Does SOFA-2 Improve Mortality Prediction in Sepsis? A Retrospective Single-Center Observational Cohort Study Comparing SOFA-1 and SOFA-2

Does SOFA-2 Improve Mortality Prediction in Sepsis? 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A Retrospective Single-Center Observational Cohort Study Comparing SOFA-1 and SOFA-2 Kamil Deveci, Maruf Boran, Kübra Elif Bahar, Fatma Sarıdağ, Esma Eryılmaz Eren This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9003079/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background: The Sequential Organ Failure Assessment (SOFA) score has been widely used for nearly three decades to evaluate organ dysfunction and predict mortality in patients with sepsis. Advances in critical care practice have led to the development of an updated version, SOFA-2, incorporating contemporary organ support strategies and revised clinical thresholds. However, real-world comparative data evaluating the prognostic performance of the original SOFA score (SOFA-1) and SOFA-2 remain limited. This study aimed to compare the ability of SOFA-1 and SOFA-2 to predict intensive care unit (ICU), 28-day, and 90-day mortality in patients with sepsis. Methods: This retrospective, single-center observational cohort study included adult patients (≥18 years) diagnosed with sepsis according to Sepsis-3 criteria and admitted between December 2023 and August 2024. SOFA-1 and SOFA-2 scores were calculated using clinical and laboratory data obtained at ICU admission. The primary outcome was ICU mortality; secondary outcomes were 28-day and 90-day mortality. Multivariable logistic regression was performed to identify independent predictors of mortality. Discriminatory performance was assessed using receiver operating characteristic analysis, and areas under the curve were compared using DeLong’s test. Optimal cut-off values were determined using the Youden index. Results: Among 417 screened patients, 222 met the inclusion criteria. ICU mortality was 57.7%. Each one-point increase in SOFA-1 and SOFA-2 scores was associated with a 42% and 43% increase in ICU mortality, respectively (p<0.001 for both). The area under the curve for ICU mortality prediction was 0.843 (95% confidence interval 0.792–0.895) for SOFA-1 and 0.845 (95% confidence interval 0.795–0.896) for SOFA-2, with no statistically significant difference between the two scores (p=0.79). SOFA-2 demonstrated slightly higher specificity, whereas SOFA-1 showed marginally higher sensitivity at the optimal cut-off value. Conclusions: Both SOFA-1 and SOFA-2 demonstrated good discriminatory performance for predicting ICU mortality in patients with sepsis. Although SOFA-2 provided a more balanced sensitivity–specificity profile, its overall predictive performance was comparable to that of SOFA-1. Further prospective multicenter studies are warranted to clarify the incremental clinical value of the updated score. Trial registration : Not applicable. Mortality SOFA-2 Organ Failure Severity of Illness Index Figures Figure 1 Figure 2 Background Every year, significant transformations are taking place in intensive care medicine. Advances in pharmacological therapies, organ support technologies, and evidence-based protocols have substantially improved the delivery and quality of intensive care. Thirty years have passed since the Sequential Organ Failure Assessment (SOFA) score was first used in 1996 ( 1 ), and clinical practice has advanced significantly. Treatments we previously used, such as low-dose dopamine ( 2 ), have been replaced in clinical practice with specific vasopressors such as norepinephrine and vasopressin ( 3 , 4 ). These changes are not only related to cardiovascular support systems; the use of non-invasive respiratory support systems has also increased in our clinical practice ( 5 ). Despite these developments, the original SOFA score (hereafter referred to as SOFA-1) has remained unchanged. SOFA-1 assesses six organ systems (neurological, respiratory, renal, hepatic, cardiovascular, and coagulation) and generates a score between 0 and 24 to predict disease severity and mortality risk ( 1 ). This scoring system cannot account for current, less invasive pharmacological and device-based organ support strategies. Given the substantial evolution in critical care management, an updated organ dysfunction scoring system applicable across both high-income and low-to-middle-income settings is warranted ( 6 – 8 ). In 2025, SOFA-2 was introduced as a revised model incorporating contemporary organ support therapies, modified cut-off values, and refined clinical criteria ( 9 ). Nevertheless, real-world comparative data evaluating the prognostic performance of SOFA-1 and SOFA-2 in patients with sepsis remain limited. In this study, we aimed to compare the prognostic accuracy of SOFA-1 and SOFA-2 in predicting ICU, 28 and 90-day mortality in patients with sepsis using our institutional cohort. Methods Study Design and Setting: This retrospective, single-center observational study was conducted in the Intensive Care Unit-3 (ICU) with the approval of the Ethics Committee of Kayseri City Education and Research Hospital (Decision No: 711, Date: January 7, 2026). Given the retrospective and anonymized nature of the analysis, written patient consent was waived. All procedures adhered to the Declaration of Helsinki, institutional standards, and applicable guidelines. To enhance transparency, this study was reported following the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines ( 10 ). Our primary objective is to determine whether there is a difference in the prediction of in-ICU mortality between SOFA-1 and SOFA-2 scores. Our secondary objective is to investigate whether there is a difference in the prediction of 28 and 90 days mortality. Patient selection The study included all consecutive patients aged 18 years and older diagnosed with sepsis who met the Sepsis-3 criteria ( 11 ) and were admitted between December 2023 and August 2024. A total of 417 patients were evaluated, and 222 patients who had all the data necessary to calculate SOFA-1 and SOFA-2 scores and who met the documentation criteria for ICU, 28 and 90 day mortality records were included in the study. Exclusion Criteria: Missing key clinical or laboratory parameters preventing SOFA score calculation. Hospital stay of less than 24 hours. Repeat hospitalizations (only the first admission included). Patients lower 18 years of age. Patients without a suspected or confirmed focus of infection. Patients with infection but a sofa score < 2. The flowchart is presented in Fig. 1 Data collection Retrospective review of the hospital electronic health record system (KEYDATA) was performed to extract patient information, encompassing demographic, clinical, treatment and laboratory parameters. For all patients, the following data were recorded: Demographic variables: age, sex, ICU admission area (Ward, Emergency Department, other ICU) and comorbidities. Clinical and treatment variables: GCS score, APACHE-II score, Initial vital signs, vasopressor use, oxygen/ventilation methods (mechanical ventilation, non-invasive ventilation, any advanced ventilator support), need for renal replacement (intermittent or continuous), urine output, source of infection, and antibiotic use were recorded. Laboratory parameters: complete blood cell (CBC) analysis, PaO₂/FiO₂ ratio, biochemical markers (blood urea nitrogen, creatinine, AST, ALT, total bilirubin), inflammatory markers (C-reactive protein (CRP), procalcitonin (PCT)), and lactate level. SOFA-1 and SOFA-2 scores were calculated retrospectively for all patients using clinical, treatment, and laboratory variables at the time of admission to the ICU. Disclosure of AI usage During the preparation of this manuscript, the authors used AI tools ChatGPT by OpenAI (version ChatGPT-5 Thinking/Pro) to improve language and readability. All outputs were reviewed, adapted and integrated into the final work by the authors, who take full responsibility for all content presented herein. Definitions Vasopressor Requirement: 0.05 mcg/kg/min and equivalent norepinephrine requirement was stated. Non-infectious patients: Clinical, laboratory, or radiological findings do not indicate infection, and the current clinical symptoms can be attributed to a non-infectious condition (e.g., acute kidney injury, gastrointestinal bleeding, electrolyte imbalance, vertigo, cerebrovascular disease, hypercalcemia, congestive heart failure, acute coronary syndrome, acute pancreatitis, malignancy-related processes, status epilepticus, pulmonary