OBJECTIVES: Our aim was to investigate the incidence and risk factors for prolonged air leak (PAL) in patients undergoing minimally invasive single-port pulmonary segmentectomy. METHODS: A retrospective analysis of all patients undergoing uniportal segmentectomy in our department from March 2015 to September 2023 was performed. Univariable, multivariable logistic regression analyses and machine learning were used to investigate risk factors for PAL (>
5 days). RESULTS: In total, 575 segmentectomies were performed using uniportal video-assisted thoracoscopic surgery. In total, 333 patients (57.9%) were men, and the mean age was 64.8 years. PAL occurred in 88 patients (15.3%). Length of stay and duration of chest drainage were 8.6 (SD: 4.86) and 10.6 (SD: 8.12) days in the subgroup with PAL, compared to 3.6 (SD: 2.25) and 2.0 (SD: 1.3) days in the subgroup without air leak (P <
0.0001). Multivariable analysis revealed that upper lobe location, lower body mass index (BMI), an additional wedge resection on another segment and hypertension were associated with increased risk of PAL. Machine learning was used to develop models that predicted the occurrence of PAL with an accuracy of 70%. The first model detected the following parameters as significant: resection of segment 2, diabetes, inhalers, and squamous cell carcinoma. The second model recognized diffusing capacity of the lungs for carbon monoxide (DLCO%), pack-years, forced expiratory volume in one second (FEV1%) and surgery time, respectively. CONCLUSIONS: Low BMI, DLCO% or FEV1% values, increased pack-years, inhalers, diabetes, hypertension, histology of primary lung cancer, longer surgery time, an additional wedge resection, segment 2 removal and upper lobe surgery were identified as risk factors for PAL.