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A Multidimensional Approach of Surgical Mortality Assessment and Stratification (Smatt Score).
Sara Cutti1, Catherine Klersy2, Valentina Favalli3
1Medical Direction, Foundation IRCCS San Matteo Hospital, Viale Golgi 19, 27100, Pavia, Italy.
Scientific Reports
|July 5, 2020
Summary
This study identified key predictors for surgical mortality, developing the SMATT score to personalize patient risk stratification. The SMATT score accurately predicts mortality, improving surgical outcome assessment.
Area of Science:
- Surgical outcomes research
- Clinical risk prediction modeling
- Health services research
Background:
- Surgical mortality is a critical metric for healthcare quality.
- Accurate prediction of surgical risk is essential for patient care and resource allocation.
- Existing risk stratification methods may not fully capture the complexity of surgical outcomes.
Purpose of the Study:
- To assess 30-day surgical mortality.
- To identify predictors for personalized risk stratification in elective and emergency surgery.
- To develop and validate a novel risk score for surgical mortality.
Main Methods:
- Retrospective observational cohort study (2002-2014) at a multi-disciplinary hospital.
- Analysis of patient data including demographics, comorbidities, and surgical factors.
- Development of the Surgical Mortality Assessment Tool (SMATT) score using multivariable logistic regression.
Main Results:
- Overall in-hospital mortality was 1.89%.
- Key predictors identified include age, BMI, ASA score, surgical priority, and comorbidities.
- The SMATT score demonstrated high discrimination (AUC-ROC 0.945) and accuracy in predicting mortality.
Conclusions:
- The SMATT score accurately predicts surgical mortality based on preoperative and intraoperative factors.
- This novel score enhances personalized risk stratification for surgical patients.
- The SMATT score offers dynamic risk information, particularly valuable in reoperative surgery.
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