Key predictors of 30-day mortality in non-cardiac surgery: development, key risk factors, and calibration of a risk model
Year: 2026
Type: article
Study design: Observational Study
Abstract: Introduction Thirty-day mortality remains a critical indicator of perioperative safety and quality of care in patients undergoing non-cardiac surgery. Identifying predictive factors for 30-day mortality is critical for crisis mitigation and improving patient outcomes. This study aimed to identify key predictors of 30-day mortality in non-cardiac surgery patients and develop a predictive model to aid clinical decision-making. Methods This retrospective observational study analyzed data from patients aged ≥18 years who underwent non-cardiac surgery at a tertiary care hospital between January and August 2022. Data on demographics, comorbidities, intraoperative variables, and postoperative complications were collected. Multivariate logistic regression identified independent predictors of 30-day mortality, and a nomogram was constructed to facilitate individualized risk assessment. Results Among 7,528 patients, 76 (1.0%) died within 30 days. Independent predictors of mortality included preoperative ventilatory support (odds ratio [OR] 8.76; 95% confidence interval [CI]: 3.58–21.42; p < 0.001), postoperative sepsis (OR 5.86; 95% CI: 2.23–15.37; p < 0.001), coma (OR 18.56; 95% CI: 6.81–50.55; p < 0.001), myocardial infarction (OR 26.35; 95% CI: 4.46–155.63; p < 0.001), and cardiac arrest (OR 57.9; 95% CI: 18.22–184.05; p < 0.001). The nomogram demonstrated good calibration at lower risk levels, with slight overestimation at higher probabilities. The area under the receiver operating characteristic curve indicated excellent discrimination. Discussion The developed nomogram serves as a useful tool for perioperative risk stratification in non-cardiac surgery. Incorporating both preoperative and postoperative factors, aids in early identification of high-risk patients and supports targeted clinical interventions. External validation and refinement of the model are recommended for broader applicability.
Source: Frontiers in Medicine
Institution: Prince of Songkla University
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7126210216
