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Evaluation of the performance of disease severity indices (SOFA, SAPS III, and MPM II) for the prediction of mortality rate in COVID-19 patients admitted to the intensive care units: a retrospective cross-sectional study

BMC Infectious Diseases volume 25, Article number: 637 (2025) Cite this article

Abstract

Background

The COVID-19 pandemic created a high demand for hospital beds and intensive care, which led to the collapse of healthcare systems. Therefore, it is critical to identify factors associated with increased mortality in patients to prioritize high-risk individuals.

Aim

Given the potential for similar pandemics in the future, this study investigated predictors of mortality in ICU patients with COVID-19 and their correlation with mortality rates.

Study design

In this retrospective study, all patients admitted to the ICUs of Ghaem and Imam Reza tertiary hospitals in Mashhad with a definitive diagnosis of COVID-19 from March 21, 2020, to December 1, 2021, were evaluated for disease severity assessment criteria, including SOFA, SAPS III, and MPM II.

Results

One hundred seventy-two patients with COVID-19 who were admitted to the ICU were evaluated (147 patients in the non-survivor group and 25 patients in the survivor group. The median SAPS, SOFA, and MPM scores were significantly higher in non-survivors (p<0.001 in all cases). Higher SAPS, SOFA, and MPM were associated with an increased risk of mortality in COVID-19 patients in the ICU. The best cut-off points for the three scoring systems, SAPS, SOFA, and MPM, were 39, 6, and 13.7, respectively. The AUC value of the SOFA score was significantly higher than the SAPS (P = 0.0274) and MPM (P = 0.0209) scores.

Conclusion

COVID-19 patients admitted to the ICU with higher SOFA, MPM, and SAPS scores suffered from higher mortality rates. Because the SOFA score showed high predictive accuracy, this scoring system should be considered a priority as an essential tool in triaging and managing critically ill COVID-19 patients.

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Introduction

In December 2019, doctors reported cases of pneumonia with an unknown cause. The new coronavirus (Severe Acute Respiratory Syndrome - Coronavirus 2 (SARS-CoV-2)) spread and caused a pandemic. While most patients experienced mild illness, a significant number of patients developed severe disease that rapidly progressed to acute respiratory distress syndrome or end-organ failure [1]. Severe and critical illness occurs in approximately 47% of hospitalized patients [2]. Evidence suggests that older age and underlying medical conditions increase patient risk [3]. Prognostic scores can be used to analyze cohort or group studies of specific diseases and guide health strategies and resource allocation. Among these scores, the APACHE, SOFA, and SAPS scores are widely utilized to predict outcomes in critically ill patients. These scores are comprehensive, incorporating multiple physiological variables from different organ systems. Furthermore, mortality prediction scores can estimate the likelihood of developing sepsis and assess patient survival. Early identification of patients at risk of developing sepsis facilitates appropriate approaches to ICU admission, improving treatment outcomes [4].

The Simplified Acute Physiology Score (SAPS II) was initially introduced in 1984 as a substitute for APACHE II. SAPS II is calculated based on the highest score of 12 routine physiological parameters within the first 24 hours of admission, prior health information, and information collected upon admission. It is completed within the initial 24 hours of the patient’s ICU admission and predicts in-hospital mortality [5]. The Sequential Organ Failure Assessment (SOFA) score describes the level of dysfunction in multiple organs. An elevated SOFA score, indicating the severity of multiple organ failure, is associated with high CRP and PCT levels. As this score correlates with these two markers, it is expected to be used in predicting or identifying post-discharge complications in patients [6]. Another tool for predicting mortality in the intensive care unit is the Mortality Prediction Model (MPM), created using multivariate statistical analysis and validated through a large cohort study [7]. In a study by Zhou et al., the SOFA score was employed to predict mortality in COVID-19 patients [8]. In the study by Roedl et al., the SOFA and SAPS III systems were used to assess disease severity in COVID-19 patients [1]. The study by Livingston et al. demonstrated the superiority of the SAPS II model over other models [9].

