs) between the GPC and GNR groups using modified Poisson and least-squares regression analyses, adjusting for age, sex, malignancy, immunosuppressive therapy, hemodialysis, and intravascular device use. Results: Of the 259 patients, 107 (41.3%) had GPC bacteremia and 152 (58.7%) had GNR bacteremia. Staphylococcus aureus and Escherichia coli were the most common pathogens in each group. GPC bacteremia was associated with higher mortality at both 7 days (aRD 8.9%, 95%CI: 1.3−16.4; aRR 3.48, 95%CI: 1.29−9.36) and 28 days (aRD 10.6%, 95%CI: 1.8–19.5; aRR 2.65, 95%CI: 1.21−5.83) versus GNR bacteremia. However, the GPC bacteremia patients showed less severe presentations at ED arrival, with a lower sepsis diagnosis rate (aRD −12.8%, 95%CI: −24.7 to −0.8; aRR 0.81, 95%CI: 0.66–0.99), lower qSOFA scores, and lower lactate levels (1.9 vs. 2.5 mmol/L). This pattern of higher mortality despite less-severe initial presentations was consistently observed in analyses of sepsis patients and in a comparison of S. aureus with E. coli bacteremia. Conclusions: GPC bacteremia, despite its less severe clinical presentation at ED arrival compared to GNR bacteremia, was associated with higher mortality. Clinicians should not be misled by the apparently milder initial organ dysfunction in GPC bacteremia, as these patients require careful monitoring and appropriate treatment regardless of presentation severity. These findings highlight the importance of identifying the bacterial species in the risk stratification and management of bacteremia patients in critical-care settings. bacteremia gram-positive cocci gram-negative rod sepsis mortality emergency department Figures Figure 1 Figure 2 Figure 3 BACKGROUND Despite the latest advances in intensive care medicine, the mortality rate of patients with sepsis remains high [ 1 , 2 ]. Bacteremia caused by various infectious diseases often leads to sepsis. Approximately half of intensive care unit (ICU) patients with severe sepsis have bacteremia, and these patients often have more severe clinical conditions and poorer outcomes [ 3 – 6 ]. Early intervention is crucial for improving the survival of patients with sepsis, and the rapid identification of the causative bacteria and appropriate antimicrobial therapy are key elements of effective treatment [ 7 ]. Most cases of bacteremia are caused by either gram-positive cocci (GPC) or gram-negative rods (GNR), which exhibit distinct pathogenic mechanisms and clinical manifestations [ 8 – 11 ]. Although these differences could potentially influence patient outcomes, the relationships between bacterial species and clinical outcomes have not been established, due to several limitations. First, most of the relevant studies did not sufficiently adjust their analyses for important confounding factors such as age and comorbidities [ 12 , 13 ]. Second, the heterogeneity in study settings (e.g., community vs. hospital-acquired infections) and patient populations has made it difficult to draw definitive conclusions [ 14 ]. In the present study we determined the clinical outcomes of GPC and GNR bacteremia in critically ill patients at two tertiary care centers, and we evaluated the relationship between the bacterial species causing sepsis and the patients' clinical outcomes. By focusing on a well-defined population in the emergency department (ED) and ICU settings and adjusting for key confounding factors, we seek to provide more precise evidence regarding the impact of various bacterial species on patient outcomes. This knowledge will help clinicians better understand the prognostic implications of different bacterial species and potentially guide treatment strategies for bacteremia in the critical care setting. PATIENTS AND METHODS Study design and setting This retrospective, multicenter study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology statement [ 15 ]. We used two databases: (1) that of Nagasaki University Hospital for the period from January 1, 2020 to August 31, 2022 and (2) the ED data from Hitachi General Hospital for the period from April 1, 2018, to March 31, 2020. Nagasaki University Hospital and Hitachi General Hospital are both tertiary care centers in Japan with approx. 5,000 and 20,000 annual ED visits, respectively. This study was approved by the institutional review boards of Nagasaki University Hospital (approval no. 22112121) and Hitachi General Hospital (approval no. 201795). The requirement for informed consent was waived due to the retrospective nature of the study. Patients We included the cases of the adult patients (≥ 18 years) with positive blood cultures who initially presented to either of the above-mentioned hospitals' ED and had suspected infections (as determined by the attending physician). All patients required two sets of blood cultures and were admitted to the ICU or emergency ward on the same day. We defined the presence of bacteriemia as positive results on both sets of submitted blood cultures. Measurement variables We collected the patients' data from their electronic medical records. The clinical characteristics included age, sex, suspected infection site(s), presence of malignancy, chronic hemodialysis status, and use of vascular or other medical devices (central venous catheter, peripheral line, and implanted medical devices) before visiting the ED. The physiological data on admission included vital signs (mean blood pressure, pulse rate, respiratory rate, oxygen saturation, and consciousness level) and the quick Sequential Organ Failure Assessment (qSOFA) score. The laboratory measurements on admission included the white blood cell count, hemoglobin, sodium, potassium, blood urea nitrogen, creatinine, albumin, bilirubin, C-reactive protein (CRP), and lactate levels. The treatment data included antibiotic change, use of immunosuppressants such as steroids, and renal replacement therapy. Antibiotic change was defined as the administration of more than one type of antibiotic within 48 hr after the patient's blood culture collection. The proportion of missing data for each variable is presented in Supplementary Table S1 . Exposure and outcome The exposure was GPC or GNR bacteremia at ED arrival based on blood culture results. The primary outcomes were the mortality rates at 7 days and 28 days after admission. The secondary outcomes were diagnoses of sepsis and septic shock respectively, defined using modified sepsis clinical surveillance criteria [ 16 – 18 ] ( Suppl. Table S2). These diagnoses were determined based on clinical and laboratory data collected within 2 days of the blood culture day, as specified in the surveillance criteria. Septic shock was defined as the presence of sepsis requiring a vasopressor (noradrenaline, dopamine, adrenaline, phenylephrine, or vasopressin) plus a lactate level ≥ 2.0 mmol/L. Statistical analyses We used summary statistics to describe the characteristics of the patients presenting with suspected infection to the ED and compared each variable between the groups of patients with GPC bacteremia and GNR bacteremia. Categorical variables are expressed as numbers and percentages. Continuous variables are expressed as the median and interquartile range (IQR). We examined the association between bacterial types (GPC vs. GNR) and outcomes (7-day and 28-day mortality, sepsis, and septic shock) using two complementary approaches. We calculated the adjusted risk differences (aRDs) and the adjusted risk ratios (aRRs) between the GPC and GNR groups using modified Poisson and least-squares regression analyses [ 19 , 20 ]. We adjusted for the following potential confounders based on previous studies: age, sex, malignancy, immunosuppressant use, chronic hemodialysis status, and previous use of vascular or other medical devices [ 21 – 24 ]. We used robust variance to determine the 95% confidence interval (CI) of the aRD values. All analyses were conducted using R ver. 4.2.2 (R Foundation, Vienna, Austria), with the 'rqlm' package for the estimations of the aRR and aRD values . Additional analyses We conducted two additional analyses to further examine the relationship between bacterial types and outcomes. First, to compare outcomes in patients who were already in a severe condition on admission, we analyzed the subset of patients diagnosed with sepsis at admission, focusing on septic shock and sepsis-related mortality as outcomes. Second, we compared outcomes between the most common causative pathogens identified in each bacterial group. Both additional analyses were conducted using the same approaches as the main analysis: regression to estimate aRDs and aRRs, adjusting for the same set of confounders. RESULTS Patient flow As shown in Fig. 1 , among the 1,346 eligible patients with bacteremia, 259 were included in the final analysis after the exclusion of 1,073 patients based on the predetermined study criteria including contamination, repeated hospitalizations, and presence of bacteria other than GPC or GNR. The final cohort was 107 patients with GPC bacteremia (41.3% of the total series) and 152 patients with GNR bacteremia (58.7%). The patients' baseline characteristics Table 1 summarizes the baseline characteristics of the patients in the two groups. The median age was 73 years in the GPC group and 78 years in the GNR group. The GPC group had higher proportions of males (65%) and respiratory infections (22%), and the GNR group showed a higher prevalence of genitourinary infections (25%) and more frequent presence of malignancy (22% vs. 11%). Vascular device use was more common in the GPC group versus the GNR group (28% vs. 16%). Regarding severity measures, the GNR group demonstrated higher qSOFA scores (qSOFA ≥ 2: 57% vs. 41%) and lactate levels (2.5 vs. 1.9 mmol/L). The laboratory data showed variations between the two groups, with differences in inflammatory markers and organ function parameters. Table 1 Baseline characteristics on admission and outcome between GPC and GNR bacteremia Characteristic Overall n = 259 Microorganism GPC n = 107 (41.3%) GNR n = 152 (58.7%) Age, yrs 77.0 [67.0–84.0] 73.0 [62.0–83.0] 78.0 [69.8–85.0] Males 141/259 (54%) 70/107 (65%) 71/152 (47%) Suspected infection organ (Top 3): Genitourinary 46/259 (18%) 8/107 (7.5%) 38/152 (25%) Respiratory 33/259 (13%) 24/107 (22%) 9/152 (5.9%) Device-related 25/259 (9.7%) 15/107 (14%) 10/152 (6.6%) Immunosuppressants 25/259 (9.7%) 9/107 (8.4%) 16/152 (11%) Malignancy 45/259 (17%) 12/107 (11%) 33/152 (22%) Hemodialysis 29/259 (11%) 14/107 (13%) 15/152 (9.9%) Catheter/devices 54/259 (21%) 30/107 (28%) 24/152 (16%) Antibiotic Change 82/259 (32%) 36/107 (34%) 46/152 (30%) Clinical parameters : qSOFA 0 17/173 (9.8%) 9/67 (13%) 8/106 (7.5%) 1 67/173 (39%) 30/67 (45%) 37/106 (35%) 2 69/173 (40%) 21/67 (31%) 48/106 (45%) 3 20/173 (12%) 7/67 (10%) 13/106 (12%) Vital signs : Mean blood pressure, mmHg 91.0 [74.0–105.0] 93.0 [74.8–112.0] 90.0 [74.0–103.0] Pulse rate, beats/min 105.0 [91.3–120.0] 108.0 [92.0–116.0] 101.0 [91.0–123.0] Respiratory rate, breaths/min 24.0 [20.0–30.0] 24.0 [20.0–30.0] 24.0 [19.8–28.0] SpO 2 , % 97.0 [95.0–98.0] 97.0 [95.0–98.0] 97.0 [95.0–98.0] Impaired consciousness 140/187 (75%) 48/75 (64%) 92/112 (82%) Laboratory data : WBC, ×10³/µL 98.5 [35.5–149.3] 100.0 [18.1–141.5] 98.0 [41.8–152.3] Hb, g/dL 11.4 [10.0–13.4] 11.6 [9.9–13.5] 11.4 [10.0–13.3] Sodium, mEq/L 138.0 [134.0–141.0] 138.0 [135.0–141.0] 138.0 [134.0–141.0] Potassium, mEq/L 4.1 [3.6–4.5] 4.2 [3.8–4.5] 4.0 [3.5–4.5] Lactate, mmol/L 2.1 [1.4–4.0] 1.9 [1.3–3.7] 2.5 [1.5–4.2] Albumin, g/dL 2.9 [2.3–3.5] 2.8 [2.3–3.4] 3.0 [2.4–3.5] Bilirubin, mg/dL 0.9 [0.6–1.4] 0.8 [0.6–1.2] 1.0 [0.7–1.8] BUN, mg/dL 28.4 [18.7–43.6] 29.8 [17.5–47.6] 28.2 [19.2–40.1] Creatinine, mg/dL 1.3 [0.9–2.4] 1.2 [0.8–2.8] 1.3 [0.9–2.2] CRP, mg/dL 