Journals / Eskisehir Medical Journal / 2026 / Volume: 6 Issue: 2

Predicting Mortality in Ambulance-Transported Emergency Department Patients: A Comparative Retrospective Cohort Study

Ambulansla Taşınan Acil Servis Hastalarında Mortalite Öngörüsü: Karşılaştırmalı Retrospektif Kohort Çalışması

İlker Şirin(ANKARA ETLİK CİTY HOSPİTAL)0000-0003-2694-5574
Emrah Arı(Ankara Mamak State Hospital)0000-0003-4006-380X
Pages
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Publication Date
2025-07-28
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Conclusion: This study found that both REMS and rSIGCS are effective tools for predicting early mortality among non-trauma patients transported to the emergency department by ambulance.

📌 3 Key Takeaways

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Objective & Hypothesis:Introduction: Accurate and timely triage in emergency departments facilitates the identification of critically ill patients, thereby improving the quality of care and promoting the efficient use of healthcare resources.
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Key Findings & Data:Methods: This retrospective cohort study was conducted at a single center and included 1,676 patients who were brought to the emergency department via ambulance over the course of June 2024.
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Conclusion & Impact:Conclusion: This study found that both REMS and rSIGCS are effective tools for predicting early mortality among non-trauma patients transported to the emergency department by ambulance.
🔬Design:Research Article
📍Scope:2024 Verileri
⚙️Variables:Emergency department · Mortality · Vital Signs

Abstract

Introduction: Accurate and timely triage in emergency departments facilitates the identification of critically ill patients, thereby improving the quality of care and promoting the efficient use of healthcare resources. In this study, we aimed to assess the utility of selected scoring systems calculated using prehospital data obtained in the ambulance setting, with a focus on their applicability before hospital arrival. Methods: This retrospective cohort study was conducted at a single center and included 1,676 patients who were brought to the emergency department via ambulance over the course of June 2024. For each patient, the Rapid Emergency Medicine Score (REMS), Rapid Acute Physiology Score (RAPS), Shock Index (SI), and the revised Shock Index multiplied by the Glasgow Coma Scale (rSIGCS) were calculated. To evaluate the predictive accuracy of each scoring system, receiver operating characteristic (ROC) curve analysis was employed. Additionally, multivariable logistic regression analysis was conducted to determine independent risk factors associated with mortality. Results: The REMS demonstrated the highest discriminatory power for predicting 24-hour mortality, with c-statistics value of 0.897 (95% CI: 0.881–0.911). The rSIGCS also showed good performance, with c-statistics value of 0.843 (95% CI: 0.824–0.860). No statistically significant difference was observed between REMS and rSIGCS (p = 0.2166, DeLong test), suggesting that both scoring systems may serve as effective tools for early mortality prediction in the prehospital setting. Conclusion: This study found that both REMS and rSIGCS are effective tools for predicting early mortality among non-trauma patients transported to the emergency department by ambulance.

Özet

Giriş: Acil servislerde doğru ve zamanında triyaj, kritik hastaların belirlenmesini kolaylaştırarak bakım kalitesini artırır ve sağlık hizmeti kaynaklarının etkin kullanımını teşvik eder. Bu çalışmada, hastaneye ulaşmadan önce, ambulans ortamında elde edilen verilere dayanarak hesaplanan seçilmiş skorlama sistemlerinin kullanılabilirliğini değerlendirmeyi amaçladık. Yöntemler: Bu retrospektif kohort çalışma, tek merkezde yürütüldü ve Haziran 2024 boyunca ambulansla acil servise getirilen 1.676 hasta dahil edildi. Her hasta için Rapid Emergency Medicine Score (REMS), Rapid Acute Physiology Score (RAPS), Şok İndeksi (SI) ve Glasgow Koma Skalası ile çarpılmış revize şok indeksi (rSIGCS) hesaplandı. Her bir skorlama sisteminin öngörü doğruluğunu değerlendirmek için receiver operating characteristic (ROC) eğrisi analizi kullanıldı. Ek olarak, mortalite ile ilişkili bağımsız risk faktörlerini belirlemek amacıyla çok değişkenli lojistik regresyon analizi gerçekleştirildi. Bulgular: REMS, 24 saatlik mortaliteyi öngörmede en yüksek ayırt edici gücü gösterdi ve c-istatistik değeri 0.897 (95% GA: 0.881–0.911) idi. rSIGCS de iyi bir performans sergiledi; c-istatistik değeri 0.843 (95% GA: 0.824–0.860) idi. REMS ile rSIGCS arasında istatistiksel olarak anlamlı bir fark gözlenmedi (p = 0.216, DeLong testi), bu da her iki skorlama sisteminin de prehospital ortamda erken mortalite öngörüsü açısından etkili araçlar olabileceğini göstermektedir. Sonuç: Bu çalışma, REMS ve rSIGCS’nin ambulansla acil servise taşınan travma dışı hastalarda erken mortaliteyi öngörmede etkili araçlar olduğunu ortaya koymuştur.

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Cite This Article

Şirin, İ., Arı, E. (2025). Predicting Mortality in Ambulance-Transported Emergency Department Patients: A Comparative Retrospective Cohort Study. Eskisehir Medical Journal, Volume: 6 Issue: 2. https://ajindex.com/articles/1614264

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