embolism, etc.), they were defined as non-infectious. Infection patients without sepsis: defined as the absence of signs of organ dysfunction (SOFA < 2) in addition to a clinically consistent focus of infection (pneumonia, urinary tract infection, intra-abdominal infection, skin/soft tissue infection, catheter infection, cholecystitis, central nervous system infection, etc.) supported by physical examination, laboratory findings (including microbiological), and/or imaging studies. Sepsis is diagnosed according to Sepsis-3 criteria. Patients showing signs of infection-related organ dysfunction (SOFA ≥ 2) were classified in this group. SOFA-1: The original scoring system described by Singer et al. ( 10 ), evaluating six organ systems using traditional thresholds and clinical measures. SOFA-2: A revised scoring model incorporating updated cut-off values, expanded definitions of respiratory and renal support, and contemporary clinical practices ( 9 ). Mortality Rate: All-cause mortality rates during intensive care unit admission or within 28 and 90 days. All diagnoses were determined retrospectively based on electronic medical records. Ethical approval was obtained from the local ethics committee prior to the study. Statistical Analysis Statistical analyses were conducted using IBM SPSS Statistics version 27.0. Data distribution was evaluated visually and with the Shapiro-Wilk test. Continuous variables were summarized as mean±standard deviation or median (IQR, 25–75%), as appropriate. Continuous variables were compared using the Student’s t-test or Mann–Whitney U test, as appropriate. Categorical variables were analyzed using Pearson’s chi-square or exact chi-square tests. Multivariable logistic regression was applied to determine independent predictors of mortality. Variables were selected a priori according to clinical relevance and univariate associations. All selected variables were simultaneously entered into the multivariable logistic regression model using the ENTER method. Results are presented as odds ratios (ORs) with 95% confidence intervals (CIs). To reduce collinearity and enhance interpretability, composite severity scores (APACHE II, SOFA-1, and SOFA-2) and their individual components were evaluated in separate models. SOFA-1 and SOFA-2 were evaluated for their ability to predict ICU, 28 and 90 days mortality using ROC curve analysis, with AUCs and 95% CIs reported. Correlated AUCs were compared with DeLong’s test (MedCalc). Cutoff points were determined by the Youden index, and diagnostic performance metrics (sensitivity, specificity, PPV, NPV) were calculated from 2×2 tables. Statistical significance was defined as a two-tailed p < 0.05. Results Study population and patient characteristics A total of 417 patients were screened for our study, and 222 patients meeting the inclusion criteria were enrolled (Fig. 1). Women were 38% (n = 85) of our patients and the age of all patients was 70 (62–80), with median SOFA-1 score 9 (5–13), SOFA-2 score 8 (5–12), mean APACHE-II score of 25.8 ± 9.9. Our ICU mortality rate was 57.7% (n = 128), indicating a cohort with a high severity of illness. The most common comorbid condition was hypertension (Table 1). Association of Organ Dysfunction Scores with ICU Mortality in Critically Ill Patients During the ICU course, patients were classified into survivor (SG) and non-survivor groups (NSG); however, no significant differences were identified between the groups regarding; age, gender, creatinine, pH, PCT, CRP and lymphocyte levels both group. APACHE-II, GCS, SOFA-1, and SOFA-2 scores were statistically significantly higher in the non-survivor group (all p < 0.001). All variables comprising SOFA, except creatinine, were statistically significantly higher in the NSG group (Table 2). Univariate and Multivariate Logistic Regression Analysis for Predictors of ICU Mortality In the multivariate analysis, which included variables that showed meaningful differences between SG and NSG in the univariate analysis, vasopressor requirement (OR 10.8, 95% CI 5.04–23.2; p < 0.001) and GCS score (OR 0.82, 95% CI 0.73–0.92; p = 0.001) were identified as independent predictors of mortality. Patients requiring vasopressor support had a markedly increased risk of mortality. We found that a one-point decrease in GCS increased ICU mortality by 19%. Overall, the model demonstrated good explanatory performance, accounting for approximately 56% of the variance in mortality (Table 3). Each One-Point Increase in SOFA-1 and SOFA-2 Confers a Similar Rise in ICU Mortality We found that each point rise in the SOFA-1 score was associated with a 42% increase in ICU mortality, while an increase in the SOFA-2 score was associated with a 43% increase (OR 1.428, 95% CI 1.3–1.56; p < 0.001 vs OR 1.43, 95% CI 1.3–1.575; p < 0.001). SOFA-1 and SOFA-2 Demonstrate Similar AUCs for ICU Mortality Prediction In a total of 222 patients, ICU mortality occurred in 128 patients (57.7%). The AUC of SOFA-1 for predicting ICU mortality was 0.843 (95% CI: 0.792–0.895), while the AUC of SOFA-2 was 0.845 (95% CI: 0.795–0.896). The difference between the two AUCs was not statistically meaningful (p = 0.790). The AUC values of the two scoring systems were similar. According to the Youden index, an optimal cut-off value of 6 was identified for both scores. At this threshold, diagnostic performance metrics including sensitivity, specificity, PPV, and NPV were calculated. SOFA-2 exhibited higher specificity and PPV, while SOFA-1 showed higher sensitivity and NPV. This more balanced diagnostic performance indicates that SOFA-2 may provide superior risk stratification, particularly in clinical settings where avoiding overestimation of mortality risk is crucial (Table 4 and Fig. 2). Discussion In our study, the intensive care mortality rate was 128 (57%), indicating that a very severe patient group was followed. The median SOFA-1 score for these patients was 9, the SOFA-2 score was 8 and the median APACHE-II score was 25.8 ± 9.9. Multivariate analysis identified vasopressor requirement (OR 10.8) and decreased GCS (0.81) as the strongest predictors of mortality. Each point increase in SOFA-1 was associated with a 42% increase in mortality, while each point increase in SOFA-2 was associated with a 43% increase. Both scores predicted in-ICU mortality with high accuracy (SOFA-1 AUC = 0.843 vs SOFA-2 AUC = 0.845). However, further analyses did not demonstrate a statistically significant superiority of either score in predicting mortality (p = 0.79). SOFA-2 had slightly higher specificity, while SOFA-1 had slightly better sensitivity. In a multicenter study involving 3.34 million patients, the predicted intensive care unit (ICU) mortality rate ranged from 12.4% to 31%, while the actual mortality rate was reported as 8.1%, with this rate varying between 4.5% and 20% across centers. In the same study, the AUC values for SOFA-1 and SOFA-2 scores in predicting mortality were reported as 0.81 and 0.80, respectively. A 2 stage validation analysis also showed that SOFA-1 and SOFA-2 scores performed similarly in predicting mortality, with no significant difference between them ( 9 ). In our study, the APACHE-II score was determined to be 25.8 ± 9.9, and the predicted ICU mortality rate based on this score was 45–60%, while the actual mortality rate was found to be 57%. When evaluating the ICU mortality prediction performance of SOFA-1 and SOFA-2 scores, AUC values were determined to be 0.843 and 0.845, respectively, and no statistically significant difference was observed between the two scores (p = 0.79). As expected, the higher observed mortality rates likely reflect the inclusion of a more severely ill patient population. Although there was no significant difference between the AUC values, it is thought that the high mortality rate may have contributed to higher AUC values for both scores. Also in the same study ( 9 ), a 1-point increase in the SOFA-2 score was associated with a 37% increase in mortality. In our study, this rate was found to be 43% and SOFA-1 similarly performance (42%). This difference may again be due to the high severity of disease in our patient profile. In our study, SOFA-1 and SOFA-2 scores demonstrated good discriminatory performance for predicting ICU mortality, with AUC values of 0.843 and 0.845, respectively, using a cut-off value of ≥ 6 determined by the Youden index. For SOFA-1, this threshold yielded a high sensitivity (89%) with moderate specificity (59%), whereas SOFA-2 showed a slightly lower sensitivity (86%) but higher specificity (62.8%), while PPV and NPV values