12.0 [4.4–21.1] 12.7 [5.1–22.9] 11.8 [4.1–20.3] Outcome 7-day mortality 18/259 (6.9%) 12/107 (11%) 6/152 (3.9%) 28-day mortality 28/259 (11%) 18/107 (17%) 10/152 (6.6%) Sepsis 158/259 (61%) 60/107 (56%) 98/152 (64%) Septic shock 69/259 (27%) 27/107 (25%) 42/152 (28%) Data are n (percentage), median [interquartile range]. BUN: blood urea nitrogen, CRP: C-reactive protein, GNR: gram-negative rods, GPC: gram-positive cocci, Hb: hemoglobin, qSOFA: quick Sequential Organ Failure Assessment, SpO 2 : peripheral oxygen saturation, WBC: white blood cell count. The distribution of bacterial species Figure 2 illustrates the distribution of bacterial species in each group. In the GPC group, Staphylococcus aureus ( S. aureus ) was the predominant pathogen (32.1%), consisting of methicillin-susceptible S. aureus (MSSA; 25.5%) and methicillin-resistant S. aureus (MRSA; 6.6%). Other major pathogens included Streptococcus pneumoniae (9.4%), Group G Streptococcus (7.6%), and Enterococcus faecalis (4.7%). In the GNR group, Escherichia coli ( E. coli ) was the most common pathogen (66.4%), with non-extended-spectrum beta-lactamase (ESBL) strains accounting for 57.2% and ESBL-producing strains accounting for 9.2%. Other GNR species included Klebsiella pneumoniae (7.2%), Proteus mirabilis (4.0%), and Klebsiella oxytoca (2.6%). Association between bacteria group and outcomes The proportions of clinical outcomes for each bacteremia group are presented in Fig. 3 . As shown in Table 2 , the comparison of the GPC and GNR bacteremia groups demonstrated that the GPC group showed higher mortality at both 7 days (11.3% vs. 3.9%) and 28 days (17.0% vs. 6.6%) after admission. While sepsis was diagnosed less frequently in the GPC group (55.7% vs. 64.5%), the occurrence of septic shock was similar in the groups (24.5% vs. 27.6%). Table 2 Association between the bacteremia group (GPC vs. GNR) and outcomes Outcome GPC group n/N (%) GNR group n/N (%) Adjusted risk difference (95%CI)* Adjusted risk ratio (95%CI)* 7-day mortality 12/107 (11.3) 6/152 (3.9) 8.9% (1.3 to 16.4) 3.48 (1.29–9.36) 28-day mortality 18/107 (17.0) 10/152 (6.6) 10.6% (1.8 to 19.5) 2.65 (1.21–5.83) Sepsis 60/107 (55.7) 98/152 (64.5) −12.8% (− 24.7 to − 0.8) 0.81 (0.66–0.99) Septic shock 27/107 (24.5) 42/152 (27.6) −6.1% (− 17.2 to 5.0) 0.79 (0.51–1.22) *Adjusted risk differences and risk ratios were estimated using the modified Poisson and least-squares regression analyses, adjusting for the following covariates: age, sex, use of steroids or immunosuppressive drugs, presence of malignancy, and hemodialysis. The GNR group served as the reference group for all analyses. GNR: gram-negative rod, GPC: gram-positive cocci. After the adjustment for confounders, we observed that GPC bacteremia was associated with higher 7-day mortality (aRD 8.9%, 95%CI: 1.3–16.4; aRR 3.48, 95%CI: 1.29–9.36) and higher 28-day mortality (aRD 10.6%, 95%CI: 1.8–19.5; aRR 2.65, 95%CI: 1.21–5.83) compared to GNR bacteremia. GPC bacteremia was also associated with a lower risk of sepsis diagnosis (aRD − 12.8%, 95%CI: −24.7 to − 0.8; aRR 0.81, 95%CI: 0.66–0.99). There was no significant between-group difference in the rate of septic shock (aRD − 6.1%, 95%CI: −17.2 to 5.0; aRR 0.79, 95%CI: 0.51–1.22). Additional analyses As shown in Table 3 , among the group of patients with sepsis (n = 158), GPC bacteremia was associated with higher mortality at both 7 days (aRD 8.8%, 95%CI: 0.3–17.3; aRR 5.84, 95%CI: 1.40–24.35) and 28 days (aRD 10.0%, 95%CI: −0.5 to 20.5; aRR 2.60, 95%CI: 0.89–7.63) compared to GNR bacteremia. No significant between-group differences were identified for septic shock in both the crude analysis (43.3% vs. 42.9%) and adjusted analysis (aRD − 0.6%, 95%CI: −16.7 to 15.4; aRR 0.97, 95%CI: 0.67–1.41). Table 3 Additional analyses: association between the bacteremia group (GPC vs. GNR) and outcomes in patients diagnosed with sepsis Outcomes GPC sepsis group n/N (%) GNR sepsis group n/N (%) Adjusted risk difference (95%CI)* Adjusted risk ratio (95%CI)* 7-day mortality 6/60 (10.0) 2/98 (2.0) 8.8% (0.3 to 17.3) 5.84 (1.40 to 24.35) 28-day mortality 10/60 (16.7) 5/98 (5.1) 10.0% (− 0.5 to 20.5) 2.60 (0.89 to 7.63) Septic shock 26/60 (43.3) 42/98 (42.9) −0.6% (− 16.7 to 15.4) 0.97 (0.67 to 1.41) *Adjusted risk differences and risk ratios were estimated using the modified Poisson and least-squares regression analyses, adjusting for the following covariates: age, sex, use of steroids or immunosuppressive drugs, presence of malignancy, and hemodialysis. The GNR group served as the reference group for this table. GNR: gram-negative rod, GPC: gram-positive cocci. As shown in Table 4 , our comparison of the most common causative pathogens revealed that S. aureus bacteremia (MSSA and MRSA combined; n = 37) was associated with higher mortality compared to E. coli bacteremia (ESBL and non-ESBL strains combined; n = 102) at both 7 days (aRD 12.2%, 95%CI: −0.9 to 25.3; aRR 5.10, 95%CI: 1.15–22.76) and 28 days (aRD 11.6%, 95%CI: −2.4 to 25.6; aRR 3.12, 95%CI: 0.81–12.01). After the adjustment for confounders, no significant between-group differences were observed for sepsis diagnosis (aRD − 12.2%, 95%CI: −29.8 to 5.4; aRR 0.82, 95%CI: 0.59–1.13) or septic shock (aRD − 12.2%, 95%CI: −28.0 to 3.6; aRR 0.60, 95%CI: 0.30–1.19). Table 4 Additional analyses: association between most common causative pathogens ( S. aureus vs. E. coli ) and outcomes Outcomes S. aureus group n/N (%) E. coli group n/N (%) Adjusted risk difference (95%CI)* Adjusted risk ratio (95%CI)* 7-day mortality 5/37 (13.5) 3/102 (2.9) 12.2% (− 0.9 to 25.3) 5.10 (1.15 to 22.76) 28-day mortality 6/37 (16.2) 5/102 (4.9) 11.6% (− 2.4 to 25.6) 3.12 (0.81 to 12.01) Sepsis 20/37 (54.1) 60/102 (58.8) −12.2% (− 29.8 to 5.4) 0.82 (0.59 to 1.13) Septic shock 8/37 (21.6) 28/102 (27.5) −12.2% (− 28.0 to 3.6) 0.60 (0.30 to 1.19) *Adjusted risk differences and risk ratios were estimated using the modified Poisson and least-squares regression analyses, adjusting for the following covariates: age, sex, use of steroids or immunosuppressive drugs, presence of malignancy, and hemodialysis. The E. coli group served as the reference group for this Table. S. aureus: Staphylococcus aureus, E. coli: Escherichia coli. DISCUSSION Summary of findings We compared clinical outcomes between GPC bacteremia and GNR bacteremia in 259 adult patients suspected of having an infection and were admitted to an ICU or ED. The most common causative pathogens were S. aureus for GPC bacteremia and E. coli for GNR bacteremia. Having quantified the association using ratio measures and difference measures, we observed that GPC bacteremia was associated with higher mortality at both 7 and 28 days after ICU admission compared to GNR bacteremia, despite having a lower risk of sepsis and septic shock diagnoses. The association between GPC bacteremia and higher mortality was consistently observed in both of our additional analyses, i.e., among the patients with sepsis and in the comparison of the most common pathogens ( S. aureus vs. E. coli ). Notably, although the initial presentation of the patients with GPC bacteremia was less severe with a lower risk of sepsis diagnosis, the patients with GPC bacteremia demonstrated consistently higher mortality across all analyses after adjustment for confounders. Comparison with extant research and implications Several research groups have reported differences in pathogenic mechanisms between GPC and GNR bacteremia [ 8 – 10 , 25 , 26 ]. The meta-analysis by Tang et al. revealed that sepsis caused by GNR bacteria was more severe than that caused by GPC bacteria, with significantly higher concentrations of inflammatory factors in their GNR group [ 27 ]. Abe et al. reported that in Japan, GNR bacteremia was associated with significantly higher blood concentrations of CRP and interleukin (IL)-6 compared to GPC bacteremia [ 14 ]. They also observed that among ICU patients with bacteremia and septic shock, the incidence of GNR bacteremia was significantly higher than that in patients with sepsis or severe sepsis. These findings suggest that GNR bacteremia is associated with more severe inflammatory responses and higher rates of septic shock compared to GPC bacteremia. However, varying results regarding survival rates have been obtained. Tang et al.'s analyses revealed no significant differences in the survival rate, coagulation function, length of stay, APACHE II score, or SOFA score between GNR and GPC groups [ 27 ]. A possible reason for the discrepancy between the meta-analysis and our present findings is the difference in the causative bacterial strains between Japan and other regions/countries. Several studies have demonstrated that the mortality of patients with sepsis varies depending on the causative bacteria [ 28 – 31 ]. In the present investigation, S. aureus was the most common GPC bacterium and E. coli was the most common GNR bacterium, whereas the meta-analysis indicated that S. aureus and Pseudomonas aeruginosa were the most common bacteria for GPC and GNR bacteremia, respectively [ 27 ]. In a study conducted in Japan, about half of the cases were caused by E. coli and only 9% were caused by P. aeruginosa . Moreover, there was a two-fold difference in the 7-day mortality rate ( E. coli 4.0% vs. Pseudomonas 10.3%) [ 32 ]. In our study, the proportion of cases caused by E. coli was 66.4%, while P. aeruginosa accounted for only 3.3%. This significant difference in pathogen distribution may explain why our GNR group showed a relatively lower mortality trend compared to the GPC group. This discrepancy between our findings and international data likely reflects regional differences in infection sources. The higher prevalence of P. aeruginosa in the international studies may be attributed to ventilator-associated pneumonia cases, which are less common in our cohort (in which urinary tract infections were predominant among the GNR cases). It has been suggested that respiratory infections generally carry a worse prognosis than urinary-source infections [ 33 ]. The favorable outcomes in our GNR group likely reflect the high proportion of urinary tract infections, which typically show a good treatment response despite the initial severe presentation. In addition, antimicrobial resistance patterns differ significantly between Japan and other countries. Investigations performed in settings outside Japan have reported higher rates of resistant organisms, particularly among non-fermenting GNR bacteria like P. aeruginosa [ 34 ]. The incidence and mortality of GPC-induced sepsis have been increasing in both Japan and elsewhere, with resistant GPCs such as MRSA on the rise [ 35 – 37 ]. Indeed, our additional analysis focusing on S. aureus and E. coli revealed that the patients infected with S. aureus had significantly higher odds of 7-day mortality. Study limitations Several study limitations should be addressed. We did not account for polymicrobial infections, which could potentially influence clinical outcomes and treatment responses. We also did not measure the SOFA scores or detailed inflammatory markers, which might have provided a more comprehensive assessment of disease severity and host response patterns. Moreover, as with all observational studies, we cannot completely eliminate the influence of unmeasured confounding factors despite our attempts to adjust for key variables. The study's retrospective design also introduces potential selection bias, particularly in the identification of sepsis and septic shock cases. Although we used established clinical surveillance criteria, their retrospective application may have missed some nuances in the patients' clinical presentations. In addition, our findings from two Japanese tertiary care centers