Abstract
BACKGROUND AND AIMS: Hepatectomy is currently the most effective way to treat liver diseases, and its safety has observably improved. However, the incidence of postoperative complications (POCs) remains high. Therefore, exploring the related influencing factors helps identify high-risk groups early and improve patient prognosis. METHODS: Clinical data were retrospectively collected from a real-world setting. Patients were divided into two groups based on the incidence of postoperative pulmonary complications (PPCs). Univariate analysis, LASSO regression, and logistic regression were applied to analyse the correlation between PPCs and perioperative indicators. A nomogram prediction model was constructed, whose discrimination, accuracy, and clinical effectiveness were evaluated. RESULTS: The incidence of PPCs was 36.33% among the 1244 patients in this study. The total length of hospital stay and perioperative mortality in the PPCs group were markedly higher (P < 0.001) than in the non-PPCs group. Logistic regression showed that surgical method [odds ratio (OR) =2.469 (95% CI: 1.665, 3.748); P < 0.001], duration of surgery [OR = 1.003 (95% CI: 1.002, 1.005); P < 0.001], postoperative patient destination [OR = 1.453 (95% CI: 1.115, 1.893); P = 0.006], and postoperative international normalised ratio (INR) [OR = 2.245 (95% CI: 1.287, 4.120); P = 0.007] were independent risk factors of PPCs; the number of clamping [OR = 0.988 (95% CI: 0.980, 0.995); P = 0.001] was an independent protective factor of PPCs. The area under the receiver operating characteristic (ROC) curve was 0.675 (95% CI: 0.638, 0.703), the consistency index of the calibration curve was 0.675 (95% CI: 0.641, 0.703), and the Hosmer-Lemeshow goodness-of-fit test yielded P = 0.327. CONCLUSIONS: In this study, the incidence of PPCs after hepatectomy was the highest. Our nomogram model can predict the probability of PPCs after hepatectomy.