were comparable between the two scores. These findings suggest that SOFA-2 provides a more balanced sensitivity–specificity profile, which may be advantageous for clinical risk stratification in the ICU setting. Previous studies have reported lower discriminatory performance for SOFA-1 when higher cut-off values were applied. For example, a study using a SOFA-1 cut-off value greater than 9 reported an AUC of 0.726 for predicting in-hospital mortality, with a sensitivity of 65% and specificity of 75% ( 12 ). Despite using a lower cut-off value, our study demonstrated a substantially higher AUC, indicating superior overall discrimination. This apparent discrepancy can be explained by differences in study populations, outcome definitions (ICU mortality versus in-hospital mortality), and the methodology used to determine optimal cut-off values. This study has several limitations. Its single-center, retrospective design may limit the generalizability of the findings. SOFA-1 and SOFA-2 scores were calculated using the worst values within the first 24 hours of ICU admission; therefore, dynamic changes in organ dysfunction over time were not evaluated. The study population consisted of a severely ill sepsis cohort with a high ICU mortality rate, which may have influenced the discriminatory performance of both scores and limited the ability to detect small differences between them. Finally, although DeLong’s test was used for AUC comparison, the sample size may not have been sufficient to identify modest differences in predictive performance. Conclusion In this study, both SOFA-1 and SOFA-2 scores demonstrated good discriminatory performance for predicting ICU mortality. SOFA-2 showed a slightly more balanced sensitivity–specificity profile, the overall predictive performance of the two scores was comparable, as reflected by similar AUC values. Importantly, DeLong analysis did not demonstrate a statistically significant difference between SOFA-1 and SOFA-2, indicating that the updated score does not confer a clear advantage in discriminatory performance. These findings suggest that both scoring systems remain clinically useful for ICU mortality risk stratification, while the potential advantages of SOFA-2 may relate more to calibration and contemporary clinical applicability rather than improved discriminatory ability. However, prospective studies are needed on this subject. Abbreviations AI: Artificial intelligence APACHE: Acute physiology and chronic health evaluation AUC: Area under the curve CBC: Complete blood cell CRP: C-reactive protein CI: Confidence interval GCS: Glaskow coma scale ICU: Intensive care ünit MD: Medical doctor NPV: Negative predictive value OR: Odds ratio ROC: Receiver operating characteristic SOFA: Sequential organ failure assessment. STROBE: Strengthening the reporting of observational studies in epidemiology PCT: Procalcitonin PPV: Positive predictive value Declarations Ethical Approval and Consent to Participate This retrospective study was conducted in accordance with the Declaration of Helsinki and was approved by the Clinical Research Ethics Committee of Kayseri City Training and Research Hospital (Decision No: 711, Date: January 7, 2026). Due to the retrospective design of the study and the use of anonymized patient data, the requirement for informed consent was waived by the ethics committee. Consent for Publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The authors received no external funding for this study. Author Contributions The contributions of the authors to this manuscript are defined according to the Contributor Roles Taxonomy as follows: Conceptualization: Kamil Deveci. Methodology: Kamil Deveci, Maruf Boran, Esma Eryılmaz Eren. Formal analysis: Kamil Deveci. Investigation: All authors. Data curation: Kamil Deveci, Maruf Boran, Kübra Elif Bahar, Fatma Sarıdağ. Writing–original draft: All authors. Writing–review&editing: All authors. Supervision: All authors. Acknowledgements First and foremost, we would like to express our gratitude to our valued families and to the staff of the Intensive Care Unit-3 at Kayseri City Education and Research Hospital, especially the nurses. References Vincent JL, Moreno R, Takala J, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure: on behalf of the working group on sepsis-related problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707-710. doi:10. 1007/BF01709751 Carcoana OV, Hines RL. Is renal dose dopamine protective or therapeutic? Yes. Crit Care Clin. 1996;12(3):677-685. doi:10.1016/s0749-0704(05)70271-2 Rhodes A, Evans LE, Alhazzani W, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016. Crit Care Med. 2017;45(3):486-552. doi:10.1097/CCM.0000000000002255 Evans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021;47(11):1181-1247. doi:10.1007/s00134-021-06506-y Twagirumugabe T, Gashame DF, Uwamahoro DL, Riviello E. Advanced non-invasive respiratory support in resource-constrained settings: a narrative review. Crit Care. 2025;29(1):492. Published 2025 Nov 14. doi:10.1186/s13054-025-05688-x Moreno R, Rhodes A, Piquilloud L, et al. The Sequential Organ Failure Assessment (SOFA) score: has the time come for an update? Crit Care. 2023; 27(1):15. doi:10.1186/s13054-022-04290-9 Moreno R, Singer M, Rhodes A.Why the Sequential Organ Failure Assessment score needs updating? Crit Care Sci. 2024;36. doi:10.62675/ 2965-2774.20240296-en 7 Salluh JIF, Quintairos A, Dongelmans DA, et al; Linking of Global Intensive Care (LOGIC) and Japanese Intensive Care Patient Database (JIPAD) working group. National ICU registries as enablers of clinical research and quality improvement. Crit Care Med. 2024;52(1):125-135. doi:10.1097/CCM. 0000000000006050 10 Ranzani OT, Singer M, Salluh JIF, et al. Development and Validation of the Sequential Organ Failure Assessment (SOFA)-2 Score. JAMA. Published online October 29, 2025. doi:10.1001/jama.2025.20516 von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007 Oct 20;335(7624):806-8. doi: 10.1136/bmj.39335.541782.AD. PMID: 17947786; PMCID: PMC2034723 Singer M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801-810. doi:10.1001/jama.2016.0287 Kilinc Toker A, Kose S, Turken M. Comparison of SOFA Score, SIRS, qSOFA, and qSOFA + L Criteria in the Diagnosis and Prognosis of Sepsis. Eurasian J Med. 2021;53(1):40-47. doi:10.5152/eurasianjmed.2021.20081 Tables Tablo 1. Baseline Characteristics of The Study Population Variable Value Age years 70 (62-80) Female Sex, n (%) 85 (38) ICU admission n (%) Emergency Department 125 (56.3) Ward 79 (35.6) Other ICU 18 (8.1) Comorbities, n (%) Hypertension 97 (18.5) Solid malignancy 74 (14.1) Diabetes mellitus 72 (13.8) Chronic kidney disease 47 (9) Coronary artery disease 42 (8) COPD 30 (5.7) GCS Score 12 (5-14) APACHE-II Score 25.8±9.9 SOFA-1 Score 9 (5-13) SOFA-2 Score 8 (5-12) ICU mortality n (%) 128 (57.7) 28 days mortality n (%) 120 (54) 90 days mortality n (%) 143 (64) Abbreviations: APACHE, Acute Physiology and Chronic Health Evaluation; GCS, Glaskow Coma Scale; ICU, Intensive Care Unit; SOFA, Sequential Organ Failure Assessment. Tablo 2. Comparison of Survivors and Non-Survivors in the ICU Variable Survivors (n=94) Non-survivors (n=128) p Age years 71.5 (60-82) 70 (63-79.7) 0,994 Female Sex, n (%) 37 (39.4) 48 (37.5) 0.782 Apache-II Score 21±7.8 29±10.1 <0.001 SOFA-1 Score 5 (3-8) 12 (8.2-14.7) <0.001 SOFA-2 Score 5 (3-7) 11 (7.2-14) <0.001 GCS Score 14 (11-14.2) 8 (3-13) <0.001 PaO 2/ FiO 2 ratio 276±102 213±95 <0.001 Vasopressor requirement n,(%) 20 (21.3) 108 (84.4) <0.001 Laboratory variables WBC count* 12.5 (8.6-17.7) 13.1 (7.1-21.5) 0.30 Lymphocyte count * 0.9 (0.55-1.44) 0.81 (0.52-1.47) 0.930 Platelet count * 195 (144-270) 164 (71-264) 0.023 Total bilirubin mg/dL 0.6 (0.4-1.2) 0.8 (0.5-1.97) 0.005 Creatinin mg/dL 1.28 (0.73-3.2) 1.4 (1.2-3.2) 0.144 INR 1.25 (1.1-1.4) 1.4 (1.2-1.87) <0.001 pH 7.38 (7.30-7.41) 7.31 (7.24-7.43) 0.104 Lactate mmol/L 1.5 (1.1-2.5) 2.5 (1.4-4.1) <0.001 PCT ng/mL 1.3 (0.3-6.4) 1.5 (0.37-6.4) 0.802 CRP mg/L 142 (79-200) 115 (43-208) 0.224 Abbreviations: APACHE-II, Acute Physiology and Chronic Health Evaluation II; GCS, Glaskow Coma Scale; SOFA, Sequential Organ Failure Assessment; WBC,White Blood Cells; *×10 3 /mm 3 Table 3. Univariate and Multivariate Logistic Regression Analysis for Predictors of ICU Mortality Univariate OR(%95 CI) p value Multivariate OR(% 95 CI) p value GCS Score 0.817 (0.726–0.919) <0.001 0.817 (0.726–0.919) 0.001 PaO 2 /FiO 2 ratio 0.997 (0.993–1.001) <0.001 --- 0.177 Vasopressor requirement 10.8 (5.04–23.2) <0.001 10.8 (5.04–23.2) <0.001 