Literature DB >> 35298079

Improving the Model for End-Stage Liver Disease with sodium by incorporating kidney dysfunction types.

Giuseppe Cullaro1, Elizabeth C Verna2, Charles E McCulloch3, Jennifer C Lai1.   

Abstract

BACKGROUND AND AIMS: We investigated the impact of the inclusion of kidney dysfunction type on the discrimination and calibration of the Model for End-Stage Liver Disease with sodium (MELD-Na-KT) score. APPROACH AND
RESULTS: We included all adults listed for ≥90 days without exception points from January 1, 2008, through December 31, 2018. We defined kidney dysfunction types as follows: acute kidney disease (AKD; an increase of ≥0.3 mg/dL or ≥50% in serum creatinine in the last 7 days or fewer than 72 days of hemodialysis), chronic kidney disease (CKD; an estimated glomerular filtration rate <60 ml/min/1.73 m2  for 90 days or ≥72 days of hemodialysis), AKD on CKD (met both definitions), or none (met neither definition). We then developed and validated a multivariable survival model with follow-up beginning at the first assessment after 90 days from waitlist registration and ending at the time of death, waitlist removal, or 90 days from enrollment in this study. The predictor variables were MELD-Na and the derived MELD-Na-KT model. In the derivation cohort, kidney dysfunction type was significantly associated with waitlist mortality after controlling for MELD-Na. There was a significant linear interaction between kidney dysfunction type and MELD-Na score. In the validation cohort, we saw an improvement in the discrimination of the model with an increase in the c-index from 0.76 with MELD-Na to 0.78 with MELD-Na-KT (p = 0.002) and a net reclassification index of 10.8% (95% CI, 1.9%-11.4%). The newly derived MELD-Na-KT model had lower Brier scores (MELD-Na-KT 0.042 vs. MELD-Na 0.053).
CONCLUSIONS: This study demonstrates the feasibility and the potential for objectively defined kidney dysfunction types to enhance the prognostication of waitlist mortality provided by the MELD-Na score.
© 2022 American Association for the Study of Liver Diseases.

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Year:  2022        PMID: 35298079      PMCID: PMC9378344          DOI: 10.1002/hep.32448

Source DB:  PubMed          Journal:  Hepatology        ISSN: 0270-9139            Impact factor:   17.298


  32 in total

1.  Differential Impact of Age Among Liver Transplant Candidates With and Without Hepatocellular Carcinoma.

Authors:  Giuseppe Cullaro; Jessica B Rubin; Neil Mehta; Jennifer C Lai
Journal:  Liver Transpl       Date:  2019-11-20       Impact factor: 5.799

2.  Estimating a time-dependent concordance index for survival prediction models with covariate dependent censoring.

Authors:  Thomas A Gerds; Michael W Kattan; Martin Schumacher; Changhong Yu
Journal:  Stat Med       Date:  2012-11-22       Impact factor: 2.373

3.  Tests of calibration and goodness-of-fit in the survival setting.

Authors:  Olga V Demler; Nina P Paynter; Nancy R Cook
Journal:  Stat Med       Date:  2015-02-11       Impact factor: 2.373

4.  Development and validation of a mathematical equation to estimate glomerular filtration rate in cirrhosis: The royal free hospital cirrhosis glomerular filtration rate.

Authors:  Maria Kalafateli; Fred Wickham; Maria Burniston; Evangelos Cholongitas; Eleni Theocharidou; Matteo Garcovich; James O'Beirne; Rachel Westbrook; Gioacchino Leandro; Andrew K Burroughs; Emmanuel A Tsochatzis
Journal:  Hepatology       Date:  2016-11-29       Impact factor: 17.425

Review 5.  Simultaneous liver kidney transplantation.

Authors:  Ashwani K Singal; Song Ong; Sanjaya K Satapathy; Patrick S Kamath; Russel H Wiesner
Journal:  Transpl Int       Date:  2019-02-21       Impact factor: 3.782

Review 6.  A model to predict survival in patients with end-stage liver disease.

Authors:  P S Kamath; R H Wiesner; M Malinchoc; W Kremers; T M Therneau; C L Kosberg; G D'Amico; E R Dickson; W R Kim
Journal:  Hepatology       Date:  2001-02       Impact factor: 17.425

7.  Acute kidney disease and renal recovery: consensus report of the Acute Disease Quality Initiative (ADQI) 16 Workgroup.

Authors:  Lakhmir S Chawla; Rinaldo Bellomo; Azra Bihorac; Stuart L Goldstein; Edward D Siew; Sean M Bagshaw; David Bittleman; Dinna Cruz; Zoltan Endre; Robert L Fitzgerald; Lui Forni; Sandra L Kane-Gill; Eric Hoste; Jay Koyner; Kathleen D Liu; Etienne Macedo; Ravindra Mehta; Patrick Murray; Mitra Nadim; Marlies Ostermann; Paul M Palevsky; Neesh Pannu; Mitchell Rosner; Ron Wald; Alexander Zarbock; Claudio Ronco; John A Kellum
Journal:  Nat Rev Nephrol       Date:  2017-02-27       Impact factor: 28.314

8.  Glomerular filtration rate equations for liver-kidney transplantation in patients with cirrhosis: validation of current recommendations.

Authors:  Claire Francoz; Mitra K Nadim; Aurore Baron; Dominique Prié; Corinne Antoine; Jacques Belghiti; Dominique Valla; Richard Moreau; François Durand
Journal:  Hepatology       Date:  2014-03-03       Impact factor: 17.425

Review 9.  Precipitants of Acute-on-Chronic Liver Failure: An Opportunity for Preventative Measures to Improve Outcomes.

Authors:  Giuseppe Cullaro; Rajani Sharma; Jonel Trebicka; Andrés Cárdenas; Elizabeth C Verna
Journal:  Liver Transpl       Date:  2020-01-06       Impact factor: 5.799

10.  MELD-GRAIL-Na: Glomerular Filtration Rate and Mortality on Liver-Transplant Waiting List.

Authors:  Sumeet K Asrani; Linda W Jennings; W R Kim; Patrick S Kamath; Josh Levitsky; Mitra K Nadim; Giuliano Testa; Michael D Leise; James F Trotter; Goran Klintmalm
Journal:  Hepatology       Date:  2020-01-29       Impact factor: 17.425

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