may not be generalizable to different healthcare settings or geographical regions with varying bacterial epidemiology and resistance patterns. Our analyses did not incorporate antimicrobial prescription patterns such as empirical treatment regimens and targeted treatment regimens, which can significantly affect patient outcomes and treatment efficacy. Finally, we could not fully account for differences in treatment approaches, including the timing of appropriate antimicrobial therapy and source control measures, which are known to significantly impact the outcomes of patients with bacteremia. Conclusions Our analyses of 259 critically ill patients requiring ICU or emergency ward admission revealed that after an adjustment for several potential confounding factors, the difference in bacterial species (GPC or GNR) is a crucial factor in the clinical course and prognosis of patients with sepsis. Our results demonstrated that the mortality associated with GPC bacteremia was higher than that of GNR bacteremia. We speculate that differences in the causative bacterial strains of GNR bacteremia between Japan and other countries, as well as the increase in MRSA, may contribute to these observed disparities. These findings highlight the importance of identifying bacterial species and implementing appropriate treatment strategies in the management and treatment of patients with sepsis. Future research should focus on these differences to further clarify the pathophysiology of sepsis and improve treatment outcomes. Abbreviations APACHE II Acute Physiology and Chronic Health Evaluation II aRD adjusted risk difference aRR adjusted risk ratio CI confidence interval CRP C-reactive protein E. coli Escherichia coli ED emergency department ESBL extended-spectrum beta-lactamase GNR gram-negative rods GPC gram-positive cocci ICU intensive care unit IL-6 interleukin 6 IQR interquartile range MRSA methicillin-resistant Staphylococcus aureus MSSA methicillin-susceptible Staphylococcus aureus qSOFA Quick Sequential Organ Failure Assessment S. aureus Staphylococcus aureus SOFA Sequential Organ Failure Assessment Declarations Ethics approval and consent to participate: This study was approved by the institutional review boards of Nagasaki University Hospital (approval no. 22112121) and Hitachi General Hospital (approval no. 201795). The requirement for patients' informed consent was waived due to the retrospective nature of the study. Consent for publication: This study protocol was approved by the Ethics Committee of Nagasaki University Hospital and Hitachi General Hospital. Due to the retrospective nature of the study, the requirement for patients' consent for publication was waived. Availability of data and materials: The datasets generated and analyzed in this study are not publicly available because data-sharing is not approved by the Ethics Committee. Competing interests: All of the study's authors declare that they have no competing interests. Funding: No funding was received for this study. Author contributions: TN and SS take responsibility for the study as a whole. TN, SS, and MS conceived the study. SS, MS, TT, and TG supervised the conduct of the study. SS provided statistical advice. TN analyzed the data. JS, IOs, and TS were instrumental in organizing and preparing the data from Hitachi General Hospital, which was crucial for the analysis. TN drafted the manuscript, and all authors contributed substantially to its revision. The content is solely the responsibility of the authors. Acknowledgements : We thank the medical staff at Nagasaki University Hospital and Hitachi General Hospital for their assistance with the data collection. We appreciate the clinical laboratory technicians for providing microbiological data and the ICU and ED nursing staff for their dedication to patient care. References Martin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003;348:1546–54. Imaeda T, Nakada T-A, Takahashi N, Yamao Y, Nakagawa S, Ogura H, et al. Trends in the incidence and outcome of sepsis using data from a Japanese nationwide medical claims database-the Japan Sepsis Alliance (JaSA) study group. Crit Care. 2021;25:338. Ku NS, Kim YC, Kim MH, Song JE, Oh DH, Ahn JY, et al. Risk factors for 28-day mortality in elderly patients with extended-spectrum β-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae bacteremia. Arch Gerontol Geriatr. 2014;58:105–9. Sianipar O, Asmara W, Dwiprahasto I, Mulyono B. Mortality risk of bloodstream infection caused by either Escherichia coli or Klebsiella pneumoniae producing extended-spectrum β-lactamase: a prospective cohort study. BMC Res Notes. 2019;12:719. Digiovine B, Chenoweth C, Watts C, Higgins M. The attributable mortality and costs of primary nosocomial bloodstream infections in the intensive care unit. Am J Respir Crit Care Med. 1999;160:976–81. Komori A, Abe T, Kushimoto S, Ogura H, Shiraishi A, Saitoh D, et al. Characteristics and outcomes of bacteremia among ICU-admitted patients with severe sepsis. Sci Rep. 2020;10:2983. Garrouste-Orgeas M, Timsit JF, Tafflet M, Misset B, Zahar J-R, Soufir L, et al. Excess risk of death from intensive care unit-acquired nosocomial bloodstream infections: a reappraisal. Clin Infect Dis. 2006;42:1118–26. Bearman GML, Wenzel RP. Bacteremias: a leading cause of death. Arch Med Res. 2005;36:646–59. Renaud B, Brun-Buisson C, ICU-Bacteremia Study Group. Outcomes of primary and catheter-related bacteremia. A cohort and case-control study in critically ill patients. Am J Respir Crit Care Med. 2001;163:1584–90. Parrillo JE, Parker MM, Natanson C, Suffredini AF, Danner RL, Cunnion RE, et al. Septic shock in humans. Advances in the understanding of pathogenesis, cardiovascular dysfunction, and therapy. Ann Intern Med. 1990;113:227–42. Identification of key genes in Grampositive and Gramnegative sepsis using stochastic perturbation. Ramachandran G. Gram-positive and gram-negative bacterial toxins in sepsis: a brief review. Virulence. 2014;5:213–8. Wang Q, Li X, Tang W, Guan X, Xiong Z, Zhu Y, et al. Differential gene sets profiling in Gram-negative and Gram-positive sepsis. Front Cell Infect Microbiol. 2022;12:801232. Abe R, Oda S, Sadahiro T, Nakamura M, Hirayama Y, Tateishi Y, et al. Gram-negative bacteremia induces greater magnitude of inflammatory response than Gram-positive bacteremia. Crit Care. 2010;14:R27. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147:573–7. Rhee C, Kadri S, Huang SS, Murphy MV, Li L, Platt R, et al. Objective sepsis surveillance using electronic clinical data. Infect Control Hosp Epidemiol. 2016;37:163–71. Rhee C, Dantes R, Epstein L, Murphy DJ, Seymour CW, Iwashyna TJ, et al. Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009–2014. JAMA. 2017;318:1241. Delahanty RJ, Alvarez J, Flynn LM, Sherwin RL, Jones SS. Development and evaluation of a machine learning model for the early identification of patients at risk for sepsis. Ann Emerg Med. 2019;73:334–44. Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702–6. Cheung YB. A modified least-squares regression approach to the estimation of risk difference. Am J Epidemiol. 2007;166:1337–44. Cheng B, Xie G, Yao S, Wu X, Guo Q, Gu M, et al. Epidemiology of severe sepsis in critically ill surgical patients in ten university hospitals in China. Crit Care Med. 2007;35:2538–46. Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;29:1303–10. Vincent J-L, Sakr Y, Sprung CL, Ranieri VM, Reinhart K, Gerlach H, et al. Sepsis in European intensive care units: results of the SOAP study. Crit Care Med. 2006;34:344–53. Brun-Buisson C, Doyon F, Carlet J. Incidence, risk factors, and outcome of severe sepsis and septic shock in adults: A multicenter prospective study in intensive care units. JAMA. 1995;274:968–74. Akira S, Uematsu S, Takeuchi O. Pathogen recognition and innate immunity. Cell. 2006;124:783–801. Elson G, Dunn-Siegrist I, Daubeuf B, Pugin J. Contribution of Toll-like receptors to the innate immune response to Gram-negative and Gram-positive bacteria. Blood. 2007;109:1574–83. Tang A, Shi Y, Dong Q, Wang S, Ge Y, Wang C, et al. Prognostic differences in sepsis caused by gram-negative bacteria and gram-positive bacteria: a systematic review and meta-analysis. Crit Care. 2023;27:467. Chiang H-Y, Chen T-C, Lin C-C, Ho L-C, Kuo C-C, Chi C-Y. Trend and Predictors of Short-term Mortality of Adult Bacteremia at Emergency Departments: A 14-Year Cohort Study of 14 625 Patients. Open Forum Infect Dis [Internet]. 2021 [cited 2023 Jul 2];8. Available from: https://academic.oup.com/ofid/article-pdf/8/11/ofab 485/41145859/ofab485.pdf Lyytikäinen O, Lumio J, Sarkkinen H, Kolho E, Kostiala A, Ruutu P, et al. Nosocomial bloodstream infections in Finnish hospitals during 1999–2000. Clin Infect Dis. 2002;35:e14-9. Weinstein MP, Towns ML, Quartey SM, Mirrett S, Reimer LG, Parmigiani G, et al. The clinical significance of positive blood cultures in the 1990s: a prospective comprehensive evaluation of the microbiology, epidemiology, and outcome of bacteremia and fungemia in adults. Clin Infect Dis. 1997;24:584–602. Hongmei TW, Evans SJ. Bench-to-Bedside Review: Sepsis, Severe Sepsis and Septic Shock - Does the Nature of the Infecting Organism Matter? Critical Care / the Society of Critical Care Medicine. 2008;12. Kosai K, Yamagishi Y, Mikamo H, Ishii Y, Tateda K, Yanagihara K. Epidemiological analysis and antimicrobial susceptibility profile of Gram-negative bacilli that cause bacteremia in Japan. J Infect Chemother. 2023;29:1091–6. Chen Y, Huang J, Xu J, Qiu R, Lin T. Association between site of infection and mortality in patients with cancer with sepsis or septic shock: A retrospective cohort study. Exp Ther Med. 2023;25:33. Elfadadny A, Ragab RF, AlHarbi M, Badshah F, Ibáñez-Arancibia E, Farag A, et al. Antimicrobial resistance of Pseudomonas aeruginosa: navigating clinical impacts, current resistance trends, and innovations in breaking therapies. Front Microbiol. 2024;15:1374466. Blaskovich MAT, Hansford KA, Butler MS, Ramu S, Kavanagh AM, Jarrad AM, et al. A lipoglycopeptide antibiotic for Gram-positive biofilm-related infections. Sci Transl Med. 2022;14:eabj2381. Guo Q, Qu P, Cui W, Liu M, Zhu H, Chen W, et al. Organism type of infection is associated with prognosis in sepsis: an analysis from the MIMIC-IV database. BMC Infect Dis. 2023;23:431. A lipoglycopeptide antibiotic for gram-positive biofilm-related infections. Sci Transl Med. 2022;14. Additional Declarations No competing interests reported. Supplementary Files bacteremiasupplement20250510nt.docx Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6632548","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":457331252,"identity":"42d95bb8-d47b-40ac-8aa9-cd85b521fa99","order_by":0,"name":"Takaya Nakashima","email":"","orcid":"","institution":"Nagasaki University Graduate School of Biomedical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Takaya","middleName":"","lastName":"Nakashima","suffix":""},{"id":457331253,"identity":"97941c8f-01a1-400d-aeea-04ab0128f8fb","order_by":1,"name":"Shuntaro Sato","email":"data:image/png;base64,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","orcid":"","institution":"Nagasaki University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Shuntaro","middleName":"","lastName":"Sato","suffix":""},{"id":457331254,"identity":"23362174-97cd-43bf-89b8-aaad646b5631","order_by":2,"name":"Motohiro Sekino","email":"","orcid":"","institution":"Nagasaki University Graduate School of Biomedical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Motohiro","middleName":"","lastName":"Sekino","suffix":""},{"id":457331255,"identity":"d59269cf-af89-43ee-b98d-d2ca640c7747","order_by":3,"name":"Takeshi Tanaka","email":"","orcid":"","institution":"Nagasaki