Following the spread of the COVID-19 virus in December 2019, the COVID-19 pandemic posed a global challenge for healthcare systems worldwide. The rapid spread of the disease, COVID-19, created a high demand for hospital beds and intensive care, resulting in overwhelmed healthcare systems, particularly in developing countries with limited hospital resources. Therefore, it is critical to identify factors associated with increased mortality in patients to prioritize high-risk individuals. Mortality prediction scores can predict the likelihood of developing sepsis and assess patient survival. Given the potential for similar pandemics in the future, this study investigated predictors of mortality in ICU patients with COVID-19 and their correlation with mortality rates.

Methods

Study design

In this retrospective cross-sectional study, we examined patients admitted to the ICUs of Ghaem and Imam Reza tertiary hospitals in Mashhad from March 21, 2020, to December 1, 2021. All adult patients aged more than 18 who were admitted to the ICUs of Ghaem and Imam Reza hospitals with a confirmed diagnosis of COVID-19 by positive polymerase chain reaction (PCR) test were included in this study.

The exclusion criteria for this study were as follows: lack of PCR test result, diagnosis of COVID-19 solely based on imaging findings, lack of sufficient medical information in the record to complete the assessment questionnaires, and unclear final patient status.

Data collection

We evaluated all individuals who met the inclusion criteria for SAPS III, MPM II, and SOFA scoring systems at the time of ICU admission. It is important to note that we used the latest versions of the predictive criteria in this study. Two independent researchers reviewed patients’ medical records admitted to the ICU and conducted the scoring process to ensure consistency. Discrepancies were resolved through discussion with a senior clinician. We used criteria such as heart rate, blood pressure, respiratory rate, body temperature, GCS, and laboratory parameters recorded in the patients’ manual records and hospital information system (HIS) at admission to calculate the scoring systems. Any complications were recorded in the relevant sheets for each patient, specific to each scoring system. We investigated and analyzed the relationship between these criteria at admission and subsequent patient mortality rates using statistical methods.

Ethical approval

The study protocol was reviewed and approved by the ethics committee of the Mashhad University of Medical Sciences (ethics code: IR.MUMS.MEDICAL.REC.1400.839). The study followed the Declaration of Helsinki, and considering its retrospective structure, no consent forms were obtained from the patients.

Statistical analysis

SPSS version 16 software (SPSS Inc., Chicago, Illinois) was used for data analysis. Qualitative data were reported as numbers and percentages, and chi-square and Fisher’s exact tests were used to compare them between the two groups. In order to check the distribution of quantitative variables, the Kolmogorov-Smirnov test was used. Variables with normal distribution were reported as Mean ± SD and non-normal distribution as medians (interquartile range). Independent samples t-test was used to compare quantitative variables with normal distribution between two groups and the Mann-Whitney U test with non-normal distribution between two groups. Univariate regression analysis was used to identify the odds ratio of mortality if the level of any of the predictive scoring systems increased.

The receiver operating characteristic (ROC) analysis was performed using MedCalc® Statistical Software version 20.013 (MedCalc Software Ltd). The ROC curve was used to investigate and compare the role of scoring systems in predicting the mortality of COVID-19 patients hospitalized in the ICU. The optimal cut-off point was determined using the Youden index.

Results

In this study, 172 patients with COVID-19 who were admitted to the ICU were evaluated. One hundred forty-seven patients finally died in the ICU (non-survivor group), and 25 patients survived and were discharged (survivor group). Table 1 compares the characteristics of the two groups of patients.

Table 1 Comparison of the data examined in deceased patients and discharged patient
Full size table

The mean ages of survivors and non-survivors were 50.64 ± 16.45 years and 45.67 ± 16.87 years, respectively (P = 0.174). The prevalence of male gender in survivors and non-survivors was 44.0% and 57.8%, respectively (P = 0.198). The intra-hospital location before ICU admission in 80.0% of survivors and 61.2% of non-survivors were in the emergency department (P = 0.071).

