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Risk factors for prolonged air leak after uniportal anatomical segmentectomy†
Konstantinos Gioutsos1, Olga Rieder1, Michail Galanis1
1Department of Thoracic Surgery, Inselspital, University Hospital Bern, Bern, Switzerland.
Summary
Prolonged air leak (PAL) affects 15.3% of patients after single-port pulmonary segmentectomy. Risk factors include upper lobe location, low BMI, and comorbidities like hypertension and diabetes.
Area of Science:
- Thoracic Surgery
- Minimally Invasive Procedures
- Pulmonary Medicine
Background:
- Minimally invasive single-port pulmonary segmentectomy is increasingly used.
- Prolonged air leak (PAL) is a common complication following pulmonary resections.
- Identifying risk factors for PAL is crucial for improving patient outcomes.
Purpose of the Study:
- To determine the incidence of prolonged air leak (PAL) after single-port pulmonary segmentectomy.
- To identify risk factors associated with PAL in this patient cohort.
Main Methods:
- Retrospective analysis of 575 uniportal segmentectomies performed between March 2015 and September 2023.
- Univariable, multivariable logistic regression, and machine learning analyses were employed.
- PAL was defined as air leak lasting longer than 5 days.
Main Results:
- The incidence of PAL was 15.3% (88/575 patients).
- Multivariable analysis identified upper lobe location, lower body mass index (BMI), additional wedge resection, and hypertension as significant risk factors for PAL.
- Machine learning models predicted PAL with 70% accuracy, highlighting factors like segment 2 resection, diabetes, inhaler use, squamous cell carcinoma, diffusing capacity of the lungs for carbon monoxide (DLCO%), pack-years, forced expiratory volume in one second (FEV1%), and surgery time.
Conclusions:
- Several factors are associated with an increased risk of PAL after uniportal segmentectomy.
- These include patient-related factors (low BMI, low DLCO%/FEV1%, pack-years, diabetes, hypertension), surgical factors (upper lobe location, additional wedge resection, segment 2 removal, longer surgery time), and histology (squamous cell carcinoma).
- Predictive models using machine learning show promise in identifying patients at high risk for PAL.
