Hepatectomy is still the major curative treatment for patients with liver malignancies.However,it is still a big challenge to remove the tumors in the central posterior area,especially if their location involves the r...Hepatectomy is still the major curative treatment for patients with liver malignancies.However,it is still a big challenge to remove the tumors in the central posterior area,especially if their location involves the retrohepatic inferior vena cava and hepatic veins.Ex vivo liver resection and auto-transplantation(ELRA),a hybrid technique of the traditional liver resection and transplantation,has brought new hope to these patients and therefore becomes a valid alternative to liver transplantation.Due to its technical difficulty,ELRA is still concentrated in a few hepatobiliary centers that have experienced surgeons in both liver resection and liver transplantation.The efficacy and safety of this technique has already been demonstrated in the treatment of benign liver diseases,especially in the advanced alveolar echinococcosis.Recently,the application of ELRA for liver malignances has gained more attention.However,standardization of clinical practice norms and international consensus are still lacking.The prognostic impact in these oncologic patients also needs further evaluation.In this review,we summarized the principles and recent progresses on ELRA.展开更多
BACKGROUND Due to the complexity and numerous comorbidities associated with Crohn’s disease(CD),the incidence of postoperative complications is high,significantly impacting the recovery and prognosis of patients.Cons...BACKGROUND Due to the complexity and numerous comorbidities associated with Crohn’s disease(CD),the incidence of postoperative complications is high,significantly impacting the recovery and prognosis of patients.Consequently,additional stu-dies are required to precisely predict short-term major complications following intestinal resection(IR),aiding surgical decision-making and optimizing patient care.AIM To construct novel models based on machine learning(ML)to predict short-term major postoperative complications in patients with CD following IR.METHODS A retrospective analysis was performed on clinical data derived from a patient cohort that underwent IR for CD from January 2017 to December 2022.The study participants were randomly allocated to either a training cohort or a validation cohort.The logistic regression and random forest(RF)were applied to construct models in the training cohort,with model discrimination evaluated using the area under the curves(AUC).The validation cohort assessed the performance of the constructed models.RESULTS Out of the 259 patients encompassed in the study,5.0%encountered major postoperative complications(Clavien-Dindo≥III)within 30 d following IR for CD.The AUC for the logistic model was 0.916,significantly lower than the AUC of 0.965 for the RF model.The logistic model incorporated a preoperative CD activity index(CDAI)of≥220,a diminished preoperative serum albumin level,conversion to laparotomy surgery,and an extended operation time.A nomogram for the logistic model was plotted.Except for the surgical approach,the other three variables ranked among the top four important variables in the novel ML model.CONCLUSION Both the nomogram and RF exhibited good performance in predicting short-term major postoperative complic-ations in patients with CD,with the RF model showing more superiority.A preoperative CDAI of≥220,a di-minished preoperative serum albumin level,and an extended operation time might be the most crucial variables.The findings of this study can assist clinicians in identifying patients at a higher risk for complications and offering personalized perioperative management to enhance patient outcomes.展开更多
文摘Hepatectomy is still the major curative treatment for patients with liver malignancies.However,it is still a big challenge to remove the tumors in the central posterior area,especially if their location involves the retrohepatic inferior vena cava and hepatic veins.Ex vivo liver resection and auto-transplantation(ELRA),a hybrid technique of the traditional liver resection and transplantation,has brought new hope to these patients and therefore becomes a valid alternative to liver transplantation.Due to its technical difficulty,ELRA is still concentrated in a few hepatobiliary centers that have experienced surgeons in both liver resection and liver transplantation.The efficacy and safety of this technique has already been demonstrated in the treatment of benign liver diseases,especially in the advanced alveolar echinococcosis.Recently,the application of ELRA for liver malignances has gained more attention.However,standardization of clinical practice norms and international consensus are still lacking.The prognostic impact in these oncologic patients also needs further evaluation.In this review,we summarized the principles and recent progresses on ELRA.
基金Supported by Horizontal Project of Shanghai Tenth People’s Hospital,No.DS05!06!22016 and No.DS05!06!22017.
文摘BACKGROUND Due to the complexity and numerous comorbidities associated with Crohn’s disease(CD),the incidence of postoperative complications is high,significantly impacting the recovery and prognosis of patients.Consequently,additional stu-dies are required to precisely predict short-term major complications following intestinal resection(IR),aiding surgical decision-making and optimizing patient care.AIM To construct novel models based on machine learning(ML)to predict short-term major postoperative complications in patients with CD following IR.METHODS A retrospective analysis was performed on clinical data derived from a patient cohort that underwent IR for CD from January 2017 to December 2022.The study participants were randomly allocated to either a training cohort or a validation cohort.The logistic regression and random forest(RF)were applied to construct models in the training cohort,with model discrimination evaluated using the area under the curves(AUC).The validation cohort assessed the performance of the constructed models.RESULTS Out of the 259 patients encompassed in the study,5.0%encountered major postoperative complications(Clavien-Dindo≥III)within 30 d following IR for CD.The AUC for the logistic model was 0.916,significantly lower than the AUC of 0.965 for the RF model.The logistic model incorporated a preoperative CD activity index(CDAI)of≥220,a diminished preoperative serum albumin level,conversion to laparotomy surgery,and an extended operation time.A nomogram for the logistic model was plotted.Except for the surgical approach,the other three variables ranked among the top four important variables in the novel ML model.CONCLUSION Both the nomogram and RF exhibited good performance in predicting short-term major postoperative complic-ations in patients with CD,with the RF model showing more superiority.A preoperative CDAI of≥220,a di-minished preoperative serum albumin level,and an extended operation time might be the most crucial variables.The findings of this study can assist clinicians in identifying patients at a higher risk for complications and offering personalized perioperative management to enhance patient outcomes.