University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Takeshi","middleName":"","lastName":"Tanaka","suffix":""},{"id":457331256,"identity":"1280cefc-35a4-494c-b3df-6915e26168cf","order_by":4,"name":"Tomohiro Sonoo","email":"","orcid":"","institution":"TXP Medical Co. Ltd","correspondingAuthor":false,"prefix":"","firstName":"Tomohiro","middleName":"","lastName":"Sonoo","suffix":""},{"id":457331257,"identity":"f3e2aeef-4491-43ea-897f-418db2bacee8","order_by":5,"name":"Tadahiro Goto","email":"","orcid":"","institution":"TXP Medical Co. Ltd","correspondingAuthor":false,"prefix":"","firstName":"Tadahiro","middleName":"","lastName":"Goto","suffix":""},{"id":457331258,"identity":"218137d4-5828-477a-a47d-25203f21c86c","order_by":6,"name":"Junichiro Shibata","email":"","orcid":"","institution":"TXP Medical Co. Ltd","correspondingAuthor":false,"prefix":"","firstName":"Junichiro","middleName":"","lastName":"Shibata","suffix":""},{"id":457331259,"identity":"9601b344-3b72-41a9-b748-886820639e2e","order_by":7,"name":"Itsuki Osawa","email":"","orcid":"","institution":"Columbia University Irving Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Itsuki","middleName":"","lastName":"Osawa","suffix":""},{"id":457331260,"identity":"966e3847-8e9d-465d-bd5d-33191f163460","order_by":8,"name":"Koichi Izumikawa","email":"","orcid":"","institution":"Nagasaki University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Koichi","middleName":"","lastName":"Izumikawa","suffix":""},{"id":457331261,"identity":"834d9837-d14a-4556-9a59-7339153e39e9","order_by":9,"name":"Osamu Tasaki","email":"","orcid":"","institution":"Nagasaki University Hospital Acute \u0026 Critical Care Center","correspondingAuthor":false,"prefix":"","firstName":"Osamu","middleName":"","lastName":"Tasaki","suffix":""},{"id":457331262,"identity":"f890c13a-47ff-4bbd-b7e6-81ab32b4e499","order_by":10,"name":"Tetsuya Hara","email":"","orcid":"","institution":"Nagasaki University Graduate School of Biomedical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Tetsuya","middleName":"","lastName":"Hara","suffix":""}],"badges":[],"createdAt":"2025-05-10 05:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6632548/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6632548/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83143922,"identity":"8c17eed2-673d-43e3-919e-e50f45ef15b3","added_by":"auto","created_at":"2025-05-20 12:41:12","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37085,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flowchart. We divided the patients into two groups based on the bacterial species causing their bacteremia: gram-positive cocci (GPC) or gram-negative rods (GNR). ED: emergency department, ICU: intensive care unit.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6632548/v1/24c6ac2618453c8b2c4f29ea.png"},{"id":83142717,"identity":"552b09b5-7961-4c45-84ad-5a4978aa6973","added_by":"auto","created_at":"2025-05-20 12:33:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":52276,"visible":true,"origin":"","legend":"\u003cp\u003eThe distribution of bacterial species in the patients with gram-positive cocci (GPC) and those with gram-negative rod (GNR) bacteremia. \u003cem\u003eUpper panel:\u003c/em\u003e the GPC distribution, \u003cem\u003elower panel:\u003c/em\u003e GNR distribution, with \u003cem\u003ehorizontal bars\u003c/em\u003e representing the percentage for each bacterial species. \u003cem\u003eE. faecalis\u003c/em\u003e: \u003cem\u003eEnterococcus faecalis\u003c/em\u003e, \u003cem\u003eE. coli\u003c/em\u003e: \u003cem\u003eEscherichia coli\u003c/em\u003e, ESBL: extended-spectrum beta-lactamases, \u003cem\u003eK. oxytoca\u003c/em\u003e: \u003cem\u003eKlebsiella oxytoca\u003c/em\u003e, \u003cem\u003eK. pneumoniae\u003c/em\u003e: \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, MRSA: methicillin-resistant \u003cem\u003eS. aureus\u003c/em\u003e, MSSA: methicillin-susceptible \u003cem\u003eS. aureus\u003c/em\u003e, \u003cem\u003eP. mirabilis\u003c/em\u003e: \u003cem\u003eProteus mirabilis\u003c/em\u003e, \u003cem\u003eS. aureus\u003c/em\u003e: \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003eSt. pneumoniae\u003c/em\u003e: \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6632548/v1/6ebba3d014678aef04d9b468.png"},{"id":83142714,"identity":"5d47d4f8-9f82-4284-826c-fb743f7421c4","added_by":"auto","created_at":"2025-05-20 12:33:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":63591,"visible":true,"origin":"","legend":"\u003cp\u003eThe clinical outcomes of the patients with GPC bacteremia and those with GNR bacteremia. The proportions of clinical outcomes in each group are shown.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6632548/v1/bf0fbc2df31b678df221bcfd.png"},{"id":84274969,"identity":"fee939e6-bdb0-4a34-87e5-cbd16485df4d","added_by":"auto","created_at":"2025-06-10 05:32:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1340992,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6632548/v1/ce5b0466-df53-4849-8247-6b905138d339.pdf"},{"id":83142725,"identity":"612261b7-dfd0-482b-a577-67119e2b44b3","added_by":"auto","created_at":"2025-05-20 12:33:12","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":17888,"visible":true,"origin":"","legend":"","description":"","filename":"bacteremiasupplement20250510nt.docx","url":"https://assets-eu.researchsquare.com/files/rs-6632548/v1/9655ed5c7583681f37c4219e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Associations of Gram-Positive Cocci and Gram-Negative Rods with Disease Severity and Mortality in Critically Ill Patients: A Retrospective Cohort Study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eDespite the latest advances in intensive care medicine, the mortality rate of patients with sepsis remains high [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Bacteremia caused by various infectious diseases often leads to sepsis. Approximately half of intensive care unit (ICU) patients with severe sepsis have bacteremia, and these patients often have more severe clinical conditions and poorer outcomes [\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Early intervention is crucial for improving the survival of patients with sepsis, and the rapid identification of the causative bacteria and appropriate antimicrobial therapy are key elements of effective treatment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMost cases of bacteremia are caused by either gram-positive cocci (GPC) or gram-negative rods (GNR), which exhibit distinct pathogenic mechanisms and clinical manifestations [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although these differences could potentially influence patient outcomes, the relationships between bacterial species and clinical outcomes have not been established, due to several limitations. First, most of the relevant studies did not sufficiently adjust their analyses for important confounding factors such as age and comorbidities [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Second, the heterogeneity in study settings (e.g., community vs. hospital-acquired infections) and patient populations has made it difficult to draw definitive conclusions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study we determined the clinical outcomes of GPC and GNR bacteremia in critically ill patients at two tertiary care centers, and we evaluated the relationship between the bacterial species causing sepsis and the patients' clinical outcomes. By focusing on a well-defined population in the emergency department (ED) and ICU settings and adjusting for key confounding factors, we seek to provide more precise evidence regarding the impact of various bacterial species on patient outcomes. This knowledge will help clinicians better understand the prognostic implications of different bacterial species and potentially guide treatment strategies for bacteremia in the critical care setting.\u003c/p\u003e"},{"header":"PATIENTS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis retrospective, multicenter study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology statement [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. We used two databases: (1) that of Nagasaki University Hospital for the period from January 1, 2020 to August 31, 2022 and (2) the ED data from Hitachi General Hospital for the period from April 1, 2018, to March 31, 2020. Nagasaki University Hospital and Hitachi General Hospital are both tertiary care centers in Japan with approx. 5,000 and 20,000 annual ED visits, respectively. This study was approved by the institutional review boards of Nagasaki University Hospital (approval no. 22112121) and Hitachi General Hospital (approval no. 201795). The requirement for informed consent was waived due to the retrospective nature of the study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatients\u003c/h3\u003e\n\u003cp\u003eWe included the cases of the adult patients (\u0026ge;\u0026thinsp;18 years) with positive blood cultures who initially presented to either of the above-mentioned hospitals' ED and had suspected infections (as determined by the attending physician). All patients required two sets of blood cultures and were admitted to the ICU or emergency ward on the same day. We defined the presence of bacteriemia as positive results on both sets of submitted blood cultures.\u003c/p\u003e\n\u003ch3\u003eMeasurement variables\u003c/h3\u003e\n\u003cp\u003eWe collected the patients' data from their electronic medical records. The clinical characteristics included age, sex, suspected infection site(s), presence of malignancy, chronic hemodialysis status, and use of vascular or other medical devices (central venous catheter, peripheral line, and implanted medical devices) before visiting the ED. The physiological data on admission included vital signs (mean blood pressure, pulse rate, respiratory rate, oxygen saturation, and consciousness level) and the quick Sequential Organ Failure Assessment (qSOFA) score. The laboratory measurements on admission included the white blood cell count, hemoglobin, sodium, potassium, blood urea nitrogen, creatinine, albumin, bilirubin, C-reactive protein (CRP), and lactate levels. The treatment data included antibiotic change, use of immunosuppressants such as steroids, and renal replacement therapy. Antibiotic change was defined as the administration of more than one type of antibiotic within 48 hr after the patient's blood culture collection. The proportion of missing data for each variable is presented in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\n\u003ch3\u003eExposure and outcome\u003c/h3\u003e\n\u003cp\u003eThe exposure was GPC or GNR bacteremia at ED arrival based on blood culture results. The primary outcomes were the mortality rates at 7 days and 28 days after admission. The secondary outcomes were diagnoses of sepsis and septic shock respectively, defined using modified sepsis clinical surveillance criteria [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] \u003cb\u003e(\u003c/b\u003eSuppl. Table S2). These diagnoses were determined based on clinical and laboratory data collected within 2 days of the blood culture day, as specified in the surveillance criteria. Septic shock was defined as the presence of sepsis requiring a vasopressor (noradrenaline, dopamine, adrenaline, phenylephrine, or vasopressin) plus a lactate level\u0026thinsp;\u0026ge;\u0026thinsp;2.0 mmol/L.\u003c/p\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eWe used summary statistics to describe the characteristics of the patients presenting with suspected infection to the ED and compared each variable between the groups of patients with GPC bacteremia and GNR bacteremia. Categorical variables are expressed as numbers and percentages. Continuous variables are expressed as the median and interquartile range (IQR).