Journal of Clinical Medicine
A Preoperative Risk-Prediction Model (SSPAL) for Prolonged Air Leak After Lobectomy for Lung Cancer: Development and Internal Validation
Par Yunus Türk, Necati Çıtak, Esra Yamansavcı Şirzai et 1 autres.
Contenu en anglais
Résumé
Background
Prolonged air leak (PAL) remains one of the most common complications following lobectomy for non-small-cell lung cancer (NSCLC), leading to prolonged hospitalization, increased healthcare costs, and delayed recovery. We aimed to develop and internally validate a practical model for predicting PAL after lobectomy.
Methods
This retrospective single-center cohort study included 905 consecutive patients who underwent lobectomy for NSCLC between 2017 and 2024. Patients were randomly allocated to derivation (n = 680) and internal validation (n = 225) cohorts (3:1). Candidate clinical, operative, and pathological variables were evaluated to identify predictors of PAL, and multivariable logistic regression was used to develop the Suat Seren Prolonged Air Leak (SSPAL) model. Model performance was assessed by discrimination (AUC) and calibration.