A clinical prediction model for prolonged air leak after pulmonary resection

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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 < .001). Final model variables associated with increased risk included low percent forced expiratory volume in 1 second, smoking history, bilobectomy, higher annual surgeon caseload, previous chest surgery, Zubrod score >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 < .001). Patients at intermediate and high risk were 4.80 times (95% CI, 2.86-8.07) and 11.86 times (95% CI, 7.21-19.52) more likely to have prolonged air leak compared with patients at low risk.

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.

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