Background: Sepsis is a major cause of morbidity and mortality in emergency and critical care settings, particularly in resource-limited countries like India. Early identification of high-risk patients is crucial for timely intervention and optimal resource utilization. The Rapid Emergency Medicine Score (REMS) is a simple, bedside physiological scoring system that may help predict mortality at the time of emergency department presentation.

Methods: This was a prospective observational study conducted in a tertiary care emergency department. A total of 166 adult patients with sepsis were enrolled and followed until discharge or death. REMS was calculated at presentation using six clinical parameters: age, heart rate, respiratory rate, mean arterial pressure, Glasgow Coma Scale, and oxygen saturation. Patients were categorized into survivors and non-survivors. ROC curve analysis was performed to evaluate the predictive accuracy of REMS. Multivariate logistic regression was used to identify independent predictors of in-hospital mortality.

Results: Out of 166 patients, 108 (65.1%) survived and 58 (34.9%) died. Mean REMS score was significantly higher among non-survivors (11.1 ± 3.1) compared to survivors (6.4 ± 2.3), (p < 0.001). REMS demonstrated good predictive accuracy for in-hospital mortality with an AUC of 0.84 (95% CI: 0.77–0.89). At a cut-off of REMS ≥10, sensitivity was 62.1%, specificity 88.9%, PPV 75.8%, NPV 81.4%, and overall accuracy 79.5%. On multivariate analysis, REMS (AOR: 1.39 per point increase, p < 0.001), septic shock at presentation (AOR: 3.46, p < 0.001), serum lactate (AOR: 1.57 per mmol/L, p < 0.001), and age (AOR: 1.31 per 10-year increase, p = 0.003) were independent predictors of mortality.

Conclusion: REMS is a simple, rapid, and reliable bedside tool for predicting in-hospital mortality in patients with sepsis. Its good discriminatory ability and ease of application make it particularly useful for triage and risk stratification in busy and resource-limited emergency departments. Early use of REMS may help prioritize critically ill patients for aggressive management and intensive care admission.