The role of the comprehensive complication index for the prediction of survival after liver transplantation.
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ABSTRACT:
SUBMITTER: Lai Q
PROVIDER: S-EPMC7889667 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
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The role of the comprehensive complication index for the prediction of survival after liver transplantation.
Lai Quirino Q Melandro Fabio F Nowak Greg G Nicolini Daniele D Iesari Samuele S Fasolo Elisa E Mennini Gianluca G Romano Antonio A Mocchegiani Federico F Ackenine Kevin K Polacco Marina M Marinelli Laura L Ciccarelli Olga O Zanus Giacomo G Vivarelli Marco M Cillo Umberto U Rossi Massimo M Ericzon Bo-Göran BG Lerut Jan J
Updates in surgery 20200906 1
In the last years, several scoring systems based on pre- and post-transplant parameters have been developed to predict early post-LT graft function. However, some of them showed poor diagnostic abilities. This study aims to evaluate the role of the comprehensive complication index (CCI) as a useful scoring system for accurately predicting 90-day and 1-year graft loss after liver transplantation. A training set (n = 1262) and a validation set (n = 520) were obtained. The study was registered at h ...[more]
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Project description:We aimed to assess the ability of comprehensive complication index (CCI) and Clavien-Dindo complication (CDC) scale to predict excessive length of hospital stay (e-LOS) in patients undergoing liver resection for hepatocellular carcinoma. Patients were identified from an Italian multi-institutional database and randomly selected to be included in either a derivation or validation set. Multivariate logistic regression models and ROC curve analysis including either CCI or CDC as predictors of e-LOS were fitted to compare predictive performance. E-LOS was defined as a LOS longer than the 75th percentile among patients with at least one complication. A total of 2669 patients were analyzed (1345 for derivation and 1324 for validation). The odds ratio (OR) was 5.590 (95%CI 4.201; 7.438) for CCI and 5.507 (4.152; 7.304) for CDC. The AUC was 0.964 for CCI and 0.893 for CDC in the derivation set and 0.962 vs. 0.890 in the validation set, respectively. In patients with at least two complications, the OR was 2.793 (1.896; 4.115) for CCI and 2.439 (1.666; 3.570) for CDC with an AUC of 0.850 and 0.673, respectively in the derivation cohort. The AUC was 0.806 for CCI and 0.658 for CDC in the validation set. When reporting postoperative morbidity in liver surgery, CCI is a preferable scale.
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Project description:Background: Modern surgical techniques and scientific advancements have made liver transplant (LT) in infants feasible. However, there are only a small number of studies examining the short- as well as long-term outcomes of LT in this vulnerable subset of children. Methods: Comprehensive searches were done systematically through the PubMed, Scopus, and Google scholar databases. Studies that were retrospective record based or adopted a cohort approach and reported either patient survival rates or graft survival rates or complications of LT in infants were included in the meta-analysis. Statistical analysis was done using STATA version 13.0. Results: A total of 22 studies were included in the meta-analysis. The overall pooled patient survival rate at 1 year, >1-5 years, and >5 years post-transplantation was 85% (95% CI: 78--92%), 71% (95% CI: 59-83%), and 80% (95% CI: 69-91%), respectively. The overall pooled graft survival rate at 1 year, >1-5 years, and >5 years post-transplantation was 72% (95% CI: 68-76%), 62% (95% CI: 46-78%), and 71% (95% CI: 56-86%), respectively. The overall pooled rate for vascular complications, need for re-transplantation, biliary complications, and infection/sepsis was 12% (95% CI: 10-15%), 16% (95% CI: 12-20%), 15% (95% CI: 9-21%), and 50% (95% CI: 38-61%), respectively. Conclusion: The current meta-analysis showed modest patient and graft survival rates for infant liver transplantation. However, the complication rates related to infection/sepsis were high. More comprehensive evidence is required from studies with larger sample sizes and a longer duration of follow-up.
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Project description:Transplant and patient survival are the validated endpoints to assess the success of liver transplantation (LT). This study evaluates arterial and biliary complication-free survival (ABCFS) as a new metric. ABC, considered as an event, was an arterial or biliary complication of Dindo-Clavien grade ≥III complication dated at the interventional, endoscopic, or surgical treatment required to correct it. ABCFS was defined as the time from the date of LT to the dates of first ABC, death, relisting, or last follow-up (transplant survival is time from LT to repeat LT or death). Following primary whole LT (n = 532), 106 ABCs occurred and 99 (93%) occurred during the first year after LT. An ABC occurring during the first year after LT (overall rate 19%) was an independent factor associated with transplant survival (hazard ratio [HR], 3.17; P < 0.001) and patient survival (HR, 2.7; P = 0.002) in univariate and multivariate analyses. This result was confirmed after extension of the cohort to split-liver graft, donation after circulatory death, or re-LT (n = 658). Data from 2 external cohorts of primary whole LTs (n = 249 and 229, respectively) confirmed that the first-year ABC was an independent prognostic factor for transplant survival but not for patient survival. ABCFS was correlated with transplant and patient survival (ρ = 0.85 [95% CI, 0.78-0.90] and 0.81 [95% CI, 0.71-0.88], respectively). Preoperative factors known to influence 5-year transplant survival influenced ABCFS after 1 year of follow-up. The 1-year ABCFS was indicative of 5-year transplant survival. ABCFS is a reproducible metric to evaluate the results of LT after 1 year of follow-up and could serve as a new endpoint in clinical trials.