Median GCS at the ICU admission time in survivors was significantly higher than non-survivors (15.0 (IQR 12.5 - 15.0) vs. 6.0 (IQR 4.0 - 6.0), respectively) (P<0.001). Both groups had a similar body temperature and heart rate (P = 0.592 and P = 0.838, respectively). Median systolic blood pressure in the survivors group was 126.0 mmHg (IQR 124.0 - 136.0), and in the non-survivors group was 124.0 mmHg (IQR 115.0 - 135.0) (P = 0.030).

Median serum creatinine level at the time of ICU admission in the survivors group was significantly lower than in the non-survivors group (0.90 mg/dL (IQR 0.7–1.10) vs. 1.20 mg/dL (IQR 0.8–2.0), respectively) (P = 0.002). The platelet count, PaO2, and PaO2/FiO2 were significantly higher in the survivors’ group (P = 0.012, P = 0.026, and P<0.001, respectively). The Median of FiO2 was 50.0% (IQR 50.0 - 80.0) in survivors and 100% (IQR 100-100) in non-survivors (P<0.001).

The prevalence of comorbidities, as shown in Table 1, was similar in both groups. The prevalence of gastrointestinal bleeding and cerebrovascular accident during ICU stay in both groups showed no significant difference. Acute kidney injury during ICU stay was observed in 12.0% of survivors and 55.8% of non-survivors (P<0.001). The median SAPS, SOFA, and MPM scores were significantly higher in non-survivors (48.0 (IQR 43.5 - 53.5) vs. 37.0 (IQR 34.0 - 42.0), 10.0 (IQR 8.0 - 11.0) vs. 3.0 (IQR 2.0 - 6.0), and 27.9 (IQR 13.6 - 48.9) vs. 7.6 (IQR 4.7 - 12.5), respectively; p<0.001 in all cases). As shown in Table 1, other variables did not show any significant differences between the two groups.

Univariate regression analysis was used to determine the odds ratio of mortality if the level of any of the predictive scoring systems in the ICU increased. The results of univariate analysis are shown in Table 2. According to the results of univariate regression analysis, higher SAPS (OR, 1.224; 95% CI, 1.131 - 1.325), SOFA (OR, 2.073; 95% CI, 1.624 - 2.647), and MPM (OR, 1.120; 95% CI, 1.056 - 1.187) were associated with increased risk of mortality in COVID-19 ICU patients.

Table 2 Univariate regression analysis of scoring systems (SAPS, MPM, and SOFA) according to their association with mortality in COVID-19 patients
Full size table

The ROC curve was used to evaluate the clinical value of the three scoring systems, SAPS, SOFA, and MPM, in predicting mortality and assessing their diagnostic potential in discriminating individuals with high and low risk of mortality by determining sensitivity, specificity, and cut-off points. The best cut-off points for the three scoring systems, SAPS, SOFA, and MPM, were 39, 6, and 13.7, respectively. Among these three scoring systems, the SOFA system demonstrated the highest accuracy due to having the largest area under the curve (0.921) and, a sensitivity of 92.52% and specificity of 80.0%. However, the SAPS and MPM scoring systems also exhibited high predictive power for mortality in this study. The results related to the area under the curve, best cut-off point, and sensitivity and specificity of the scoring systems are presented in Table 3 and Fig. 1.

Table 3 Results from ROC analysis to estimate the best cut-off, sensitivity, and specificity of scoring systems in predicting patient mortality
Full size table
Fig. 1
figure 1

Curve for the three scoring systems SAPS, SOFA, and MPM to determine the area under the curve as an estimate of predictive power for mortality, the best cut-off point, and sensitivity and specificity

Full size image

Table 4 shows a pairwise comparison of ROC curves. The AUC value of the SOFA score was significantly higher than that of the SAPS (P = 0.0274) and MPM (P = 0.0209) scores. The AUC value of the SAPS and MPM scores did not show any significant difference (P = 5735).