Platelet count 1.00(1.00-1.00) 0.205 --- 0.142 Total Bilirubin mg/dL 1.01 (0.832–1.226) 0.096 --- 0.921 INR 1.56 (0.77–3.1) 0.294 --- 0.216 Lactate mmol/L 1.08 (0.892–1.314) 0.001 --- 0.423 Abbreviations: CI, Confidence Interval; GCS,Glaskow Coma Scale; OR, Odds ratio. Model fit: −2 Log likelihood=173; Cox & Snell R² = 0.42; Nagelkerke R² = 0.567 Table 4. Analysis of the Performance of SOFA-1 and SOFA-2 in Predicting in-ICU, 28 and 90 days Mortality in Sepsis Patients Outcome Score Cut-off Sensitivity (%) Specificity (%) PPV NPV AUC p ICU mortality SOFA-1 ≥6 89 51 71.2 77.4 0.843 <0.001 SOFA-2 ≥6 86 62.8 71 77.6 0.845 <0.001 28-day mortality SOFA-1 ≥6 88.3 47.1 66.3 77.4 0.806 <0.001 SOFA-2 ≥6 85.0 56.9 69.9 76 0.810 <0.001 90-day mortality SOFA-1 ≥6 86.0 53.2 76.9 67.7 0.819 <0.001 SOFA-2 ≥6 81.8 63.3 80 65.8 0.819 <0.001 Abbreviations: AUC, Area under curve; ICU, Intensive care unit; NPV, Negative predictive value; PPV,Positive predictive value. There was no statistically significant difference between SOFA-1 and SOFA-2 AUCs (DeLong test) Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9003079","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":609376558,"identity":"b3e779b4-af76-4542-8f4a-d1a7fee43d08","order_by":0,"name":"Kamil Deveci","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACCSA+8IANxGRsfAAkefiI0pIA0dJsANLCRowWBogWBjYwh6AWyfbTiQcSymwS+9kPt1V+zbGTYWNgfvjoBh4t0jy5Gw4knEtLnNmT2HZbdlsy0GFsxsY5eLTIMQC1JLYdNja4wdh2W3IbM1ALD5s0Xi38b0Fa/hvbA7UUS26rJ6xFWgJsywE5AwnGNsaP2w4T1iI54y3IL8lyEmcSm6UZtx3nYWMm4BeJ87mbP3wos+Phbz/+8OPPbdX2/OzNDx/j04ICmHnAJLHKQYDxBymqR8EoGAWjYMQAAJE9SNv4NAvjAAAAAElFTkSuQmCC","orcid":"","institution":"Kayseri Eğitim ve Araştırma Hastanesi","correspondingAuthor":true,"prefix":"","firstName":"Kamil","middleName":"","lastName":"Deveci","suffix":""},{"id":609376559,"identity":"f6155073-d202-4d13-b867-4623730a18de","order_by":1,"name":"Maruf Boran","email":"","orcid":"","institution":"Kayseri Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Maruf","middleName":"","lastName":"Boran","suffix":""},{"id":609376560,"identity":"6c330603-0e66-4c19-922d-3eb022ca65ee","order_by":2,"name":"Kübra Elif Bahar","email":"","orcid":"","institution":"Kayseri Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Kübra","middleName":"Elif","lastName":"Bahar","suffix":""},{"id":609376561,"identity":"74979e52-11a7-4b92-9954-3784b6a371d0","order_by":3,"name":"Fatma Sarıdağ","email":"","orcid":"","institution":"Kayseri Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Fatma","middleName":"","lastName":"Sarıdağ","suffix":""},{"id":609376563,"identity":"859c67a3-f38c-472e-bfc6-26ce0aaf01f3","order_by":4,"name":"Esma Eryılmaz Eren","email":"","orcid":"","institution":"Kayseri Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Esma","middleName":"Eryılmaz","lastName":"Eren","suffix":""}],"badges":[],"createdAt":"2026-03-01 17:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9003079/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9003079/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105314742,"identity":"2209d7c9-bae3-4a37-9490-0e67caaf8cb8","added_by":"auto","created_at":"2026-03-24 16:00:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":104881,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of patient selection and ICU outcomes\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9003079/v1/fce9a9afe4f2769f24ff59e4.png"},{"id":105314741,"identity":"3b2e5514-145f-4eeb-ab1f-18962bd1b799","added_by":"auto","created_at":"2026-03-24 16:00:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":68482,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curves of SOFA-1 and SOFA-2 for ICU(A), 28(B) and 90(C) day Mortality\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9003079/v1/297f09cf5d00082379995f12.png"},{"id":105564921,"identity":"7ff0343b-9e25-488e-aacd-e9385cc29d1d","added_by":"auto","created_at":"2026-03-27 12:51:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1186223,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9003079/v1/6d5b0edb-b11e-4aeb-bd2b-fbf13840738b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Does SOFA-2 Improve Mortality Prediction in Sepsis? A Retrospective Single-Center Observational Cohort Study Comparing SOFA-1 and SOFA-2","fulltext":[{"header":"Background","content":"\u003cp\u003eEvery year, significant transformations are taking place in intensive care medicine. Advances in pharmacological therapies, organ support technologies, and evidence-based protocols have substantially improved the delivery and quality of intensive care. Thirty years have passed since the Sequential Organ Failure Assessment (SOFA) score was first used in 1996 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), and clinical practice has advanced significantly. Treatments we previously used, such as low-dose dopamine (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e), have been replaced in clinical practice with specific vasopressors such as norepinephrine and vasopressin (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). These changes are not only related to cardiovascular support systems; the use of non-invasive respiratory support systems has also increased in our clinical practice (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite these developments, the original SOFA score (hereafter referred to as SOFA-1) has remained unchanged. SOFA-1 assesses six organ systems (neurological, respiratory, renal, hepatic, cardiovascular, and coagulation) and generates a score between 0 and 24 to predict disease severity and mortality risk (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). This scoring system cannot account for current, less invasive pharmacological and device-based organ support strategies.\u003c/p\u003e \u003cp\u003eGiven the substantial evolution in critical care management, an updated organ dysfunction scoring system applicable across both high-income and low-to-middle-income settings is warranted (\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In 2025, SOFA-2 was introduced as a revised model incorporating contemporary organ support therapies, modified cut-off values, and refined clinical criteria (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Nevertheless, real-world comparative data evaluating the prognostic performance of SOFA-1 and SOFA-2 in patients with sepsis remain limited.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to compare the prognostic accuracy of SOFA-1 and SOFA-2 in predicting ICU, 28 and 90-day mortality in patients with sepsis using our institutional cohort.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting:\u003c/h2\u003e \u003cp\u003e This retrospective, single-center observational study was conducted in the Intensive Care Unit-3 (ICU) with the approval of the Ethics Committee of Kayseri City Education and Research Hospital (Decision No: 711, Date: January 7, 2026). Given the retrospective and anonymized nature of the analysis, written patient consent was waived. All procedures adhered to the Declaration of Helsinki, institutional standards, and applicable guidelines. To enhance transparency, this study was reported following the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Our primary objective is to determine whether there is a difference in the prediction of in-ICU mortality between SOFA-1 and SOFA-2 scores. Our secondary objective is to investigate whether there is a difference in the prediction of 28 and 90 days mortality.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatient selection\u003c/h3\u003e\n\u003cp\u003eThe study included all consecutive patients aged 18 years and older diagnosed with sepsis who met the Sepsis-3 criteria (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) and were admitted between December 2023 and August 2024. A total of 417 patients were evaluated, and 222 patients who had all the data necessary to calculate SOFA-1 and SOFA-2 scores and who met the documentation criteria for ICU, 28 and 90 day mortality records were included in the study. Exclusion Criteria: Missing key clinical or laboratory parameters preventing SOFA score calculation. Hospital stay of less than 24 hours. Repeat hospitalizations (only the first admission included). Patients lower 18 years of age. Patients without a suspected or confirmed focus of infection. Patients with infection but a sofa score\u0026thinsp;\u0026lt;\u0026thinsp;2. The flowchart is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003e Retrospective review of the hospital electronic health record system (KEYDATA) was performed to extract patient information, encompassing demographic, clinical, treatment and laboratory parameters. For all patients, the following data were recorded: Demographic variables: age, sex, ICU admission area (Ward, Emergency Department, other ICU) and comorbidities. Clinical and treatment variables: GCS score, APACHE-II score, Initial vital signs, vasopressor use, oxygen/ventilation methods (mechanical ventilation, non-invasive ventilation, any advanced ventilator support), need for renal replacement (intermittent or continuous), urine output, source of infection, and antibiotic use were recorded. Laboratory parameters: complete blood cell (CBC) analysis, PaO₂/FiO₂ ratio, biochemical markers (blood urea nitrogen, creatinine, AST, ALT, total bilirubin), inflammatory markers (C-reactive protein (CRP), procalcitonin (PCT)), and lactate level. SOFA-1 and SOFA-2 scores were calculated retrospectively for all patients using clinical, treatment, and laboratory variables at the time of admission to the ICU.