High MELD score and extended operating time predict prolonged initial ICU stay after liver transplantation and influence the outcome

Stratigopoulou, Panagiota; Paul, Andreas; Hoyer, Dieter P.; Kykalos, Stylianos; Saner, Fuat H.; Sotiropoulos, Georgios C.

doi:10.1371/journal.pone.0174173

Cited by 20 publications

(14 citation statements)

References 29 publications

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“…Several studies used either single‐center analysis or registry data to focus on the C1 risk model for mortality after LT. Importantly, although previous risk factor analyses included the MELD score as a preoperative predictor using C1 variables, in the present study, similar to a previous meta‐analysis, it was not an independent risk factor. Observation of a significantly improved AUC of the C1 risk calculator model for mortality versus the previously reported equations from single‐center analyses indicates an effectiveness of these novel risk calculator models.…”

Section: Discussionsupporting

confidence: 55%

“…The postoperative clinical course after LT should be determined by preoperative/postoperative recipient conditions and donor allograft conditions. Many studies have investigated the preoperative and intraoperative risk factors of recipient‐related or allograft‐related DDLT and LDLT recipients . However, to our knowledge, a large population study investigating both recipient and donor allograft conditions based on registry data has not been carried out to date.…”

Section: Introductionmentioning

confidence: 99%

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“Real‐time” risk models of postoperative morbidity and mortality for liver transplants

Marubashi

Ichihara²,

Kakeji

et al. 2018

Annals of Gastroent Surgery

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AimA comprehensive description of morbidity and mortality risk factors for post liver transplant has not been available to date. In this study, we established real‐time risk models of postoperative morbidities and mortality in liver transplant recipients using two Japanese nationwide databases.MethodsData from two Japanese nationwide databases were combined and used for this study. We developed real‐time prognostic models for morbidity and mortality from a derivation cohort (n = 1472) and validated the findings with an independent cohort (n = 395). Preoperative variables (C1), preoperative and intraoperative variables (C2), and all variables including postoperative morbidities within 30 days (C3) were analyzed to evaluate the independent risk factors for postoperative morbidity and mortality.ResultsWe established real‐time risk models for morbidity and mortality. Areas under the curve (AUC) of C1 and C2 risk models for mortality were 0.74 (0.63‐0.82) and 0.79 (0.69‐0.86), respectively. Multivariate logistic analysis using C3 showed that hemoglobin <10 g/dL, operative time (hours), and five postoperative morbidities (prolonged ventilation >48 hours, coma >24 hours, renal dysfunction, postoperative systemic sepsis, and serum total bilirubin ≥10 mg/dL) represented independent risk factors for mortality (AUC = 0.87, 95% confidence interval [CI]: 0.78‐0.93).ConclusionsReal‐time risk models of postoperative morbidities and mortality at various perioperative time points in liver transplant recipients were established. These novel approaches may improve postoperative outcomes of liver transplant recipients. Furthermore, these real‐time risk models may be applicable to other surgical procedures.

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Section: Discussionsupporting

confidence: 55%

Section: Introductionmentioning

confidence: 99%

“Real‐time” risk models of postoperative morbidity and mortality for liver transplants

Marubashi

Ichihara²,

Kakeji

et al. 2018

Annals of Gastroent Surgery

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“…Finally, we analyzed a potential allocation bias by comparing match frequencies of marginal livers and marginal recipients. Marginal livers were defined as donor age > 60 years [ 17 ], BMI > 25 kg/m 2 [ 18 ] and cold ischemia time > 12 hours [ 19 ], while marginal recipients were defined as those with a MELD > 35 or HU-status [ 20 ]. In addition, we calculated the donor risk index (DRI, [ 17 ]) for every patient.…”

