A novel model for early prediction of in- hospital mortality in seawater drowning: the SNOP score
Dublin Core
Title
A novel model for early prediction of in- hospital mortality in seawater drowning: the SNOP score
Subject
Drowning, Hospital mortality, Seawater, Sodium, Oxygen saturation, Emergency medicine, Prognostic model
Description
Abstract
Background Drowning is a leading cause of preventable mortality worldwide; however, early in-hospital risk
stratification remains limited. Although tools such as the Szpilman score assist in early severity assessment, they may
not fully capture the evolving clinical status after admission. This study aimed to develop a simplified and objective
model based on readily available parameters to predict in-hospital mortality following seawater drowning.
Methods This retrospective study was conducted at a referral emergency department (ED) in northern Turkey
between July 1, 2011, and December 31, 2024. Of 190 patients initially included, 166 with complete clinical and
laboratory data were analyzed. Data were obtained from institutional and national health information systems.
Clinical, physiological, and biochemical variables were assessed. Predictors of in-hospital mortality were identified
using receiver operating characteristic (ROC) analysis and multivariable logistic regression. Variables with near-perfect
discrimination (e.g., GCS, pH, Szpilman score) were excluded to avoid overfitting.
Results Among the 166 patients, 34 (20.5%) died during hospitalization. CPR and endotracheal intubation rates
were significantly higher among non-survivors (CPR: 97.1% vs. 0%; intubation: 97.1% vs. 2.3%; both p<0.001). Non-
survivors also presented with lower GCS (median 3 vs. 15), lower arterial pH, and higher Szpilman scores (all p<0.001).
ROC analysis identified four potential predictors with AUC values between 0.90 and 0.95—pCO2, lactate, SpO2, and
sodium—all showing significant discriminatory capacity (p<0.001). These variables were entered into a binary logistic
regression model, from which serum sodium (OR=2.110; 95% CI: 1.310–3.401; p=0.002) and SpO2 (OR=0.902; 95%
CI: 0.847–0.961; p=0.001) emerged as independent predictors. These formed the basis of the SNOP score (Saturation
and Natremia-based Outcome Predictor), a two-parameter logistic model demonstrating excellent performance:
AUC=0.996, sensitivity=99.0%, specificity=96.2%, and overall accuracy=98.4%.
Conclusion: The SNOP score is a simple, ED-specific tool for early prediction of in-hospital mortality in seawater
drowning. It complements existing assessment systems by incorporating objective, admission-based parameters.
Prospective multicenter validation is warranted to confirm its clinical applicability and support broader
implementation.
Background Drowning is a leading cause of preventable mortality worldwide; however, early in-hospital risk
stratification remains limited. Although tools such as the Szpilman score assist in early severity assessment, they may
not fully capture the evolving clinical status after admission. This study aimed to develop a simplified and objective
model based on readily available parameters to predict in-hospital mortality following seawater drowning.
Methods This retrospective study was conducted at a referral emergency department (ED) in northern Turkey
between July 1, 2011, and December 31, 2024. Of 190 patients initially included, 166 with complete clinical and
laboratory data were analyzed. Data were obtained from institutional and national health information systems.
Clinical, physiological, and biochemical variables were assessed. Predictors of in-hospital mortality were identified
using receiver operating characteristic (ROC) analysis and multivariable logistic regression. Variables with near-perfect
discrimination (e.g., GCS, pH, Szpilman score) were excluded to avoid overfitting.
Results Among the 166 patients, 34 (20.5%) died during hospitalization. CPR and endotracheal intubation rates
were significantly higher among non-survivors (CPR: 97.1% vs. 0%; intubation: 97.1% vs. 2.3%; both p<0.001). Non-
survivors also presented with lower GCS (median 3 vs. 15), lower arterial pH, and higher Szpilman scores (all p<0.001).
ROC analysis identified four potential predictors with AUC values between 0.90 and 0.95—pCO2, lactate, SpO2, and
sodium—all showing significant discriminatory capacity (p<0.001). These variables were entered into a binary logistic
regression model, from which serum sodium (OR=2.110; 95% CI: 1.310–3.401; p=0.002) and SpO2 (OR=0.902; 95%
CI: 0.847–0.961; p=0.001) emerged as independent predictors. These formed the basis of the SNOP score (Saturation
and Natremia-based Outcome Predictor), a two-parameter logistic model demonstrating excellent performance:
AUC=0.996, sensitivity=99.0%, specificity=96.2%, and overall accuracy=98.4%.
Conclusion: The SNOP score is a simple, ED-specific tool for early prediction of in-hospital mortality in seawater
drowning. It complements existing assessment systems by incorporating objective, admission-based parameters.
Prospective multicenter validation is warranted to confirm its clinical applicability and support broader
implementation.
Creator
Kıvanç Öncü1* , Özhan Özcan2 , Şeyma Şi̇mşi̇rgi̇l Kara3 , Ayhan Parmaksız4 and Teoman Erşen5
Date
2025
Contributor
Peri Irawan
Format
pdf
Language
english
Type
text
Files
Collection
Citation
Kıvanç Öncü1* , Özhan Özcan2 , Şeyma Şi̇mşi̇rgi̇l Kara3 , Ayhan Parmaksız4 and Teoman Erşen5, “A novel model for early prediction of in- hospital mortality in seawater drowning: the SNOP score,” Repository Horizon University Indonesia, accessed April 20, 2026, https://repository.horizon.ac.id/items/show/13271.