\u003c/p\u003e \u003cp\u003eWe examined the association between bacterial types (GPC vs. GNR) and outcomes (7-day and 28-day mortality, sepsis, and septic shock) using two complementary approaches. We calculated the adjusted risk differences (aRDs) and the adjusted risk ratios (aRRs) between the GPC and GNR groups using modified Poisson and least-squares regression analyses [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. We adjusted for the following potential confounders based on previous studies: age, sex, malignancy, immunosuppressant use, chronic hemodialysis status, and previous use of vascular or other medical devices [\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. We used robust variance to determine the 95% confidence interval (CI) of the aRD values. All analyses were conducted using R ver. 4.2.2 (R Foundation, Vienna, Austria), with the 'rqlm' package for the estimations of the aRR and aRD values .\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAdditional analyses\u003c/h2\u003e \u003cp\u003eWe conducted two additional analyses to further examine the relationship between bacterial types and outcomes. First, to compare outcomes in patients who were already in a severe condition on admission, we analyzed the subset of patients diagnosed with sepsis at admission, focusing on septic shock and sepsis-related mortality as outcomes. Second, we compared outcomes between the most common causative pathogens identified in each bacterial group. Both additional analyses were conducted using the same approaches as the main analysis: regression to estimate aRDs and aRRs, adjusting for the same set of confounders.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePatient flow\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, among the 1,346 eligible patients with bacteremia, 259 were included in the final analysis after the exclusion of 1,073 patients based on the predetermined study criteria including contamination, repeated hospitalizations, and presence of bacteria other than GPC or GNR. The final cohort was 107 patients with GPC bacteremia (41.3% of the total series) and 152 patients with GNR bacteremia (58.7%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eThe patients' baseline characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the baseline characteristics of the patients in the two groups. The median age was 73 years in the GPC group and 78 years in the GNR group. The GPC group had higher proportions of males (65%) and respiratory infections (22%), and the GNR group showed a higher prevalence of genitourinary infections (25%) and more frequent presence of malignancy (22% vs. 11%). Vascular device use was more common in the GPC group versus the GNR group (28% vs. 16%). Regarding severity measures, the GNR group demonstrated higher qSOFA scores (qSOFA\u0026thinsp;\u0026ge;\u0026thinsp;2: 57% vs. 41%) and lactate levels (2.5 vs. 1.9 mmol/L). The laboratory data showed variations between the two groups, with differences in inflammatory markers and organ function parameters.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics on admission and outcome between GPC and GNR bacteremia\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;259\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMicroorganism\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGPC\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;107 (41.3%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGNR\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;152 (58.7%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, yrs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77.0 [67.0\u0026ndash;84.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.0 [62.0\u0026ndash;83.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.0 [69.8\u0026ndash;85.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141/259 (54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70/107 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71/152 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSuspected infection organ (Top 3):\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenitourinary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46/259 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8/107 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38/152 (25%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33/259 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24/107 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9/152 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDevice-related\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25/259 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15/107 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10/152 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmunosuppressants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25/259 (9.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/107 (8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16/152 (11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalignancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45/259 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12/107 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33/152 (22%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemodialysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29/259 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14/107 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15/152 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatheter/devices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54/259 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30/107 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24/152 (16%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibiotic Change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82/259 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36/107 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46/152 (30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical parameters\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eqSOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17/173 (9.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/67 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8/106 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67/173 (39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30/67 (45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37/106 (35%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69/173 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21/67 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48/106 (45%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20/173 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7/67 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13/106 (12%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVital signs\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean blood pressure, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91.0 [74.0\u0026ndash;105.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.0 [74.8\u0026ndash;112.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.0 [74.0\u0026ndash;103.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulse rate, beats/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105.0 [91.3\u0026ndash;120.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108.0 [92.0\u0026ndash;116.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101.0 [91.0\u0026ndash;123.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory rate, breaths/min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.0 [20.0\u0026ndash;30.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.0 [20.0\u0026ndash;30.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.0 [19.8\u0026ndash;28.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpO\u003csub\u003e2\u003c/sub\u003e, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97.0 [95.0\u0026ndash;98.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.0 [95.0\u0026ndash;98.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.0 [95.0\u0026ndash;98.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired consciousness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140/187 (75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48/75 (64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92/112 (82%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory data\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC, \u0026times;10\u0026sup3;/\u0026micro;L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98.5 [35.5\u0026ndash;149.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0 [18.1\u0026ndash;141.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.0 [41.8\u0026ndash;152.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHb, g/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.4 [10.0\u0026ndash;13.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.6 [9.9\u0026ndash;13.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.4 [10.0\u0026ndash;13.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium, mEq/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138.0 [134.0\u0026ndash;141.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138.0 [135.0\u0026ndash;141.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e138.0 [134.0\u0026ndash;141.0]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium, mEq/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.1 [3.6\u0026ndash;4.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.2 [3.8\u0026ndash;4.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.0 [3.5\u0026ndash;4.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1 [1.4\u0026ndash;4.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.9 [1.3\u0026ndash;3.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5 [1.5\u0026ndash;4.2]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin, g/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9 [2.3\u0026ndash;3.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8 [2.3\u0026ndash;3.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0 [2.4\u0026ndash;3.5]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBilirubin, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9 [0.6\u0026ndash;1.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 [0.6\u0026ndash;1.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 [0.7\u0026ndash;1.8]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBUN, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.4 [18.7\u0026ndash;43.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.8 [17.5\u0026ndash;47.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.2 [19.2\u0026ndash;40.1]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3 [0.9\u0026ndash;2.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2 [0.8\u0026ndash;2.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.3 [0.9\u0026ndash;2.2]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP, mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.0 [4.4\u0026ndash;21.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.7 [5.1\u0026ndash;22.