OBJECTIVE: To investigate the independent risk factors for catheter-related complications after PTBD in patients with malignant obstructive jaundice, and to construct a risk prediction model to provide evidence for clinical prevention and intervention strategies. METHODS: This retrospective study included 337 patients with malignant obstructive jaundice who underwent ultrasound-guided PTBD at our hospital between January 2024 and December 2025. We collected demographic data, preoperative laboratory indices, intraoperative parameters, and postoperative complications. Univariate and multivariate logistic regression analyses identified independent risk factors for postoperative infection and bleeding. Prediction models were constructed and evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS: Among the 337 patients with malignant obstructive jaundice, the incidence of postoperative infection was 7.4%, and the incidence of postoperative bleeding was 9.5%. Multivariate analysis showed that independent risk factors for postoperative infection included ascites, multiple punctures, elevated preoperative neutrophil count, and decreased preoperative hemoglobin levels. Positive HBV DNA status and diuretic use showed unexpected inverse associations. Independent risk factors for postoperative bleeding were decreased preoperative hemoglobin and decreased preoperative prealbumin levels. ROC curve analysis demonstrated that the infection prediction model incorporating the six above-mentioned factors yielded an AUC of 0.825 (95% CI: 0.750-0.900), while the bleeding prediction model combining hemoglobin and prealbumin achieved an AUC of 0.866 (95% CI: 0.810-0.922), indicating good predictive performance for both models. CONCLUSIONS: Ascites, multiple punctures, elevated preoperative neutrophil count, and low preoperative hemoglobin level are independent risk factors for post-PTBD infection, whereas low preoperative hemoglobin and low prealbumin levels are independent risk factors for post-PTBD bleeding. The risk prediction models based on these factors demonstrate good discriminative ability and may help identify high‑risk patients preoperatively, guide targeted preventive strategies, reduce complication rates, and improve the safety of PTBD.
Wang et al. (Thu,) studied this question.
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