A clinical prediction model for prolonged air leak after pulmonary resection

Abstract Objective Prolonged air leak increases costs and worsens outcomes after pulmonary resection. We aimed to develop a clinical prediction tool for prolonged air leak using pretreatment and intraoperative variables. Methods Patients who underwent pulmonary resection for lung cancer/nodules (from January 2009 to June 2014) were stratified by prolonged parenchymal air leak (>5 days). Using backward stepwise logistic regression with bootstrap resampling for internal validation, candidate variables were identified and a nomogram risk calculator was developed. Results A total of 2317 patients underwent pulmonary resection for lung cancer/nodules. Prolonged air leak (8.6%, n = 200) was associated with significantly longer hospital stay (median 10 vs 4 days; P 2, and interaction terms for right-sided thoracotomy and wedge resection by thoracotomy. Wedge resection, higher body mass index, and unmeasured percent forced expiratory volume in 1 second were protective. Derived nomogram discriminatory accuracy was 76% (95% confidence interval [CI], 0.72-0.79) and facilitated patient stratification into low-, intermediate- and high-risk groups with monotonic increase in observed prolonged air leaks (2.0%, 8.9%, and 19.2%, respectively; P Conclusions Using readily available candidate variables, our nomogram predicts increasing risk of prolonged air leak with good discriminatory ability. Risk stratification can support surgical decision making, and help initiate proactive, patient-specific surgical management.