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.8 [4.1\u0026ndash;20.3]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOutcome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18/259 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12/107 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6/152 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28/259 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18/107 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10/152 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158/259 (61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60/107 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98/152 (64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeptic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69/259 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27/107 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42/152 (28%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are n (percentage), median [interquartile range]. BUN: blood urea nitrogen, CRP: C-reactive protein, GNR: gram-negative rods, GPC: gram-positive cocci, Hb: hemoglobin, qSOFA: quick Sequential Organ Failure Assessment, SpO\u003csub\u003e2\u003c/sub\u003e: peripheral oxygen saturation, WBC: white blood cell count.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe distribution of bacterial species\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the distribution of bacterial species in each group. In the GPC group, \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (\u003cem\u003eS. aureus\u003c/em\u003e) was the predominant pathogen (32.1%), consisting of methicillin-susceptible \u003cem\u003eS. aureus\u003c/em\u003e (MSSA; 25.5%) and methicillin-resistant \u003cem\u003eS. aureus\u003c/em\u003e (MRSA; 6.6%). Other major pathogens included \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e (9.4%), \u003cem\u003eGroup G Streptococcus\u003c/em\u003e (7.6%), and \u003cem\u003eEnterococcus faecalis\u003c/em\u003e (4.7%).\u003c/p\u003e \u003cp\u003eIn the GNR group, \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003eE. coli\u003c/em\u003e) was the most common pathogen (66.4%), with non-extended-spectrum beta-lactamase (ESBL) strains accounting for 57.2% and ESBL-producing strains accounting for 9.2%. Other GNR species included \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (7.2%), \u003cem\u003eProteus mirabilis\u003c/em\u003e (4.0%), and \u003cem\u003eKlebsiella oxytoca\u003c/em\u003e (2.6%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between bacteria group and outcomes\u003c/h2\u003e \u003cp\u003eThe proportions of clinical outcomes for each bacteremia group are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the comparison of the GPC and GNR bacteremia groups demonstrated that the GPC group showed higher mortality at both 7 days (11.3% vs. 3.9%) and 28 days (17.0% vs. 6.6%) after admission. While sepsis was diagnosed less frequently in the GPC group (55.7% vs. 64.5%), the occurrence of septic shock was similar in the groups (24.5% vs. 27.6%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between the bacteremia group (GPC vs. GNR) and outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGPC group\u003c/p\u003e \u003cp\u003en/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGNR group\u003c/p\u003e \u003cp\u003en/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted risk difference (95%CI)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted risk ratio\u003c/p\u003e \u003cp\u003e(95%CI)*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12/107 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6/152 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.9% (1.3 to 16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.48 (1.29\u0026ndash;9.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18/107 (17.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10/152 (6.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6% (1.8 to 19.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.65 (1.21\u0026ndash;5.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60/107 (55.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98/152 (64.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;12.8% (\u0026minus;\u0026thinsp;24.7 to \u0026minus;\u0026thinsp;0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.81 (0.66\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeptic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27/107 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42/152 (27.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;6.1% (\u0026minus;\u0026thinsp;17.2 to 5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.79 (0.51\u0026ndash;1.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Adjusted risk differences and risk ratios were estimated using the modified Poisson and least-squares regression analyses, adjusting for the following covariates: age, sex, use of steroids or immunosuppressive drugs, presence of malignancy, and hemodialysis. The GNR group served as the reference group for all analyses. GNR: gram-negative rod, GPC: gram-positive cocci.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAfter the adjustment for confounders, we observed that GPC bacteremia was associated with higher 7-day mortality (aRD 8.9%, 95%CI: 1.3\u0026ndash;16.4; aRR 3.48, 95%CI: 1.29\u0026ndash;9.36) and higher 28-day mortality (aRD 10.6%, 95%CI: 1.8\u0026ndash;19.5; aRR 2.65, 95%CI: 1.21\u0026ndash;5.83) compared to GNR bacteremia. GPC bacteremia was also associated with a lower risk of sepsis diagnosis (aRD \u0026minus;\u0026thinsp;12.8%, 95%CI: \u0026minus;24.7 to \u0026minus;\u0026thinsp;0.8; aRR 0.81, 95%CI: 0.66\u0026ndash;0.99). There was no significant between-group difference in the rate of septic shock (aRD \u0026minus;\u0026thinsp;6.1%, 95%CI: \u0026minus;17.2 to 5.0; aRR 0.79, 95%CI: 0.51\u0026ndash;1.22).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAdditional analyses\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, among the group of patients with sepsis (n\u0026thinsp;=\u0026thinsp;158), GPC bacteremia was associated with higher mortality at both 7 days (aRD 8.8%, 95%CI: 0.3\u0026ndash;17.3; aRR 5.84, 95%CI: 1.40\u0026ndash;24.35) and 28 days (aRD 10.0%, 95%CI: \u0026minus;0.5 to 20.5; aRR 2.60, 95%CI: 0.89\u0026ndash;7.63) compared to GNR bacteremia. No significant between-group differences were identified for septic shock in both the crude analysis (43.3% vs. 42.9%) and adjusted analysis (aRD \u0026minus;\u0026thinsp;0.6%, 95%CI: \u0026minus;16.7 to 15.4; aRR 0.97, 95%CI: 0.67\u0026ndash;1.41).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdditional analyses: association between the bacteremia group (GPC vs. GNR) and outcomes in patients diagnosed with sepsis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGPC sepsis group\u003c/p\u003e \u003cp\u003en/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGNR sepsis group\u003c/p\u003e \u003cp\u003en/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted risk difference (95%CI)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted risk ratio (95%CI)*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6/60 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2/98 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.8% (0.3 to 17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.84 (1.40 to 24.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10/60 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5/98 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.0% (\u0026minus;\u0026thinsp;0.5 to 20.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.60 (0.89 to 7.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeptic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26/60 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42/98 (42.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.6% (\u0026minus;\u0026thinsp;16.7 to 15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97 (0.67 to 1.41)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Adjusted risk differences and risk ratios were estimated using the modified Poisson and least-squares regression analyses, adjusting for the following covariates: age, sex, use of steroids or immunosuppressive drugs, presence of malignancy, and hemodialysis. The GNR group served as the reference group for this table. GNR: gram-negative rod, GPC: gram-positive cocci.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, our comparison of the most common causative pathogens revealed that \u003cem\u003eS. aureus\u003c/em\u003e bacteremia (MSSA and MRSA combined; n\u0026thinsp;=\u0026thinsp;37) was associated with higher mortality compared to \u003cem\u003eE. coli\u003c/em\u003e bacteremia (ESBL and non-ESBL strains combined; n\u0026thinsp;=\u0026thinsp;102) at both 7 days (aRD 12.2%, 95%CI: \u0026minus;0.9 to 25.3; aRR 5.10, 95%CI: 1.15\u0026ndash;22.76) and 28 days (aRD 11.6%, 95%CI: \u0026minus;2.4 to 25.6; aRR 3.12, 95%CI: 0.81\u0026ndash;12.01). After the adjustment for confounders, no significant between-group differences were observed for sepsis diagnosis (aRD \u0026minus;\u0026thinsp;12.2%, 95%CI: \u0026minus;29.8 to 5.4; aRR 0.82, 95%CI: 0.59\u0026ndash;1.13) or septic shock (aRD \u0026minus;\u0026thinsp;12.2%, 95%CI: \u0026minus;28.0 to 3.6; aRR 0.60, 95%CI: 0.30\u0026ndash;1.19).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdditional analyses: association between most common causative pathogens (\u003cem\u003eS. aureus\u003c/em\u003e vs. \u003cem\u003eE. coli\u003c/em\u003e) and outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS. aureus group\u003c/p\u003e \u003cp\u003en/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE. coli group\u003c/p\u003e \u003cp\u003en/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted risk difference (95%CI)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted risk ratio (95%CI)*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5/37 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3/102 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.2% (\u0026minus;\u0026thinsp;0.9 to 25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.10 (1.15 to 22.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6/37 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5/102 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.6% (\u0026minus;\u0026thinsp;2.4 to 25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.12 (0.81 to 12.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20/37 (54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60/102 (58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;12.2% (\u0026minus;\u0026thinsp;29.8 to 5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82 (0.59 to 1.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeptic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8/37 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28/102 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;12.2% (\u0026minus;\u0026thinsp;28.0 to 3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.60 (0.30 to 1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Adjusted risk differences and risk ratios were estimated using the modified Poisson and least-squares regression analyses, adjusting for the following covariates: age, sex, use of steroids or immunosuppressive drugs, presence of malignancy, and hemodialysis. The \u003cb\u003eE. coli group served as the reference group for this Table. S. aureus: Staphylococcus aureus, E. coli: Escherichia coli.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSummary of findings\u003c/h2\u003e \u003cp\u003eWe compared clinical outcomes between GPC bacteremia and GNR bacteremia in 259 adult patients suspected of having an infection and were admitted to an ICU or ED. The most common causative pathogens were \u003cem\u003eS. aureus\u003c/em\u003e for GPC bacteremia and \u003cem\u003eE. coli\u003c/em\u003e for GNR bacteremia. Having quantified the association using ratio measures and difference measures, we observed that GPC bacteremia was associated with higher mortality at both 7 and 28 days after ICU admission compared to GNR bacteremia, despite having a lower risk of sepsis and septic shock diagnoses. The association between GPC bacteremia and higher mortality was consistently observed in both of our additional analyses, i.e., among the patients with sepsis and in the comparison of the most common pathogens (\u003cem\u003eS. aureus\u003c/em\u003e vs. \u003cem\u003eE. coli\u003c/em\u003e). Notably, although the initial presentation of the patients with GPC bacteremia was less severe with a lower risk of sepsis diagnosis, the patients with GPC bacteremia demonstrated consistently higher mortality across all analyses after adjustment for confounders.