Development and validation of a nomogram for predicting postoperative atrial fibrillation in trauma patients admitted to the ICU.

BACKGROUND

Postoperative atrial fibrillation (POAF) in trauma patients is closely related to poor prognosis. This study aims to identify the risk factors of POAF and establish a predictive model.

METHODS

We extracted data from the MIMIC-IV 2.2 database on ICU trauma patients who underwent surgery. The patients were randomly divided into a training set and a validation set at a ratio of 7:3. We used least absolute shrinkage and selection operator (LASSO) regression combined with multivariable logistic regression to select predictive factors. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves were used to evaluate the developed nomogram model.

RESULTS

Among 5170 included patients, POAF incidence was 9.15%. POAF was associated with significantly postoperative higher mortality at 7 days, 28 days, and 1 year, as well as prolonged hospital stays and ICU stays. Independent predictors of POAF included age (OR 1.06, 95% CI 1.04-1.07, P < 0.001), congestive heart failure history (CHF) (OR 1.85, 95% CI 1.35-2.54, P < 0.001), sequential organ failure assessment (SOFA) score on the first ICU day (OR 1.09, 95% CI 1.03-1.16, P = 0.002), and epinephrine use on the day of surgery (OR 1.95, 95% CI 1.14-3.28, P = 0.013). The nomogram, developed from age, CHF history, and ICU SOFA score, showed an area under the curve (AUC) of 0.791 (95% CI 0.768-0.814) in training set and 0.800 (95% CI 0.763-0.836) in validation set.

CONCLUSION

POAF significantly worsens outcomes in trauma patients. The developed nomogram provides effective risk stratification for early identification and clinical decision-making.

HIGHLIGHTS: POAF incidence was 9.15% and predicted higher mortality in trauma patients. A novel nomogram was developed using age, congestive heart failure history, and SOFA score. The model showed good predictive performance with an AUC of 0.800 upon validation. This tool aids in early risk stratification for POAF to guide clinical management.