Section: Resultsmentioning

confidence: 99%

The weekend effect in liver transplantation

et al. 2018

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BackgroundThe weekend effect describes a phenomenon whereby patients admitted to hospitals on weekends are at higher risk of complications compared to those admitted during weekdays. However, if a weekend effect exists in orthotopic liver transplantation (oLT).MethodsWe analyzed oLT between 2006 and 2016 and stratified patients into weekday (Monday to Friday) and weekend (Saturday, Sunday) groups. Primary outcome measures were one-year patient and graft survival.Results364 deceased donor livers were transplanted into 329 patients with 246 weekday (74.77%) and 83 weekend (25.23%) patients. Potential confounders (e.g. age, ischemia time, MELD score) were comparable. One-year patient and graft survival were similar. Frequencies of rejections, primary-non function or re-transplantation were not different. The day of transplantation was not associated with one-year patient and graft survival in multivariate analysis.ConclusionsWe provide the first data for the Eurotransplant region on oLT stratified for weekend and weekday procedures and our findings suggest there was no weekend effect on oLT. While we hypothesize that the absent weekend effect is due to standardized transplant procedures and specialized multidisciplinary transplant teams, our results are encouraging showing oLT is a safe and successful procedure, independent from the day of the week.

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“…Regarding length of stay in the ICU, Pedersen and associates, 17 in a study of factors associated with a longer stay in the ICU, found that pretransplant MELD was the most potent predictor of prolonged ICU stay. Stratigopoulou and colleagues 18 confirmed that MELD and transplant duration are independent predictors of prolonged ICU stay. However, Rana and associates 19 hospital stay, the 2 most significant were shown to be previous admission of the recipient to the ICU (odds ratio of 1.75; 95% CI, 1.58-1.95) and previous transplant (odds ratio of 1.60; 95% CI, 1.47-1.75).…”

Section: Discussionmentioning

confidence: 91%

Graft Risk Index After Liver Transplant: Internal and External Validation of a New Spanish Indicator

Burdio¹,

Buil²,

Lopez³

et al. 2019

Exp Clin Transplant

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Objectives: Scarcity of liver grafts has led to the use of marginal donors, consequently increasing the number of complications posttransplant. To prevent this situation, several indicators have been developed. However, important differences remain among countries. Here, we compared an early-risk liver transplant indicator based on the Spanish Liver Transplant Registry, called the Graft Risk Index, versus the US donor risk index and the Eurotransplant donor risk index. Materials and Methods: The new indicator was based on prospectively collected data from 600 adult liver transplants performed in our center. We considered 2 events to compare the indexes: graft survival and rejection-free graft survival, with Cox proportional regression for analyses. Power to predict graft survival was evaluated by calculating the receiver operating characteristic area under the curve. Results: We found no differences between the US and Eurotransplant donor risk indexes in prediction of patients with and without early graft failure. With regard to early survival, only the Graft Risk Index allowed better survival discrimination, in which survival progressively decreased with values ≥ 3 (with probability of graft survival at 1 month of 68%; 95% confidence interval, 46.2-82.5). This increase in risk was significant compared with the standard group (hazard ratio of 10.15; 95% confidence interval, C 3.91-26.32; P < .001). We calculated powers of prediction of 0.52 (95% confidence interval, 0.43-0.62), 0.54 (95% confidence interval, 0.45-0.65), and 0.69 (95% confidence interval, 0.61-0.77) for donor risk index, Eurotransplant donor risk index, and early Graft Risk Index, respectively. Conclusions: Neither the US donor risk index nor the Eurotransplant donor risk index was valid for our Spanish liver donation and transplant program. Therefore, an indicator to predict posttransplant graft survival that is adapted to our environment is necessary. This national Graft Risk Index can be a useful tool to optimize donor-recipient matching.

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High MELD score and extended operating time predict prolonged initial ICU stay after liver transplantation and influence the outcome

Cited by 20 publications

References 29 publications

“Real‐time” risk models of postoperative morbidity and mortality for liver transplants

“Real‐time” risk models of postoperative morbidity and mortality for liver transplants

The weekend effect in liver transplantation

Graft Risk Index After Liver Transplant: Internal and External Validation of a New Spanish Indicator

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