ArticleLangenbeck's archives of surgery2025
Risk factors and predictive model for postoperative pulmonary complications following pancreaticoduodenectomy: a retrospective cohort study.
Article in Langenbeck's archives of surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Elevated Liver Enzymes Can Predict Complications Early After Pancreatic Resection.Journal of clinical medicine · 2026Article
- A machine learning-based predictive model for postoperative pulmonary complications in lung cancer and its SHAP interpretation.Frontiers in oncology · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPostoperative pulmonary complications (PPCs) can significantly reduce quality of life and may be life-threatening. While predictors of PPCs have been studied in various surgeries, specific data on pancreaticoduodenectomy is limited.
methodsWe conducted a retrospective analysis of 338 patients who underwent pancreaticoduodenectomy for biliary, pancreatic, and duodenal tumors at our hospital from 2017 to 2023. We compared demographic, clinical, and laboratory variables between patients with and without PPCs within 30 days post-surgery. Independent risk factors were identified using multivariate logistic regression analysis, and a nomogram was developed to predict PPC risk. Model accuracy was validated with the concordance index (C-index) and calibration curves.
resultsOf the 338 patients, 149 (44.1%) developed PPCs. Significant variables associated with PPCs included age, smoking, alcohol consumption, type and duration of surgery, timing of nasogastric tube removal, tumor size, tumor location, and preoperative albumin levels. Multivariate logistic regression analysis identified independent risk factors: type and duration of surgery, tumor location, maximum tumor diameter, and preoperative albumin levels. The nomogram incorporating these factors had a C-index of 0.749. The ROC curve showed an AUC of 0.75, indicating satisfactory predictive performance. Calibration curves, decision curve analysis (DCA), and clinical impact curves confirmed the model's validity and reliability.
conclusionType and duration of surgery, tumor location, maximum tumor diameter, and preoperative albumin levels are independent risk factors for PPCs after pancreaticoduodenectomy. We developed a new nomogram to predict PPCs in these patients.
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