A Nomogram for Preoperative Prediction of Prolonged Air Leak After Pulmonary Malignancy Resection

Overview

Journal Transl Lung Cancer Res

Date 2021 Sep 29

PMID 34584861

Citations 10

Authors

Runsen Jin

Yuyan Zheng

Taotao Gao

Yajie Zhang

Bingshun Wang

Junbiao Hang

Hecheng Li

Affiliations

Soon will be listed here.

Abstract

Background: Prolonged air leak (PAL) is one of the most common postoperative complications after lung surgery. This study aimed to identify risk factors of PAL after lung resection and develop a preoperative predictive model to estimate its risk for individual patients.

Methods: Patients with pulmonary malignancies or metastasis who underwent pulmonary resection between January 2014 and January 2018 were included. PAL was defined as an air leak more than 5 days after surgery, risk factors were analyzed. Forward stepwise multivariable logistic regression analysis was performed to identify independent risk factors, and a derived nomogram was built. Data from February 2018 to September 2018 were collected for internal validation.

Results: A total of 1,511 patients who met study criteria were enrolled in this study. The overall incidence of PAL was 9.07% (137/1,511). Age, percent forced expiratory volume in 1 second, surgical type, surgical approach and smoking history were included in the final model. A nomogram was developed according to the multivariable logistic regression results. The C-index of the predictive model was 0.70, and the internal validation value was 0.77. The goodness-of-fit test was non-significant for model development and internal validation.

Conclusions: The predictive model and derived nomogram achieved satisfied preoperative prediction of PAL. Using this nomogram, the risk for an individual patient can be estimated, and preventive measures can be applied to high-risk patients.

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