\u003c/p\u003e\n\u003ch3\u003eDisclosure of AI usage\u003c/h3\u003e\n\u003cp\u003eDuring the preparation of this manuscript, the authors used AI tools ChatGPT by OpenAI (version ChatGPT-5 Thinking/Pro) to improve language and readability. All outputs were reviewed, adapted and integrated into the final work by the authors, who take full responsibility for all content presented herein.\u003c/p\u003e\n\u003ch3\u003eDefinitions\u003c/h3\u003e\n\u003cp\u003eVasopressor Requirement: 0.05 mcg/kg/min and equivalent norepinephrine requirement was stated. Non-infectious patients: Clinical, laboratory, or radiological findings do not indicate infection, and the current clinical symptoms can be attributed to a non-infectious condition (e.g., acute kidney injury, gastrointestinal bleeding, electrolyte imbalance, vertigo, cerebrovascular disease, hypercalcemia, congestive heart failure, acute coronary syndrome, acute pancreatitis, malignancy-related processes, status epilepticus, pulmonary embolism, etc.), they were defined as non-infectious. Infection patients without sepsis: defined as the absence of signs of organ dysfunction (SOFA\u0026thinsp;\u0026lt;\u0026thinsp;2) in addition to a clinically consistent focus of infection (pneumonia, urinary tract infection, intra-abdominal infection, skin/soft tissue infection, catheter infection, cholecystitis, central nervous system infection, etc.) supported by physical examination, laboratory findings (including microbiological), and/or imaging studies. Sepsis is diagnosed according to Sepsis-3 criteria. Patients showing signs of infection-related organ dysfunction (SOFA\u0026thinsp;\u0026ge;\u0026thinsp;2) were classified in this group. SOFA-1: The original scoring system described by Singer et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), evaluating six organ systems using traditional thresholds and clinical measures. SOFA-2: A revised scoring model incorporating updated cut-off values, expanded definitions of respiratory and renal support, and contemporary clinical practices (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Mortality Rate: All-cause mortality rates during intensive care unit admission or within 28 and 90 days. All diagnoses were determined retrospectively based on electronic medical records.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e was obtained from the local ethics committee prior to the study.\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using IBM SPSS Statistics version 27.0. Data distribution was evaluated visually and with the Shapiro-Wilk test. Continuous variables were summarized as mean\u0026plusmn;standard deviation or median (IQR, 25\u0026ndash;75%), as appropriate. Continuous variables were compared using the Student\u0026rsquo;s t-test or Mann\u0026ndash;Whitney U test, as appropriate. Categorical variables were analyzed using Pearson\u0026rsquo;s chi-square or exact chi-square tests. Multivariable logistic regression was applied to determine independent predictors of mortality. Variables were selected a priori according to clinical relevance and univariate associations. All selected variables were simultaneously entered into the multivariable logistic regression model using the ENTER method. Results are presented as odds ratios (ORs) with 95% confidence intervals (CIs). To reduce collinearity and enhance interpretability, composite severity scores (APACHE II, SOFA-1, and SOFA-2) and their individual components were evaluated in separate models. SOFA-1 and SOFA-2 were evaluated for their ability to predict ICU, 28 and 90 days mortality using ROC curve analysis, with AUCs and 95% CIs reported. Correlated AUCs were compared with DeLong\u0026rsquo;s test (MedCalc). Cutoff points were determined by the Youden index, and diagnostic performance metrics (sensitivity, specificity, PPV, NPV) were calculated from 2\u0026times;2 tables. Statistical significance was defined as a two-tailed p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eStudy population and patient characteristics\u003c/h2\u003e\n \u003cp\u003eA total of 417 patients were screened for our study, and 222 patients meeting the inclusion criteria were enrolled (Fig.\u0026nbsp;1). Women were 38% (n = 85) of our patients and the age of all patients was 70 (62–80), with median SOFA-1 score 9 (5–13), SOFA-2 score 8 (5–12), mean APACHE-II score of 25.8 ± 9.9. Our ICU mortality rate was 57.7% (n = 128), indicating a cohort with a high severity of illness. The most common comorbid condition was hypertension (Table\u0026nbsp;1).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eAssociation of Organ Dysfunction Scores with ICU Mortality in Critically Ill Patients\u003c/h2\u003e\n \u003cp\u003eDuring the ICU course, patients were classified into survivor (SG) and non-survivor groups (NSG); however, no significant differences were identified between the groups regarding; age, gender, creatinine, pH, PCT, CRP and lymphocyte levels both group. APACHE-II, GCS, SOFA-1, and SOFA-2 scores were statistically significantly higher in the non-survivor group (all p \u0026lt; 0.001). All variables comprising SOFA, except creatinine, were statistically significantly higher in the NSG group (Table\u0026nbsp;2).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eUnivariate and Multivariate Logistic Regression Analysis for Predictors of ICU Mortality\u003c/h2\u003e\n \u003cp\u003eIn the multivariate analysis, which included variables that showed meaningful differences between SG and NSG in the univariate analysis, vasopressor requirement (OR 10.8, 95% CI 5.04–23.2; p \u0026lt; 0.001) and GCS score (OR 0.82, 95% CI 0.73–0.92; p = 0.001) were identified as independent predictors of mortality. Patients requiring vasopressor support had a markedly increased risk of mortality. We found that a one-point decrease in GCS increased ICU mortality by 19%. Overall, the model demonstrated good explanatory performance, accounting for approximately 56% of the variance in mortality (Table 3).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eEach One-Point Increase in SOFA-1 and SOFA-2 Confers a Similar Rise in ICU Mortality\u003c/h2\u003e\n \u003cp\u003eWe found that each point rise in the SOFA-1 score was associated with a 42% increase in ICU mortality, while an increase in the SOFA-2 score was associated with a 43% increase (OR 1.428, 95% CI 1.3–1.56; p \u0026lt; 0.001 vs OR 1.43, 95% CI 1.3–1.575; p \u0026lt; 0.001).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eSOFA-1 and SOFA-2 Demonstrate Similar AUCs for ICU Mortality Prediction\u003c/h2\u003e\n \u003cp\u003eIn a total of 222 patients, ICU mortality occurred in 128 patients (57.7%). The AUC of SOFA-1 for predicting ICU mortality was 0.843 (95% CI: 0.792–0.895), while the AUC of SOFA-2 was 0.845 (95% CI: 0.795–0.896). The difference between the two AUCs was not statistically meaningful (p = 0.790). The AUC values of the two scoring systems were similar. According to the Youden index, an optimal cut-off value of 6 was identified for both scores. At this threshold, diagnostic performance metrics including sensitivity, specificity, PPV, and NPV were calculated. SOFA-2 exhibited higher specificity and PPV, while SOFA-1 showed higher sensitivity and NPV. This more balanced diagnostic performance indicates that SOFA-2 may provide superior risk stratification, particularly in clinical settings where avoiding overestimation of mortality risk is crucial (Table 4 and Fig. 2).