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Project description:Liver transplantation (LT) is one of the most effective treatments for hepatocellular carcinoma (HCC). Although LT eliminates HCC and greatly reduces recurrence, some patients experience recurrence after LT. Criteria and models for screening patients with a high probability of HCC recurrence after LT, starting with the Milan criteria, have been published. These models have changed over time, but a standard has not been established. We summarized HCC prediction models after LT by focusing on the application of radiologic, serologic, and pathologic factors and recent trends. This review will look at studies that are based on living donor LT and deceased donor LT, as well as studies that downstaging procedures have been performed preoperatively. This ultimately aims to help make decisions for evaluating the HCC state and selecting candidates for LT according to the circumstances of each transplantation center.
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Project description:ObjectiveTo investigate the prognostic impact of postoperative complications for patients with gastric cancer.MethodsPostoperative complications of patients undergoing radical gastrectomy for gastric cancer were reviewed. The severity of complications was graded by the CCI and C-D classification.ResultsA total of 5327 patients were included in the study. Complications were observed in 767 patients. When the C-D classification system was applied, for patients with grade I-II complications, the length of stay (LOS) of those with high CCI (CCI ≥ 26.2) was significantly longer than that of patients with low CCI (CCI < 26.2) (p < 0.001). The 5-year cancer-specific survival rate of patients with complications (52%) was lower than that of patients without complications (61%) (p < 0.001). Analysis of the factors associated with prognosis in patients with gastric cancer revealed that complications were independent risk factors for specific survival. When CCI was used to classify complication severity, the 5-year cancer-specific survival rate of the high-CCI group was 46.3%, which was lower than that of the low-CCI group (54.9%, p = 0.009).ConclusionComplication after radical gastrectomy is an independent prognostic factor, and the complication severity as graded by CCI reflects the difference of cancer-specific survival in gastric cancer patients with postoperative complications.
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Project description:Background and objectives: Immunonutrition is recommended by enhanced recovery after surgery in patients undergoing pancreatoduodenectomy for 5-7 days perioperatively as it may reduce the rate of infectious complications. However, data on effect of immunonutrition on the overall complication rate are contradictory and it is not clear, which groups of patients benefit most. The aims of this study are to evaluate the effects of immunonutrition on the overall complication rate and the rate of severe and/or multiple complications in patients with pancreatic tumours stratified according to final histological diagnosis-patients with pancreatic ductal adenocarcinoma (PDAC) vs. other tumours-and nutritional state, using more sensitive Comprehensive Complication Index. Materials and Methods: Seventy consecutive patients scheduled for pancreatoduodenectomy because of pancreatic tumours were randomised into immunonutrition vs. control groups and stratified according to final histological diagnosis and nutritional status. Surgical outcomes were assessed postoperatively using Clavien-Dindo classification (CDC) and Comprehensive Complication Index (CCI). Results: No significant differences in the overall complication rates in immunonutrition vs. control, patients with malnutrition vs. no malnutrition, PDAC vs. other pancreatic tumours groups were detected. However, significant differences in the rates of severe and/or multiple complications in immunonutrition vs. control groups and in PDAC patients segregated according to immunonutrition were obtained using CCI. Conclusions: Patients with PDAC may experience greater benefits of immunonutrition as compared to patients with benign pancreatic diseases or less aggressive tumours, while nutritional status was not a determining factor for the efficacy of immunonutrition.