Table 4 Pairwise comparison of ROC curves
Full size table

Discussion

Our study investigated the relationship between disease severity indices (SOFA, SAPS III, and MPM II) and mortality in ICU patients with COVID-19. Higher scores in these systems were significantly associated with increased mortality rates. The SOFA score exhibited the highest predictive accuracy, with an AUC of 0.92, sensitivity of 92.5%, and specificity of 80%. SOFA was the most reliable predictor compared to others.

The SOFA score, which evaluates organ dysfunction across multiple systems, showed the highest predictive performance in our cohort. Our finding aligns well with previous studies [10,11,12,13,14], such as Esmaeili et al. [11], an extensive survey of 1057 patients, which introduced the mean SOFA upon first 96 h of ICU stay as a reliable mortality predictor, and Fayed et al. [12], which indicated that a higher SOFA score is directly correlated with increased mortality in COVID-19 patients. In our study, patients with SOFA scores above 6 (the best cut-off point) were at increased risk of death. This is consistent with Fayed et al.’s data that a SOFA score 5 predicts the severity and mortality in patients with COVID-19 pneumonia. Against this, Beigmohammadi et al. reported that daily SOFA has a better predictive performance than acute physiology and chronic health evaluation (APACHE II) in critically ill patients with COVID-19, with a cut-off point of 13 for APACHE II and 5 for SOFA score. However, they could not predict death with high accuracy [15]. Also, in another study on COVID-19 patients with respiratory failure, the SOFA score was not an accurate index for ventilator triage of COVID-19 patients [16].

In our study, the SAPS III score, incorporating a range of physiological and clinical variables, also demonstrated strong predictive ability, with an AUC of 0.85. Previous studies, such as Metnitz et al. [17], similarly found that SAPS III effectively predicts mortality in ICU patients, particularly those with COVID-19. In another study, the SAPS III score was valid in predicting the 28-day mortality of COVID-19 patients in the ICU [18]. Furthermore, a study introduced the SAPS III as a reliable predictive index for death in the COVID-19 pandemic, especially in patients with renal and pulmonary dysfunction [19]. Against this, Aziz et al. evaluated the performance of SAPS III to predict mortality in patients with COVID-19 with and without diabetes. They showed that SAPS III had low discrimination and accuracy in Austrian patients with COVID-19 regardless of diabetes and non-diabetes [20]. Moreover, in a recent study, the ABC2-SPH scoring system was superior to other risk scores, including SOFA and SAPS III [21].

The MPM II score was also a reliable predictor of mortality, with an AUC of 0.83, demonstrating substantial predictive power. Align with our data in a study on mortality risk calculation for COVID-19, the MPM had a ROC-AUC of 0.79 and could predict mortality with a sensitivity of 75% and a specificity of 70% [22]. The MPM II scoring system is a practical measuring index associated with clinical parameters and can predict the risk of death of a patient. This is very useful when there is a need for more facilities. MPM’s lower accuracy level than SOFA indicates that it should be mainly used as a supplementary tool.

Using ROC curve analysis, we identified optimal cut-off points for the three scoring systems: SAPS (39), SOFA [6], and MPM (13.7). Establishing these cut-offs enables clinicians to prioritize ICU admissions, allocate ventilators, and stratify patients based on mortality risk during pandemics. A SOFA score cutoff of 6, as identified in our study, could serve as a threshold for prioritizing critically ill patients for ICU admission during periods of high demand. Incorporating this cutoff into triage protocols may help clinicians make timely and objective decisions about resource allocation, especially in settings where capacity is limited and rapid risk stratification is required. While other widely used severity indices (APACHE II and LODS) were not evaluated, our study focused on SAPS, SOFA, and MPM due to their frequent application in COVID-19 ICU patients and their ability to comprehensively assess multi-organ dysfunction. In Addition, in our healthcare setting, APACHE II and LODS are not commonly utilized, and we lacked all the data points necessary to calculate these indices accurately.

Our study found that a lower GCS score and the occurrence of AKI were both significantly associated with higher mortality. These findings are consistent with prior research [23,24,25,26], which has demonstrated that low GCS scores and AKI are common complications in critically ill COVID-19 patients and are strong predictors of higher mortality. For instance, Xiong et al. identified altered consciousness and its progression were directly related to COVID-19 mortality [23], and a meta-analysis revealed that AKI is associated with a 13-fold increased risk of mortality, reinforcing the need for careful monitoring of COVID-19 patients with AKI [25].

