A novel model for early prediction of in-hospital mortality in seawater drowning: the SNOP score

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dc.contributor.authorOncu, Kivanc
dc.contributor.authorOzcan, Ozhan
dc.contributor.authorKara, Seyma Simsirgil
dc.contributor.authorParmaksiz, Ayhan
dc.contributor.authorErsen, Teoman
dc.date.accessioned2026-04-25T14:20:16Z
dc.date.available2026-04-25T14:20:16Z
dc.date.issued2025
dc.departmentSinop Üniversitesi
dc.description.abstractBackground : 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-pCO(2), lactate, SpO(2), 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 SpO(2) (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.
dc.identifier.doi10.1186/s12245-025-00977-2
dc.identifier.issn1865-1372
dc.identifier.issn1865-1380
dc.identifier.issue1
dc.identifier.orcid0000-0001-9928-2383
dc.identifier.orcid0000-0001-6052-5640
dc.identifier.orcid0000-0001-6894-5631
dc.identifier.orcid0000-0003-1379-3161
dc.identifier.pmid41126051
dc.identifier.scopus2-s2.0-105019541652
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1186/s12245-025-00977-2
dc.identifier.urihttps://hdl.handle.net/11486/8476
dc.identifier.volume18
dc.identifier.wosWOS:001599029600001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherBmc
dc.relation.ispartofInternational Journal of Emergency Medicine
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20260420
dc.subjectDrowning
dc.subjectHospital mortality
dc.subjectSeawater
dc.subjectSodium
dc.subjectOxygen saturation
dc.subjectEmergency medicine
dc.subjectPrognostic model
dc.titleA novel model for early prediction of in-hospital mortality in seawater drowning: the SNOP score
dc.typeArticle

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