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Project description:Right heart-associated hemodynamic parameters including intraoperative pulmonary vascular resistance (PVR) were reported to be associated with patient survival after liver transplantation. We investigated whether intraoperative stroke work indexes of both ventricles could have a better prognostic value than PVR. We reviewed 683 cases at a tertiary care academic medical center. We collected intraoperative variables of baseline central venous pressure, baseline right ventricle end-diastolic volume, mixed venous oxygen saturation, intraoperative PVR and right and left ventricular stroke work indexes. Time-weighted means or area under the curve of intraoperative right and left ventricular stroke work indexes were calculated as exposure variables. One-year all-cause mortality or graft failure was our primary outcome. Cox proportional hazard regression analysis was performed to evaluate the association between exposure variables and one-year all-cause mortality or graft failure. Kaplan-Meier survival curve analysis of our primary outcome was performed for different time-weighted mean ventricular stroke work index groups. Cubic spline curve analysis was performed to evaluate the linear relationship between our exposure variables and primary outcome. Time-weighted mean right ventricular stroke work index was significantly associated with one-year all-cause mortality or graft failure (hazard ratio 1.21, 95% confidence interval (CI) 1.12-1.36, p < 0.001). However, there was no significant association between time-weighted mean left ventricular stroke work index, time-weighted mean PVR, PVR at the end of surgery and one-year mortality. Area under the curve of right ventricular stroke work index was also significantly associated with one-year mortality or graft failure (hazard ratio 1.24, 95% CI 1.15-1.37, p < 0.001). Kaplan-Meier survival curve analysis showed a significant difference in the survival between different mean right ventricular stroke work index groups (Log-rank test: p = 0.002). Cubic spline function curve showed the gradual increase in the risk of mortality with a positive slope with time-weighted mean right ventricular stroke work index. In conclusion, intraoperative elevated right ventricular stroke work index was significantly associated with poor patient or graft survival after liver transplantation. Intraoperative right ventricular stroke work index could be an intraoperative hemodynamic goal and prognostic marker for mortality after liver transplantation.
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Project description:BackgroundSeveral studies have shown that obese patients undergoing liver transplantation (LT) have an increased risk of mortality regardless of Model of End Stage Liver Disease (MELD) scores. The purpose of this study is to identify the range of body mass index (BMI) at LT associated with the lowest risks of posttransplant mortality by MELD category.MethodsA retrospective cohort of patients aged 18 years or older from the Organ Procurement and Transplantation Network database undergoing LT between February 27, 2002, and December 31, 2013, was identified and followed up through March 14, 2014. Patients' MELD score at the time of transplantation was categorized into 10 or lower (MELD1), 11 to 18 (MELD2), 19 to 24 (MELD3), and 25 or higher (MELD4). Multivariable adjusted Cox proportional hazard analyses were conducted.ResultsAmong 48 226 patients in the analytic cohort (14.8% were in MELD1, 33.7% were in MELD2, 19.6% were in MELD3, and 32.0% were in MELD4), 25% died with mean follow-up of 1371 days. For MELD1, patient BMI ranging from 30 to 33 was associated with a better survival outcome than BMI less than 30 or 33 or greater; for MELD2, BMI ranging from 28 to 37 had a better survival outcome than BMI less than 28 or 37 or greater; for MELD3, the survival outcome improved with an increasing BMI; for MELD4, the survival outcome was not associated with patient BMI.ConclusionsThis study provides evidence that obesity in LT patients is not necessarily associated with higher posttransplantation mortality and highlights the importance of the interaction between BMI and MELD category to determine their survival likelihood.
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Project description: Not available
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Project description:BackgroundPredicting survival of recipients after liver transplantation is regarded as one of the most important challenges in contemporary medicine. Hence, improving on current prediction models is of great interest.Nowadays, there is a strong discussion in the medical field about machine learning (ML) and whether it has greater potential than traditional regression models when dealing with complex data. Criticism to ML is related to unsuitable performance measures and lack of interpretability which is important for clinicians.MethodsIn this paper, ML techniques such as random forests and neural networks are applied to large data of 62294 patients from the United States with 97 predictors selected on clinical/statistical grounds, over more than 600, to predict survival from transplantation. Of particular interest is also the identification of potential risk factors. A comparison is performed between 3 different Cox models (with all variables, backward selection and LASSO) and 3 machine learning techniques: a random survival forest and 2 partial logistic artificial neural networks (PLANNs). For PLANNs, novel extensions to their original specification are tested. Emphasis is given on the advantages and pitfalls of each method and on the interpretability of the ML techniques.ResultsWell-established predictive measures are employed from the survival field (C-index, Brier score and Integrated Brier Score) and the strongest prognostic factors are identified for each model. Clinical endpoint is overall graft-survival defined as the time between transplantation and the date of graft-failure or death. The random survival forest shows slightly better predictive performance than Cox models based on the C-index. Neural networks show better performance than both Cox models and random survival forest based on the Integrated Brier Score at 10 years.ConclusionIn this work, it is shown that machine learning techniques can be a useful tool for both prediction and interpretation in the survival context. From the ML techniques examined here, PLANN with 1 hidden layer predicts survival probabilities the most accurately, being as calibrated as the Cox model with all variables.Trial registrationRetrospective data were provided by the Scientific Registry of Transplant Recipients under Data Use Agreement number 9477 for analysis of risk factors after liver transplantation.
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