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study, the intensive care mortality rate was 128 (57%), indicating that a very severe patient group was followed. The median SOFA-1 score for these patients was 9, the SOFA-2 score was 8 and the median APACHE-II score was 25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9. Multivariate analysis identified vasopressor requirement (OR 10.8) and decreased GCS (0.81) as the strongest predictors of mortality. Each point increase in SOFA-1 was associated with a 42% increase in mortality, while each point increase in SOFA-2 was associated with a 43% increase. Both scores predicted in-ICU mortality with high accuracy (SOFA-1 AUC\u0026thinsp;=\u0026thinsp;0.843 vs SOFA-2 AUC\u0026thinsp;=\u0026thinsp;0.845). However, further analyses did not demonstrate a statistically significant superiority of either score in predicting mortality (p\u0026thinsp;=\u0026thinsp;0.79). SOFA-2 had slightly higher specificity, while SOFA-1 had slightly better sensitivity.\u003c/p\u003e \u003cp\u003eIn a multicenter study involving 3.34\u0026nbsp;million patients, the predicted intensive care unit (ICU) mortality rate ranged from 12.4% to 31%, while the actual mortality rate was reported as 8.1%, with this rate varying between 4.5% and 20% across centers. In the same study, the AUC values for SOFA-1 and SOFA-2 scores in predicting mortality were reported as 0.81 and 0.80, respectively. A 2 stage validation analysis also showed that SOFA-1 and SOFA-2 scores performed similarly in predicting mortality, with no significant difference between them (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In our study, the APACHE-II score was determined to be 25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9, and the predicted ICU mortality rate based on this score was 45\u0026ndash;60%, while the actual mortality rate was found to be 57%. When evaluating the ICU mortality prediction performance of SOFA-1 and SOFA-2 scores, AUC values were determined to be 0.843 and 0.845, respectively, and no statistically significant difference was observed between the two scores (p\u0026thinsp;=\u0026thinsp;0.79). As expected, the higher observed mortality rates likely reflect the inclusion of a more severely ill patient population. Although there was no significant difference between the AUC values, it is thought that the high mortality rate may have contributed to higher AUC values for both scores. Also in the same study (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), a 1-point increase in the SOFA-2 score was associated with a 37% increase in mortality. In our study, this rate was found to be 43% and SOFA-1 similarly performance (42%). This difference may again be due to the high severity of disease in our patient profile.\u003c/p\u003e \u003cp\u003eIn our study, SOFA-1 and SOFA-2 scores demonstrated good discriminatory performance for predicting ICU mortality, with AUC values of 0.843 and 0.845, respectively, using a cut-off value of \u0026ge;\u0026thinsp;6 determined by the Youden index. For SOFA-1, this threshold yielded a high sensitivity (89%) with moderate specificity (59%), whereas SOFA-2 showed a slightly lower sensitivity (86%) but higher specificity (62.8%), while PPV and NPV values were comparable between the two scores. These findings suggest that SOFA-2 provides a more balanced sensitivity\u0026ndash;specificity profile, which may be advantageous for clinical risk stratification in the ICU setting. Previous studies have reported lower discriminatory performance for SOFA-1 when higher cut-off values were applied. For example, a study using a SOFA-1 cut-off value greater than 9 reported an AUC of 0.726 for predicting in-hospital mortality, with a sensitivity of 65% and specificity of 75% (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Despite using a lower cut-off value, our study demonstrated a substantially higher AUC, indicating superior overall discrimination. This apparent discrepancy can be explained by differences in study populations, outcome definitions (ICU mortality versus in-hospital mortality), and the methodology used to determine optimal cut-off values.\u003c/p\u003e \u003cp\u003eThis study has several limitations. Its single-center, retrospective design may limit the generalizability of the findings. SOFA-1 and SOFA-2 scores were calculated using the worst values within the first 24 hours of ICU admission; therefore, dynamic changes in organ dysfunction over time were not evaluated. The study population consisted of a severely ill sepsis cohort with a high ICU mortality rate, which may have influenced the discriminatory performance of both scores and limited the ability to detect small differences between them. Finally, although DeLong\u0026rsquo;s test was used for AUC comparison, the sample size may not have been sufficient to identify modest differences in predictive performance.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, both SOFA-1 and SOFA-2 scores demonstrated good discriminatory performance for predicting ICU mortality. SOFA-2 showed a slightly more balanced sensitivity\u0026ndash;specificity profile, the overall predictive performance of the two scores was comparable, as reflected by similar AUC values. Importantly, DeLong analysis did not demonstrate a statistically significant difference between SOFA-1 and SOFA-2, indicating that the updated score does not confer a clear advantage in discriminatory performance. These findings suggest that both scoring systems remain clinically useful for ICU mortality risk stratification, while the potential advantages of SOFA-2 may relate more to calibration and contemporary clinical applicability rather than improved discriminatory ability. However, prospective studies are needed on this subject.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAI: Artificial intelligence\u003c/p\u003e\n\u003cp\u003eAPACHE: Acute physiology and chronic health evaluation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAUC: Area under the curve\u003c/p\u003e\n\u003cp\u003eCBC: Complete blood cell\u003c/p\u003e\n\u003cp\u003eCRP: C-reactive protein\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCI: Confidence interval\u003c/p\u003e\n\u003cp\u003eGCS: Glaskow coma scale\u003c/p\u003e\n\u003cp\u003eICU: Intensive care \u0026uuml;nit\u003c/p\u003e\n\u003cp\u003eMD: Medical doctor\u003c/p\u003e\n\u003cp\u003eNPV: Negative predictive value\u003c/p\u003e\n\u003cp\u003eOR: Odds ratio\u003c/p\u003e\n\u003cp\u003eROC: Receiver operating characteristic\u003c/p\u003e\n\u003cp\u003eSOFA: Sequential organ failure assessment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSTROBE: Strengthening the reporting of observational studies in epidemiology\u003c/p\u003e\n\u003cp\u003ePCT: Procalcitonin\u003c/p\u003e\n\u003cp\u003ePPV: Positive predictive value\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was conducted in accordance with the Declaration of Helsinki and was approved by the Clinical Research Ethics Committee of Kayseri City Training and Research Hospital (Decision No: 711, Date: January 7, 2026). Due to the retrospective design of the study and the use of anonymized patient data, the requirement for informed consent was waived by the ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no external funding for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe contributions of the authors to this manuscript are defined according to the Contributor Roles Taxonomy as follows: Conceptualization: Kamil Deveci. Methodology: Kamil Deveci, Maruf Boran, Esma Eryılmaz Eren. Formal analysis: Kamil Deveci. Investigation: All authors. Data curation: Kamil Deveci, Maruf Boran, Kübra Elif Bahar, Fatma Sarıdağ. Writing–original draft: All authors. Writing–review\u0026amp;editing: All authors. Supervision: All authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst and foremost, we would like to express our gratitude to our valued families and to the staff of the Intensive Care Unit-3 at Kayseri City Education and Research Hospital, especially the nurses.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eVincent JL, Moreno R, Takala J, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure: on behalf of the working group on sepsis-related problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707-710. doi:10. 