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eComparison with extant research and implications\u003c/h2\u003e \u003cp\u003eSeveral research groups have reported differences in pathogenic mechanisms between GPC and GNR bacteremia [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The meta-analysis by Tang et al. revealed that sepsis caused by GNR bacteria was more severe than that caused by GPC bacteria, with significantly higher concentrations of inflammatory factors in their GNR group [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Abe et al. reported that in Japan, GNR bacteremia was associated with significantly higher blood concentrations of CRP and interleukin (IL)-6 compared to GPC bacteremia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. They also observed that among ICU patients with bacteremia and septic shock, the incidence of GNR bacteremia was significantly higher than that in patients with sepsis or severe sepsis. These findings suggest that GNR bacteremia is associated with more severe inflammatory responses and higher rates of septic shock compared to GPC bacteremia.\u003c/p\u003e \u003cp\u003eHowever, varying results regarding survival rates have been obtained. Tang et al.'s analyses revealed no significant differences in the survival rate, coagulation function, length of stay, APACHE II score, or SOFA score between GNR and GPC groups [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. A possible reason for the discrepancy between the meta-analysis and our present findings is the difference in the causative bacterial strains between Japan and other regions/countries. Several studies have demonstrated that the mortality of patients with sepsis varies depending on the causative bacteria [\u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In the present investigation, \u003cem\u003eS. aureus\u003c/em\u003e was the most common GPC bacterium and \u003cem\u003eE. coli\u003c/em\u003e was the most common GNR bacterium, whereas the meta-analysis indicated that \u003cem\u003eS. aureus\u003c/em\u003e and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e were the most common bacteria for GPC and GNR bacteremia, respectively [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In a study conducted in Japan, about half of the cases were caused by \u003cem\u003eE. coli\u003c/em\u003e and only 9% were caused by \u003cem\u003eP. aeruginosa\u003c/em\u003e. Moreover, there was a two-fold difference in the 7-day mortality rate (\u003cem\u003eE. coli\u003c/em\u003e 4.0% vs. \u003cem\u003ePseudomonas\u003c/em\u003e 10.3%) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In our study, the proportion of cases caused by \u003cem\u003eE. coli\u003c/em\u003e was 66.4%, while \u003cem\u003eP. aeruginosa\u003c/em\u003e accounted for only 3.3%.\u003c/p\u003e \u003cp\u003eThis significant difference in pathogen distribution may explain why our GNR group showed a relatively lower mortality trend compared to the GPC group. This discrepancy between our findings and international data likely reflects regional differences in infection sources. The higher prevalence of \u003cem\u003eP. aeruginosa\u003c/em\u003e in the international studies may be attributed to ventilator-associated pneumonia cases, which are less common in our cohort (in which urinary tract infections were predominant among the GNR cases). It has been suggested that respiratory infections generally carry a worse prognosis than urinary-source infections [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The favorable outcomes in our GNR group likely reflect the high proportion of urinary tract infections, which typically show a good treatment response despite the initial severe presentation. In addition, antimicrobial resistance patterns differ significantly between Japan and other countries. Investigations performed in settings outside Japan have reported higher rates of resistant organisms, particularly among non-fermenting GNR bacteria like \u003cem\u003eP. aeruginosa\u003c/em\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe incidence and mortality of GPC-induced sepsis have been increasing in both Japan and elsewhere, with resistant GPCs such as MRSA on the rise [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Indeed, our additional analysis focusing on \u003cem\u003eS. aureus\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e revealed that the patients infected with \u003cem\u003eS. aureus\u003c/em\u003e had significantly higher odds of 7-day mortality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStudy limitations\u003c/h2\u003e \u003cp\u003eSeveral study limitations should be addressed. We did not account for polymicrobial infections, which could potentially influence clinical outcomes and treatment responses. We also did not measure the SOFA scores or detailed inflammatory markers, which might have provided a more comprehensive assessment of disease severity and host response patterns. Moreover, as with all observational studies, we cannot completely eliminate the influence of unmeasured confounding factors despite our attempts to adjust for key variables.\u003c/p\u003e \u003cp\u003eThe study's retrospective design also introduces potential selection bias, particularly in the identification of sepsis and septic shock cases. Although we used established clinical surveillance criteria, their retrospective application may have missed some nuances in the patients' clinical presentations. In addition, our findings from two Japanese tertiary care centers may not be generalizable to different healthcare settings or geographical regions with varying bacterial epidemiology and resistance patterns. Our analyses did not incorporate antimicrobial prescription patterns such as empirical treatment regimens and targeted treatment regimens, which can significantly affect patient outcomes and treatment efficacy.\u003c/p\u003e \u003cp\u003eFinally, we could not fully account for differences in treatment approaches, including the timing of appropriate antimicrobial therapy and source control measures, which are known to significantly impact the outcomes of patients with bacteremia.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur analyses of 259 critically ill patients requiring ICU or emergency ward admission revealed that after an adjustment for several potential confounding factors, the difference in bacterial species (GPC or GNR) is a crucial factor in the clinical course and prognosis of patients with sepsis. Our results demonstrated that the mortality associated with GPC bacteremia was higher than that of GNR bacteremia. We speculate that differences in the causative bacterial strains of GNR bacteremia between Japan and other countries, as well as the increase in MRSA, may contribute to these observed disparities. These findings highlight the importance of identifying bacterial species and implementing appropriate treatment strategies in the management and treatment of patients with sepsis. Future research should focus on these differences to further clarify the pathophysiology of sepsis and improve treatment outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAPACHE II\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute Physiology and Chronic Health Evaluation II\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eaRD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eadjusted risk difference\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eaRR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eadjusted risk ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eE. coli\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eEscherichia coli\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eED\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eemergency department\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eESBL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eextended-spectrum beta-lactamase\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGNR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egram-negative rods\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGPC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egram-positive cocci\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIL-6\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterleukin 6\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emethicillin-resistant Staphylococcus aureus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMSSA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emethicillin-susceptible Staphylococcus aureus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eqSOFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eQuick Sequential Organ Failure Assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eS. aureus\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eStaphylococcus aureus\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSequential Organ Failure Assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e This study was approved by the institutional review boards of Nagasaki University Hospital (approval no. 22112121) and Hitachi General Hospital (approval no. 201795). The requirement for patients' informed consent was waived due to the retrospective nature of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eThis study protocol was approved by the Ethics Committee of Nagasaki University Hospital and Hitachi General Hospital. Due to the retrospective nature of the study, the requirement for patients' consent for publication was waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe datasets generated and analyzed in this study are not publicly available because data-sharing is not approved by the Ethics Committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e All of the study's authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e No funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eTN and SS take responsibility for the study as a whole. TN, SS, and MS conceived the study. SS, MS, TT, and TG supervised the conduct of the study. SS provided statistical advice. TN analyzed the data. JS, IOs, and TS were instrumental in organizing and preparing the data from Hitachi General Hospital, which was crucial for the analysis. TN drafted the manuscript, and all authors contributed substantially to its revision. The content is solely the responsibility of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: We thank the medical staff at Nagasaki University Hospital and Hitachi General Hospital for their assistance with the data collection. We appreciate the clinical laboratory technicians for providing microbiological data and the ICU and ED nursing staff for their dedication to patient care.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMartin GS, Mannino DM, Eaton S, Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003;348:1546\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eImaeda T, Nakada T-A, Takahashi N, Yamao Y, Nakagawa S, Ogura H, et al. Trends in the incidence and outcome of sepsis using data from a Japanese nationwide medical claims database-the Japan Sepsis Alliance (JaSA) study group. Crit Care. 2021;25:338.