ArticleBMC emergency medicine2024
Comparison of Modified Early Warning Score (MEWS), Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA), and Acute Physiology and Chronic Health Evaluation II (APACHE II) for early prediction of septic shock in diabetic patients in Emergency Departments.
Article in BMC emergency medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07249749 (Factors Associated With Mortality in the Intensive Care Unit From the Orinoco Region. An Observational Trial), which is not on this map. Cited by 10 papers.
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Factors Associated With Mortality in the Intensive Care Unit From the Orinoco Region. An Observational Trial
Who cites it
10 citing papers in PubMed.
- Development and multi-center validation of a machine learning‑based prediction model for mortality in tumor-related sepsis.BMC infectious diseases · 2026Article
- Predicting ICU in-hospital mortality from text-encoded structured EHR data using adaptive transformer layer fusion.iScience · 2026Article
- Predictive value of NLMR, PLR, and ferritin in relation to SOFA, APACHE II, and SAPS II in sepsis patients.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2026Article
- Investigating the Predictive Power of the National Early Warning Score in Predicting Outcomes Among Intensive Care Unit Patients.Critical care research and practice · 2026Article
- Shock index and early warning score in liver cancer rupture shock.World journal of gastrointestinal surgery · 2025Article
- Comparison of Intensive Care Scoring Systems in Predicting Overall Mortality of Sepsis.Diagnostics (Basel, Switzerland) · 2025Article
- Impact of Diabetes on Clinical Characteristics and Prognosis in Sepsis: A Retrospective Study.Journal of inflammation research · 2025Article
- Application of Modified Early Warning Score System (MEWS) in the Assessment of Disease Condition and Prognosis of Patients After Neurosurgical Procedure or Intervention.Risk management and healthcare policy · 2025Article
- Construction of a predictive model for severe hypertriglyceridemia-associated acute pancreatitis using machine learning.American journal of translational research · 2025Article
- Artificial intelligence-assisted phenotyping of sepsis: Research progress, clinical challenges, and translational prospects.Digital healthReview
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8 authors.
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Abstract
introductionSepsis is a severe medical condition that can be life-threatening. If sepsis progresses to septic shock, the mortality rate increases to around 40%, much higher than the 10% mortality observed in sepsis. Diabetes increases infection and sepsis risk, making management complex. Various scores of screening tools, such as Modified Early Warning Score (MEWS), Simplified Acute Physiology Score (SAPS II), Sequential Organ Failure Assessment Score (SOFA), and Acute Physiology and Chronic Health Evaluation (APACHE II), are used to predict the severity or mortality rate of disease. Our study aimed to compare the effectiveness and optimal cutoff points of these scores. We focused on the early prediction of septic shock in patients with diabetes in the Emergency Department (ED).
methodsWe conducted a retrospective cohort study to collect data on patients with diabetes. We collected prediction factors and MEWS, SOFA, SAPS II and APACHE II scores to predict septic shock in these patients. We determined the optimal cutoff points for each score. Subsequently, we compared the identified scores with the gold standard for diagnosing septic shock by applying the Sepsis-3 criteria.
resultsSystolic blood pressure (SBP), peripheral oxygen saturation (SpO2), Glasgow Coma Scale (GCS), pH, and lactate concentrations were significant predictors of septic shock (p < 0.001). The SOFA score performed well in predicting septic shock in patients with diabetes. The area under the receiver operating characteristics (ROC) curve for the SOFA score was 0.866 for detection within 48 h and 0.840 for detection after 2 h of admission to the ED, with the optimal cutoff score of ≥ 6.
conclusionSBP, SpO2, GCS, pH, and lactate concentrations are crucial for the early prediction of septic shock in patients with diabetes. The SOFA score is a superior predictor for the onset of septic shock in patients with diabetes compared with MEWS, SAPS II, and APACHE II scores. Specifically, a cutoff of ≥ 6 in the SOFA score demonstrates high accuracy in predicting shock within 48 h post-ED visit and as early as 2 h after ED admission.
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