Abstract

The aim of this study was to identify independent predictors of hospital readmission for patients undergoing lobectomy for lung cancer. Hospital readmission after lobectomy is associated with increased mortality. Greater than 80% of the variability associated with readmission after surgery is at the patient level. This underscores the importance of using a data source that includes detailed clinical information. Using the Society of Thoracic Surgeons (STS) General Thoracic Surgery Database (GTSD), we conducted a retrospective cohort study of patients undergoing elective lobectomy for lung cancer. Three separate multivariable logistic regression models were generated: the first included preoperative variables, the second added intraoperative variables, and the third added postoperative variables. The c statistic was calculated for each model. There were 39,734 patients from 277 centers. The 30-day readmission rate was 8.2% (n = 3237). In the final model, postoperative complications had the greatest effect on readmission. Pulmonary embolus {odds ratio [OR] 12.34 [95% confidence interval (CI),7.94-19.18]} and empyema, [OR 11.66 (95% CI, 7.31-18.63)] were associated with the greatest odds of readmission, followed by pleural effusion [OR 7.52 (95% CI, 6.01-9.41)], pneumothorax [OR 5.08 (95% CI, 4.16-6.20)], central neurologic event [OR 3.67 (95% CI, 2.23-6.04)], pneumonia [OR 3.13 (95% CI, 2.43-4.05)], and myocardial infarction [OR 3.16 (95% CI, 1.71-5.82)]. The c statistic for the final model was 0.736. Complications are the main driver of readmission after lobectomy for lung cancer. The highest risk was related to postoperative events requiring a procedure or medical therapy necessitating inpatient care.

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