1007/BF01709751\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCarcoana OV, Hines RL. Is renal dose dopamine protective or therapeutic? Yes. Crit Care Clin. 1996;12(3):677-685. doi:10.1016/s0749-0704(05)70271-2\u003c/li\u003e\n \u003cli\u003eRhodes A, Evans LE, Alhazzani W, et al. Surviving Sepsis Campaign: International Guidelines for Management of Sepsis and Septic Shock: 2016. Crit Care Med. 2017;45(3):486-552. doi:10.1097/CCM.0000000000002255\u003c/li\u003e\n \u003cli\u003eEvans L, Rhodes A, Alhazzani W, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock 2021. Intensive Care Med. 2021;47(11):1181-1247. doi:10.1007/s00134-021-06506-y\u003c/li\u003e\n \u003cli\u003eTwagirumugabe T, Gashame DF, Uwamahoro DL, Riviello E. Advanced non-invasive respiratory support in resource-constrained settings: a narrative review. Crit Care. 2025;29(1):492. Published 2025 Nov 14. doi:10.1186/s13054-025-05688-x\u003c/li\u003e\n \u003cli\u003eMoreno R, Rhodes A, Piquilloud L, et al. The Sequential Organ Failure Assessment (SOFA) score: has the time come for an update? Crit Care. 2023; 27(1):15. doi:10.1186/s13054-022-04290-9 \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMoreno R, Singer M, Rhodes A.Why the Sequential Organ Failure Assessment score needs updating? Crit Care Sci. 2024;36. doi:10.62675/ 2965-2774.20240296-en 7\u003c/li\u003e\n \u003cli\u003eSalluh JIF, Quintairos A, Dongelmans DA, et al; Linking of Global Intensive Care (LOGIC) and Japanese Intensive Care Patient Database (JIPAD) working group. National ICU registries as enablers of clinical research and quality improvement. Crit Care Med. 2024;52(1):125-135. doi:10.1097/CCM. 0000000000006050 10\u003c/li\u003e\n \u003cli\u003eRanzani OT, Singer M, Salluh JIF, et al. Development and Validation of the Sequential Organ Failure Assessment (SOFA)-2 Score. JAMA. Published online October 29, 2025. doi:10.1001/jama.2025.20516\u003c/li\u003e\n \u003cli\u003evon Elm E, Altman DG, Egger M, Pocock SJ, G\u0026oslash;tzsche PC, Vandenbroucke JP; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ. 2007 Oct 20;335(7624):806-8. doi: 10.1136/bmj.39335.541782.AD. PMID: 17947786; PMCID: PMC2034723\u003c/li\u003e\n \u003cli\u003eSinger M, Deutschman CS, Seymour CW, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3).\u0026nbsp;JAMA. 2016;315(8):801-810. doi:10.1001/jama.2016.0287\u003c/li\u003e\n \u003cli\u003eKilinc Toker A, Kose S, Turken M. Comparison of SOFA Score, SIRS, qSOFA, and qSOFA + L Criteria in the Diagnosis and Prognosis of Sepsis. Eurasian J Med. 2021;53(1):40-47. doi:10.5152/eurasianjmed.2021.20081\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTablo 1.\u003c/strong\u003e Baseline Characteristics of The Study Population\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eAge years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e70 (62-80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eFemale Sex, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e85 (38)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eICU admission n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Emergency Department\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e125 (56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Ward\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e79 (35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other ICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e18 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eComorbities, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hypertension\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e97 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Solid malignancy\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e74 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Diabetes mellitus\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e72 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Chronic kidney disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e47 (9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Coronary artery disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e42 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;COPD\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e30 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eGCS Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e12 (5-14)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eAPACHE-II Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e25.8\u0026plusmn;9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eSOFA-1 Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e9 (5-13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eSOFA-2 Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e8 (5-12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003eICU mortality n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e128 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e28 days mortality n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e120 (54)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e90 days mortality n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 387px;\"\u003e\n \u003cp\u003e143 (64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: APACHE, Acute Physiology and Chronic Health Evaluation; GCS, Glaskow Coma Scale; ICU, Intensive Care Unit; SOFA, Sequential Organ Failure Assessment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTablo 2.\u0026nbsp;\u003c/strong\u003eComparison of Survivors and Non-Survivors in the ICU\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"618\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvivors (n=94)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-survivors \u0026nbsp;(n=128)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eAge years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e71.5 (60-82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e70 (63-79.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0,994\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eFemale Sex, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e37 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e48 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eApache-II Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21\u0026plusmn;7.8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e29\u0026plusmn;10.1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSOFA-1 Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (3-8)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (8.2-14.7)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eSOFA-2 Score\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (3-7)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11 (7.2-14)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eGCS Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14 (11-14.2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8 (3-13)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePaO\u003csub\u003e2/\u003c/sub\u003eFiO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eratio\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e276\u0026plusmn;102\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e213\u0026plusmn;95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eVasopressor requirement n,(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20 (21.3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e108 (84.4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 618px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eWBC count* \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e12.5 (8.6-17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e13.1 (7.1-21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eLymphocyte count * \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.9 (0.55-1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e0.81 (0.52-1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.930\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePlatelet count * \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e195 (144-270)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e164 (71-264)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.023\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eTotal bilirubin mg/dL\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6 (0.4-1.2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8 (0.5-1.97)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eCreatinin mg/dL\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.28 (0.73-3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e1.4 (1.2-3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eINR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.25 (1.1-1.4)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.4 (1.2-1.87)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003epH\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e7.38 (7.30-7.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e7.31 (7.24-7.