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 < .001). Final mod

SUBMITTER: Attaar A 

PROVIDER: S-EPMC5651171 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature