Machine learning-enhanced preoperative assessment of spontaneous ventilation risk in diverse video-assisted...

Despite its widespread use, spontaneous ventilation can lead to intraoperative hypoxemia or hypercapnia. In this retrospective study, we developed and validated a preoperative clinical data-based model to predict intraoperative hypoxemia or hypercapnia risk during spontaneous ventilation video-assisted thoracoscopic surgery.

We enrolled patients who underwent spontaneous ventilation video-assisted thoracoscopic surgery at the National Respiratory Medicine Center of First Affiliated Hospital of Guangzhou Medical University between 2011 and 2023. Four machine learning algorithms-light gradient boosting machine, category boosting, extreme gradient boosting, and random forest-were trained and combined into a weighted ensemble to predict intraoperative hypoxemia (peripheral oxygen saturation <94%) or hypercapnia (partial pressure of end-tidal carbon dioxide >80 mm Hg).

Among 6590 included patients, 12.6% and 3.8% developed intraoperative hypoxemia and severe hypercapnia, respectively. The final risk assessment model achieved an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.68-0.76) and an area under the precision-recall curve of 0.35 (95% CI, 0.29-0.42). The statistical analysis of the data and the risk interpretation from the ensemble machine learning algorithm consistently identified body mass index (23.6 [21.6-25.5] vs 22.2 [20.4-24.0] kg/m²) and age (55 [46-62] vs 50 [41-58] years) as the strongest patient-related predictors positively correlated with intraoperative hypoxemia and severe hypercapnia. Segmentectomy (22.4% vs 14.7%), lobectomy (21.9% vs 17.2%), and surgical location in the right lung (86.4% vs 73.8%) increased risk of intraoperative hypoxia and hypercapnia. Analysis of postoperative hospital stay (3.67 vs 3.49 days), chest tube drainage (1.59 vs 1.47 days), complications (88.1 vs 91%), and incidence of intensive care unit (8.2 vs 7.6%) demonstrated that intraoperative hypoxia and hypercapnia can adversely affect patient postoperative recovery (P < .05).

The predictive model based on preoperative clinical characteristics effectively assessed intraoperative hypoxemia and severe hypercapnia risk in diverse spontaneous ventilation video-assisted thoracoscopic surgery procedures. This model can systematically guide preoperative evaluation to select appropriate patients and improve the intraoperative safety and surgical outcomes of spontaneous ventilation video-assisted thoracoscopic surgery.