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKu NS, Kim YC, Kim MH, Song JE, Oh DH, Ahn JY, et al. Risk factors for 28-day mortality in elderly patients with extended-spectrum β-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae bacteremia. Arch Gerontol Geriatr. 2014;58:105\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSianipar O, Asmara W, Dwiprahasto I, Mulyono B. Mortality risk of bloodstream infection caused by either Escherichia coli or Klebsiella pneumoniae producing extended-spectrum β-lactamase: a prospective cohort study. BMC Res Notes. 2019;12:719.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDigiovine B, Chenoweth C, Watts C, Higgins M. The attributable mortality and costs of primary nosocomial bloodstream infections in the intensive care unit. Am J Respir Crit Care Med. 1999;160:976\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKomori A, Abe T, Kushimoto S, Ogura H, Shiraishi A, Saitoh D, et al. Characteristics and outcomes of bacteremia among ICU-admitted patients with severe sepsis. Sci Rep. 2020;10:2983.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarrouste-Orgeas M, Timsit JF, Tafflet M, Misset B, Zahar J-R, Soufir L, et al. Excess risk of death from intensive care unit-acquired nosocomial bloodstream infections: a reappraisal. Clin Infect Dis. 2006;42:1118\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBearman GML, Wenzel RP. Bacteremias: a leading cause of death. Arch Med Res. 2005;36:646\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRenaud B, Brun-Buisson C, ICU-Bacteremia Study Group. Outcomes of primary and catheter-related bacteremia. A cohort and case-control study in critically ill patients. Am J Respir Crit Care Med. 2001;163:1584\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParrillo JE, Parker MM, Natanson C, Suffredini AF, Danner RL, Cunnion RE, et al. Septic shock in humans. Advances in the understanding of pathogenesis, cardiovascular dysfunction, and therapy. Ann Intern Med. 1990;113:227\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIdentification of key genes in Grampositive and Gramnegative sepsis using stochastic perturbation.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamachandran G. Gram-positive and gram-negative bacterial toxins in sepsis: a brief review. Virulence. 2014;5:213\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Q, Li X, Tang W, Guan X, Xiong Z, Zhu Y, et al. Differential gene sets profiling in Gram-negative and Gram-positive sepsis. Front Cell Infect Microbiol. 2022;12:801232.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbe R, Oda S, Sadahiro T, Nakamura M, Hirayama Y, Tateishi Y, et al. Gram-negative bacteremia induces greater magnitude of inflammatory response than Gram-positive bacteremia. Crit Care. 2010;14:R27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007;147:573\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRhee C, Kadri S, Huang SS, Murphy MV, Li L, Platt R, et al. Objective sepsis surveillance using electronic clinical data. Infect Control Hosp Epidemiol. 2016;37:163\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRhee C, Dantes R, Epstein L, Murphy DJ, Seymour CW, Iwashyna TJ, et al. Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009\u0026ndash;2014. JAMA. 2017;318:1241.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDelahanty RJ, Alvarez J, Flynn LM, Sherwin RL, Jones SS. Development and evaluation of a machine learning model for the early identification of patients at risk for sepsis. Ann Emerg Med. 2019;73:334\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheung YB. A modified least-squares regression approach to the estimation of risk difference. Am J Epidemiol. 2007;166:1337\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng B, Xie G, Yao S, Wu X, Guo Q, Gu M, et al. Epidemiology of severe sepsis in critically ill surgical patients in ten university hospitals in China. Crit Care Med. 2007;35:2538\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAngus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001;29:1303\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVincent J-L, Sakr Y, Sprung CL, Ranieri VM, Reinhart K, Gerlach H, et al. Sepsis in European intensive care units: results of the SOAP study. Crit Care Med. 2006;34:344\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrun-Buisson C, Doyon F, Carlet J. Incidence, risk factors, and outcome of severe sepsis and septic shock in adults: A multicenter prospective study in intensive care units. JAMA. 1995;274:968\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkira S, Uematsu S, Takeuchi O. Pathogen recognition and innate immunity. Cell. 2006;124:783\u0026ndash;801.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElson G, Dunn-Siegrist I, Daubeuf B, Pugin J. Contribution of Toll-like receptors to the innate immune response to Gram-negative and Gram-positive bacteria. Blood. 2007;109:1574\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang A, Shi Y, Dong Q, Wang S, Ge Y, Wang C, et al. Prognostic differences in sepsis caused by gram-negative bacteria and gram-positive bacteria: a systematic review and meta-analysis. Crit Care. 2023;27:467.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiang H-Y, Chen T-C, Lin C-C, Ho L-C, Kuo C-C, Chi C-Y. Trend and Predictors of Short-term Mortality of Adult Bacteremia at Emergency Departments: A 14-Year Cohort Study of 14 625 Patients. Open Forum Infect Dis [Internet]. 2021 [cited 2023 Jul 2];8. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://academic.oup.com/ofid/article-pdf/8/11/ofab\u003c/span\u003e\u003cspan address=\"https://academic.oup.com/ofid/article-pdf/8/11/ofab\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e485/41145859/ofab485.pdf\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLyytik\u0026auml;inen O, Lumio J, Sarkkinen H, Kolho E, Kostiala A, Ruutu P, et al. Nosocomial bloodstream infections in Finnish hospitals during 1999\u0026ndash;2000. Clin Infect Dis. 2002;35:e14-9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeinstein MP, Towns ML, Quartey SM, Mirrett S, Reimer LG, Parmigiani G, et al. The clinical significance of positive blood cultures in the 1990s: a prospective comprehensive evaluation of the microbiology, epidemiology, and outcome of bacteremia and fungemia in adults. Clin Infect Dis. 1997;24:584\u0026ndash;602.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHongmei TW, Evans SJ. Bench-to-Bedside Review: Sepsis, Severe Sepsis and Septic Shock - Does the Nature of the Infecting Organism Matter? Critical Care / the Society of Critical Care Medicine. 2008;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKosai K, Yamagishi Y, Mikamo H, Ishii Y, Tateda K, Yanagihara K. Epidemiological analysis and antimicrobial susceptibility profile of Gram-negative bacilli that cause bacteremia in Japan. J Infect Chemother. 2023;29:1091\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Huang J, Xu J, Qiu R, Lin T. Association between site of infection and mortality in patients with cancer with sepsis or septic shock: A retrospective cohort study. Exp Ther Med. 2023;25:33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElfadadny A, Ragab RF, AlHarbi M, Badshah F, Ib\u0026aacute;\u0026ntilde;ez-Arancibia E, Farag A, et al. Antimicrobial resistance of Pseudomonas aeruginosa: navigating clinical impacts, current resistance trends, and innovations in breaking therapies. Front Microbiol. 2024;15:1374466.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlaskovich MAT, Hansford KA, Butler MS, Ramu S, Kavanagh AM, Jarrad AM, et al. A lipoglycopeptide antibiotic for Gram-positive biofilm-related infections. Sci Transl Med. 2022;14:eabj2381.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo Q, Qu P, Cui W, Liu M, Zhu H, Chen W, et al. Organism type of infection is associated with prognosis in sepsis: an analysis from the MIMIC-IV database. BMC Infect Dis. 2023;23:431.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eA lipoglycopeptide antibiotic for gram-positive biofilm-related infections. Sci Transl Med. 2022;14.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"bacteremia, gram-positive cocci, gram-negative rod, sepsis, mortality, emergency department","lastPublishedDoi":"10.21203/rs.3.rs-6632548/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6632548/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDespite advances in intensive care medicine, the mortality rate of patients with sepsis remains high. The differences in pathogenic mechanisms between gram-positive cocci (GPC) and gram-negative rod (GNR) bacteremia are well-documented, but the relationship between bacterial types and clinical outcomes remains unclear, particularly regarding the discrepancy between severity at emergency department (ED) / intensive care unit (ICU) presentation and subsequent mortality.\u003cbr\u003e\n \u003cstrong\u003ePatients and Methods: \u003c/strong\u003eOf the adult patients who presented to two Japanese tertiary hospitals' EDs with suspected infections in 2018–2022, we included those with positive blood cultures who were admitted to the ICU or emergency ward. The primary outcomes were 7-day and 28-day mortality. The secondary outcomes were diagnoses of sepsis and septic shock. We calculated adjusted risk differences (aRDs) and adjusted risk ratios (aRRs) between the GPC and GNR groups using modified Poisson and least-squares regression analyses, adjusting for age, sex, malignancy, immunosuppressive therapy, hemodialysis, and intravascular device use.\u003cstrong\u003e\u003cbr\u003e\nResults:\u003c/strong\u003e Of the 259 patients, 107 (41.3%) had GPC bacteremia and 152 (58.7%) had GNR bacteremia. \u003cem\u003eStaphylococcus aureus \u003c/em\u003eand \u003cem\u003eEscherichia coli \u003c/em\u003ewere the most common pathogens in each group. GPC bacteremia was associated with higher mortality at both 7 days (aRD 8.9%, 95%CI: 1.3−16.4; aRR 3.48, 95%CI: 1.29−9.36) and 28 days (aRD 10.6%, 95%CI: 1.8–19.5; aRR 2.65, 95%CI: 1.21−5.83) versus GNR bacteremia. However, the GPC bacteremia patients showed less severe presentations at ED arrival, with a lower sepsis diagnosis rate (aRD −12.8%, 95%CI: −24.7 to −0.8; aRR 0.81, 95%CI: 0.66–0.99), lower qSOFA scores, and lower lactate levels (1.9 vs. 2.5 mmol/L). This pattern of higher mortality despite less-severe initial presentations was consistently observed in analyses of sepsis patients and in a comparison of \u003cem\u003eS. aureus\u003c/em\u003ewith \u003cem\u003eE. coli\u003c/em\u003e bacteremia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eGPC bacteremia, despite its less severe clinical presentation at ED arrival compared to GNR bacteremia, was associated with higher mortality. Clinicians should not be misled by the apparently milder initial organ dysfunction in GPC bacteremia, as these patients require careful monitoring and appropriate treatment regardless of presentation severity. These findings highlight the importance of identifying the bacterial species in the risk stratification and management of bacteremia patients in critical-care settings.\u003c/p\u003e","manuscriptTitle":"The Associations of Gram-Positive Cocci and Gram-Negative Rods with Disease Severity and Mortality in Critically Ill Patients: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 12:33:07","doi":"10.21203/rs.3.rs-6632548/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a095c978-d1c8-4230-8784-c2031a8e4423","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-17T07:53:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-20 12:33:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6632548","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6632548","identity":"rs-6632548","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}