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      A multicentre outcome analysis to define global benchmarks for donation after circulatory death liver transplantation

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      Journal of Hepatology
      Elsevier BV

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          Classification of Surgical Complications

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            The comprehensive complication index: a novel continuous scale to measure surgical morbidity.

            To develop and validate a comprehensive complication index (CCI) that integrates all events with their respective severity. Reporting of surgical complications is inconsistent and often incomplete. Most studies fail to provide information about the severity of complications, or inform only on the most severe event, ignoring events of lesser severity. We used an established classification of complications, adopting methods from operation risk index analysis in marketing research to develop a formula that considers all complications that may occur in a patient. The weights of each grade of complication, defined as median reference values, were obtained from 472 participants, who rated 30 different complications. Validation to assess sensitivity to treatment effects and validity of the CCI was performed by 4 different approaches, based on 1299 patients. The CCI is calculated as the sum of all complications that are weighted for their severity (multiplication of the median reference values from patients and physicians). The final formula yields a continuous scale to rank the severity of any combination of complications from 0 to 100 in a single patient. The CCI was highly sensitive in detecting treatment effect differences in the context of a randomized trial (effect size detected by CCI vs conventional standardized morbidity outcomes). It also showed a negative correlation with postoperative health status (r = -0.24, P = 0.002), and high correlation with the results of patient-rated single and multiple complications on conjoint analysis (r = 0.94, P < 0.001). The CCI summarizes all postoperative complications and is more sensitive than existing morbidity endpoints. It may serve as a standardized and widely applicable primary endpoint in surgical trials and other interventional fields of medicine. The CCI can be readily computed on the basis of tabulated complications according to the Clavien-Dindo classification (available at www.assessurgery.com).
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              Model for end-stage liver disease (MELD) and allocation of donor livers.

              A consensus has been reached that liver donor allocation should be based primarily on liver disease severity and that waiting time should not be a major determining factor. Our aim was to assess the capability of the Model for End-Stage Liver Disease (MELD) score to correctly rank potential liver recipients according to their severity of liver disease and mortality risk on the OPTN liver waiting list. The MELD model predicts liver disease severity based on serum creatinine, serum total bilirubin, and INR and has been shown to be useful in predicting mortality in patients with compensated and decompensated cirrhosis. In this study, we prospectively applied the MELD score to estimate 3-month mortality to 3437 adult liver transplant candidates with chronic liver disease who were added to the OPTN waiting list at 2A or 2B status between November, 1999, and December, 2001. In this study cohort with chronic liver disease, 412 (12%) died during the 3-month follow-up period. Waiting list mortality increased directly in proportion to the listing MELD score. Patients having a MELD score or =40 had a mortality rate of 71.3%. Using the c-statistic with 3-month mortality as the end point, the area under the receiver operating characteristic (ROC) curve for the MELD score was 0.83 compared with 0.76 for the Child-Turcotte-Pugh (CTP) score (P < 0.001). These data suggest that the MELD score is able to accurately predict 3-month mortality among patients with chronic liver disease on the liver waiting list and can be applied for allocation of donor livers.
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                Journal
                Journal of Hepatology
                Journal of Hepatology
                Elsevier BV
                01688278
                February 2022
                February 2022
                : 76
                : 2
                : 371-382
                Article
                10.1016/j.jhep.2021.10.004
                34655663
                6d6a1ffa-4f01-4d38-9709-cf6046bb7366
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

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