Our study found no significant association between GIB or CVA and increased mortality. In line with our findings, Makker et al. found that GI bleeding did not significantly alter the mortality rates in COVID-19 patients [27]. According to another study, hospitalized COVID-19 patients with acute GIB have an increased risk of mortality, but a large percentage of deaths are not related to bleeding [28]. Our results on CVA are in contrast with a meta-analysis, which reported a mortality rate of 29.2% among COVID-19 patients with ischemic CVA [29]. However, the lack of significance in our study could be due to the relatively small sample size for these specific complications, or it may indicate that these factors play a less critical role in the mortality of COVID-19 patients.

Limitations & further research

The limitations of the present study are as follows: the retrospective design would have introduced bias in general, particularly in the completion and accuracy of the records. Our research is subject to selection bias, missing data, and potential misclassification of clinical parameters. The study was conducted in two hospitals in Mashhad, and its generalization in other settings would be questionable. Although we performed a multivariate analysis, the low incidence of comorbidities and limited sample size contributed to the lack of statistically significant findings. As such, we relied on univariate analysis, which may limit our ability to adjust for potential confounders. Future studies with larger cohorts are needed to examine these associations more robustly. Finally, our study investigated only short-term mortality outcomes in the ICU, and other studies should be done on the long-term outcomes in survivors who had COVID-19. In future research, biomarkers such as CRP and procalcitonin (PCT) can be combined with clinical scoring systems to enhance the predictive value of mortality models. Additionally, more extensive multicenter studies will confirm our findings, establishing the use of these scoring systems among various populations and healthcare systems.

Conclusion

Overall, the results of the present study indicated that COVID-19 patients admitted to the ICU with higher SOFA, MPM, and SAPS scores suffered from higher mortality rates. Additionally, low GCS levels and the occurrence of AKI were significantly associated with increased mortality. Because the SOFA score showed high predictive accuracy, this scoring system should be considered a priority and an essential tool in managing critically ill COVID-19 patients. SAPS III and MPM II are equally useful for predicting outcomes.

Data availability

The data supporting this study’s findings are available from the corresponding author upon reasonable request.

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Acknowledgements

The researchers thank all individuals who participated in the execution of the project in any way.

Funding

The Mashhad University of Medical Sciences funded this study. The data in this article were taken from the thesis of Hanieh Ahmadi Hekmatikar at the Mashhad University of Medical Sciences. (Reg. No. 4000290).

Author information

Authors and Affiliations

  1. Lung Disease Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

    Reza Basiri, Hanieh Ahmadi Hekmatikar & Amir Baniasad

  2. Faculty of Medicine, Kerman University of Medical Sciences, Kerman, Iran

    Mohammad Javad Najafzadeh

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Contributions

R.B., H.A.H., M.J.N., and A.B. designed the study and collected data, A.B. and M.J.N. analyzed data, wrote the first draft of the paper and submitted the manuscript, R.B. and H.A.H. contributed to writing and revision of the manuscript. All authors contributed to finalizing the manuscript.

Corresponding author

Correspondence to Amir Baniasad.

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Ethics approval and consent to participate

The study protocol was reviewed and approved by the ethics committee of the Mashhad University of Medical Sciences (ethics code: IR.MUMS.MEDICAL.REC.1400.839). The study followed the Declaration of Helsinki, and considering its retrospective structure, no consent forms were obtained from the patients. Informed consent was obtained from all participants to participate in the study.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Basiri, R., Ahmadi Hekmatikar, H., Najafzadeh, M.J. et al. Evaluation of the performance of disease severity indices (SOFA, SAPS III, and MPM II) for the prediction of mortality rate in COVID-19 patients admitted to the intensive care units: a retrospective cross-sectional study. BMC Infect Dis 25, 637 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12879-025-11045-8

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BMC Infectious Diseases

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