Abstract
OBJECTIVE: The aim of this study was to identify independent predictors of hospital readmission for patients undergoing lobectomy for lung cancer. SUMMARY BACKGROUND DATA: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.