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eLactate mmol/L\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.5 (1.1-2.5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.5 (1.4-4.1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePCT ng/mL\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e1.3 (0.3-6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e1.5 (0.37-6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eCRP mg/L\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e142 (79-200)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e115 (43-208)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 61px;\"\u003e\n \u003cp\u003e0.224\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: APACHE-II, Acute Physiology and Chronic Health Evaluation II; GCS, Glaskow Coma Scale; SOFA, Sequential Organ Failure Assessment; WBC,White Blood Cells; *\u0026times;10\u003csup\u003e3\u003c/sup\u003e/mm\u003csup\u003e3\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Univariate and Multivariate Logistic Regression Analysis for Predictors of ICU Mortality\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOR(%95 CI)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eOR(% 95 CI)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eGCS Score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.817 (0.726\u0026ndash;0.919)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.817 (0.726\u0026ndash;0.919)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003ePaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.997 (0.993\u0026ndash;1.001)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eVasopressor requirement \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.8 (5.04\u0026ndash;23.2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.8 (5.04\u0026ndash;23.2)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003ePlatelet count\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.00(1.00-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eTotal Bilirubin mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.01 (0.832\u0026ndash;1.226)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eINR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e1.56 (0.77\u0026ndash;3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eLactate \u0026nbsp;mmol/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.08 (0.892\u0026ndash;1.314)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e---\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e0.423\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: CI, Confidence Interval; GCS,Glaskow Coma Scale; OR, Odds ratio.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModel fit: \u0026minus;2 Log likelihood=173; Cox \u0026amp; Snell R\u0026sup2; = 0.42; Nagelkerke R\u0026sup2; = 0.567\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eAnalysis of the Performance of SOFA-1 and SOFA-2 in Predicting in-ICU, 28 and 90 days Mortality in Sepsis Patients\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"604\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCut-off\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eICU mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSOFA-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSOFA-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28-day mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSOFA-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSOFA-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90-day mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSOFA-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e76.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSOFA-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: AUC, Area under curve; \u0026nbsp;ICU, Intensive care unit; NPV, Negative predictive value; PPV,Positive predictive value.\u003c/p\u003e\n\u003cp\u003eThere was no statistically significant difference between SOFA-1 and SOFA-2 AUCs (DeLong test)\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mortality, SOFA-2, Organ Failure, Severity of Illness Index","lastPublishedDoi":"10.21203/rs.3.rs-9003079/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9003079/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/em\u003e The Sequential Organ Failure Assessment (SOFA) score has been widely used for nearly three decades to evaluate organ dysfunction and predict mortality in patients with sepsis. Advances in critical care practice have led to the development of an updated version, SOFA-2, incorporating contemporary organ support strategies and revised clinical thresholds. However, real-world comparative data evaluating the prognostic performance of the original SOFA score (SOFA-1) and SOFA-2 remain limited. This study aimed to compare the ability of SOFA-1 and SOFA-2 to predict intensive care unit (ICU), 28-day, and 90-day mortality in patients with sepsis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/em\u003e This retrospective, single-center observational cohort study included adult patients (≥18 years) diagnosed with sepsis according to Sepsis-3 criteria and admitted between December 2023 and August 2024. SOFA-1 and SOFA-2 scores were calculated using clinical and laboratory data obtained at ICU admission. The primary outcome was ICU mortality; secondary outcomes were 28-day and 90-day mortality. Multivariable logistic regression was performed to identify independent predictors of mortality. Discriminatory performance was assessed using receiver operating characteristic analysis, and areas under the curve were compared using DeLong’s test. Optimal cut-off values were determined using the Youden index.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/em\u003e Among 417 screened patients, 222 met the inclusion criteria. ICU mortality was 57.7%. Each one-point increase in SOFA-1 and SOFA-2 scores was associated with a 42% and 43% increase in ICU mortality, respectively (p\u0026lt;0.001 for both). The area under the curve for ICU mortality prediction was 0.843 (95% confidence interval 0.792–0.895) for SOFA-1 and 0.845 (95% confidence interval 0.795–0.896) for SOFA-2, with no statistically significant difference between the two scores (p=0.79). SOFA-2 demonstrated slightly higher specificity, whereas SOFA-1 showed marginally higher sensitivity at the optimal cut-off value.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e\u003c/em\u003e Both SOFA-1 and SOFA-2 demonstrated good discriminatory performance for predicting ICU mortality in patients with sepsis. Although SOFA-2 provided a more balanced sensitivity–specificity profile, its overall predictive performance was comparable to that of SOFA-1. Further prospective multicenter studies are warranted to clarify the incremental clinical value of the updated score.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e\u003c/em\u003e: Not applicable.\u003c/p\u003e","manuscriptTitle":"Does SOFA-2 Improve Mortality Prediction in Sepsis? A Retrospective Single-Center Observational Cohort Study Comparing SOFA-1 and SOFA-2","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-24 16:00:41","doi":"10.21203/rs.3.rs-9003079/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-15T11:31:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T15:59:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187791812582939966155847530997482961893","date":"2026-04-10T09:34:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-28T10:44:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-27T16:35:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331110832444110530862758417576045129119","date":"2026-03-19T11:58:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"68685910829095173085612140615155377465","date":"2026-03-19T02:49:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-19T02:47:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-05T03:47:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-03T09:52:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-03T09:50:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2026-03-01T17:14:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fa5253a9-7a79-4243-a79a-e6b66495c3bc","owner":[],"postedDate":"March 24th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-15T11:31:06+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T15:23:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-24 16:00:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9003079","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9003079","identity":"rs-9003079","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}