Predictive Value of Early Postoperative CT Imaging Parameters for Major Complications Following Thoracoscopic Segmentectomy.

AIM: This study aimed to systematically evaluate the independent predictive value and diagnostic performance of quantitative indices derived from early postoperative computed tomography (CT) imaging for predicting major complications (Clavien-Dindo grade ≥II) within 30 days after pulmonary segmentectomy.

METHODS

A total of 231 patients who underwent Video-Assisted Thoracoscopic Surgery (VATS) segmentectomy were retrospectively enrolled. On CT images obtained within 2-3 days postoperatively, the depth of pleural effusion, pneumothorax rate, lung re-expansion ratio, and maximum subcutaneous air thickness were measured. The primary outcome was the occurrence of Clavien-Dindo grade ≥II complications within 30 days. Univariate and multivariate logistic regression analyses were performed, and predictive performance was evaluated using the area under the curve (AUC).

RESULTS

Major complications occurred in 42 patients (18.2%). Multivariate analysis identified depth of pleural effusion (odds ratio [OR] = 1.213, 95% confidence interval [CI]: 1.107-1.329, p < 0.001), pneumothorax rate (OR = 1.201, 95% CI: 1.081-1.333, p < 0.001), lung re-expansion ratio (OR = 0.872, 95% CI: 0.809-0.940, p < 0.001), and maximum subcutaneous air thickness (OR = 1.438, 95% CI: 1.248-1.656, p < 0.001) as independent predictors. Receiver operating characteristic (ROC) analysis demonstrated that maximum subcutaneous air thickness had the highest predictive performance (AUC = 0.850), followed by pneumothorax rate (AUC = 0.831), lung re-expansion ratio (AUC = 0.785), and depth of pleural effusion (AUC = 0.783).

CONCLUSIONS

Quantitative indices derived from early postoperative CT scans may serve as reliable imaging biomarkers for predicting major complications after pulmonary segmentectomy, thereby facilitating early identification of high-risk patients and guiding individualized postoperative management.