Annals of vascular surgery · 2026
Admission-Based Early Risk Stratification for In-Hospital Mortality in Ruptured Abdominal Aortic Aneurysm: A Pragmatic Clinical Model.
СтатьяНаблюдательное исследованиеВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Del Río-Solá M A Lourdes, Jimenez-Caja Marina, Torre-Casaseca Clara de la, Alvarez-Garcia Eva, García-Padron Carlos, Flota-Ruiz Cintia
Аннотация
BACKGROUND: To develop and internally validate a pragmatic, admission-based prediction model for in-hospital mortality in patients presenting with ruptured abdominal aortic aneurysm (rAAA), and to assess its performance, calibration, and clinical utility for early risk stratification.
METHODS: This retrospective observational cohort study included consecutive adult patients admitted with rAAA to a tertiary referral university hospital between January 2015 and December 2024. Only variables available at the time of hospital admission were analyzed. Univariable and multivariable logistic regression were used to identify independent predictors of in-hospital mortality. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC), calibration using calibration plots and the Brier score, and internal validation using bootstrap resampling. Clinical utility was evaluated with decision curve analysis.
RESULTS: A total of 334 patients with rAAA were included. Overall in-hospital mortality was 65.9% (220/334). Age was independently associated with mortality (adjusted odds ratio [aOR] 1.06 per year), while higher admission hemoglobin levels were protective (aOR 0.73 per-g/dL). Hemodynamic stability at presentation was the strongest independent predictor of survival (aOR 0.24). The admission-based model demonstrated reliable discrimination (AUC 0.74) with good calibration (Brier score 0.19) and minimal optimism after internal validation (optimism-corrected AUC 0.73). Decision curve analysis showed a net clinical benefit across a wide range of clinically relevant threshold probabilities. A simplified admission-based risk score stratified patients into low-, intermediate-, and high-risk groups with observed in-hospital mortality of approximately 11%, 49%, and 77%, respectively.
CONCLUSION: An admission-based model using readily available clinical variables provides reliable early prediction of in-hospital mortality in patients with rAAA. By prioritizing simplicity and bedside applicability, this approach may support early risk stratification and decision-making in emergency vascular surgery.
METHODS: This retrospective observational cohort study included consecutive adult patients admitted with rAAA to a tertiary referral university hospital between January 2015 and December 2024. Only variables available at the time of hospital admission were analyzed. Univariable and multivariable logistic regression were used to identify independent predictors of in-hospital mortality. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC), calibration using calibration plots and the Brier score, and internal validation using bootstrap resampling. Clinical utility was evaluated with decision curve analysis.
RESULTS: A total of 334 patients with rAAA were included. Overall in-hospital mortality was 65.9% (220/334). Age was independently associated with mortality (adjusted odds ratio [aOR] 1.06 per year), while higher admission hemoglobin levels were protective (aOR 0.73 per-g/dL). Hemodynamic stability at presentation was the strongest independent predictor of survival (aOR 0.24). The admission-based model demonstrated reliable discrimination (AUC 0.74) with good calibration (Brier score 0.19) and minimal optimism after internal validation (optimism-corrected AUC 0.73). Decision curve analysis showed a net clinical benefit across a wide range of clinically relevant threshold probabilities. A simplified admission-based risk score stratified patients into low-, intermediate-, and high-risk groups with observed in-hospital mortality of approximately 11%, 49%, and 77%, respectively.
CONCLUSION: An admission-based model using readily available clinical variables provides reliable early prediction of in-hospital mortality in patients with rAAA. By prioritizing simplicity and bedside applicability, this approach may support early risk stratification and decision-making in emergency vascular surgery.