Several unusual manifestations such as white bile draining in common bile duct (14 cases) and casual massive bleeding (2 cases ) during and following hepatobiliary and pancreatic operations is reported. These manifestations were in fact signs of hepatic insufficiency. The manners of manifestations of hepatic insufficiency and their treatment are discussed, with a stress that liver-protective treatment and nutritional support are the fundamental modalities.
【摘要】 目的 報道1例靜脈滴注胺碘酮致肝腎功能不全患者。 方法 2010年10月收治1例擴張性心肌病患者，治療過程中使用胺碘酮注射液，導致嚴重的肝腎功能不全。系統查閱中國期刊全文數據庫及外文數據庫Pubmed、Embase建庫至2011年8月關于胺碘酮致肝腎功能不全的相關文獻，進行靜脈胺碘酮致肝腎功能不全的可能性評估，探索胺碘酮靜脈滴注致肝功能不全的的作用機制。 結果 根據查閱文獻結果分析，此患者靜脈注射胺碘酮致肝功不全的可能性高，Naranjo概率評分分別為7分。 結論 提出臨床醫師和臨床藥師應進行胺碘酮靜脈的藥學監護，高度的重視胺碘酮相關的不良反應，從而及時識別和防治胺碘酮所致肝腎功能不全，減少其不良預后。【Abstract】 Objective To report a case of hepatic and renal insufficiency induced by intravenous injection with amiodarone, and to evaluate the possibility of the adverse drug reaction. Methods A patient with dilated cardiomyopathy was admitted in October, 2010. During the procedure, the use of amiodarone hydrochloride injection made the patient suffer from liver and kidney dysfunction. We retrieved the literatures about liver and kidney toxicity of amiodarone from CNKI, Pubmed, and Embase (from the establishment of the databases to November 2011). We also ssessed the possibility of the adverse drug reaction, discussed the mechanism of amiodarone-induced hepatic insufficiency. Results According to the literature, There was a great possibility of hepatic insufficiency induced by amiodarone, and the total score of the Naranjo probability score was 7. Conclusion It is important to pay more attention to the pharmaceutical care of amidarone to timely recognize and effectively prevent or treat hepatic and renal insufficiency induced by intravenous injection with amiodarone.
ObjectiveTo develop and validate a prediction model for postoperative hepatic dysfunction after Stanford type A aortic dissection (TAAD), providing a reference for early identification and intervention. MethodsWe retrospectively enrolled the patients with TAAD who underwent surgical treatment at Renmin Hospital of Wuhan University from August 2022 to August 2025 and at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from December 2022 to June 2025. The dataset was randomly divided into a training set and a validation set at a ratio of 7.5 : 2.5. Independent predictors were identified using univariate analysis and multivariate logistic regression. Predictive models were developed using logistic regression (LR), random forest (RF), and extreme gradient boosting (XGBoost). Model performance was assessed using receiver operating characteristic (ROC) curves, DeLong tests, calibration curves, and decision curve analysis (DCA). A nomogram was constructed based on the optimal model. ResultsA total of 482 patients were included, comprising 368 males and 114 females, with a median age of 54 (45, 62) years. Among them, 214 (44.4%) patients developed postoperative hepatic dysfunction. Multivariable analysis identified five independent predictors: preoperative serum creatinine level, pericardial effusion, postoperative mechanical ventilation duration, procalcitonin, and total bilirubin (all P<0.05). In the validation cohort, the area under the curve (AUC) values of the LR, RF, and XGBoost models were 0.741, 0.725, and 0.712, respectively, with the LR model demonstrating the best overall performance. The DeLong test showed no significant difference in AUC among the three models (P>0.05). Calibration curves demonstrated better agreement for the LR model. The DCA indicated that the LR model provided greater net benefit across a wider range of threshold probabilities. ConclusionMachine learning models do not outperform traditional LR in predicting postoperative hepatic dysfunction after TAAD. The LR model demonstrats more stable predictive performance and greater clinical utility. The nomogram developed based on this model may provide a reference for individualized clinical risk assessment.