Evidence map›Paper›PMID 22965903›Full record

ArticleLiver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society2012

Factors that affect deceased donor liver transplantation rates in the United States in addition to the Model for End-stage Liver Disease score.

Pratima Sharma, Douglas E Schaubel, Emily E Messersmith, Mary K Guidinger, Robert M Merion

Abstract read
In one paragraph

Article in Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Women who undergo liver transplant have longer length of stay post-transplant compared with men.Liver international : official journal of the International Association for the Study of the Liver · 2020
    Article
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  8. Article
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  10. Review
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Pratima SharmaDepartment of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA. pratimas@med.umich.edu
Douglas E Schaubel
Emily E Messersmith
Mary K Guidinger
Robert M Merion

Funding

Survival Analysis Methods for Organ Failure DataR01DK070869 · NIDDK · UNIVERSITY OF PENNSYLVANIA · PI DOUGLAS EARL SCHAUBEL · 2005 to 2026
$4.7M
Predicting the burden of renal disease among liver transplant recipientsK08DK088946 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SHARMA, PRATIMA · 2011 to 2015
$765k
NIDDK NIH HHS 5R01 DK-70869NIDDK NIH HHS K08 DK-088946NIDDK NIH HHS K08 DK088946NIDDK NIH HHS R01 DK070869
6 · The paper itself

Abstract

Under an ideal implementation of Model for End-Stage Liver Disease (MELD)-based liver allocation, the only factors that would predict deceased donor liver transplantation (DDLT) rates would be the MELD score, blood type, and donation service area (DSA). We aimed to determine whether additional factors are associated with DDLT rates in actual practice. Data from the Scientific Registry of Transplant Recipients for all adult candidates wait-listed between March 1, 2002 and December 31, 2008 (n = 57,503) were analyzed. Status 1 candidates were excluded. Cox regression was used to model covariate-adjusted DDLT rates, which were stratified by the DSA, blood type, liver-intestine policy, and allocation MELD score. Inactive time on the wait list was not modeled, so the computed DDLT hazard ratios (HRs) were interpreted as active wait-list candidates. Many factors, including the candidate's age, sex, diagnosis, hospitalization status, and height, prior DDLT, and combined listing for liver-kidney or liver-intestine transplantation, were significantly associated with DDLT rates. Factors associated with significantly lower covariate-adjusted DDLT rates were a higher serum creatinine level (HR = 0.92, P < 0.001), a higher bilirubin level (HR = 0.99, P = 0.001), and the receipt of dialysis (HR = 0.83, P < 0.001). Mild ascites (HR = 1.15, P < 0.001) and hepatic encephalopathy (grade 1 or 2, HR = 1.05, P = 0.02; grade 3 or 4, HR = 1.10, P = 0.01) were associated with significantly higher adjusted DDLT rates. In conclusion, adjusted DDLT rates for actively listed candidates are affected by many factors aside from those integral to the allocation system; these factors include the components of the MELD score itself as well as candidate factors that were considered but were deliberately omitted from the MELD score in order to keep it objective. These results raise the question whether additional candidate characteristics should be explicitly incorporated into the prioritization of wait-list candidates because such factors are already systematically affecting DDLT rates under the current allocation system.

Indexed as

Decision Support TechniquesHealthcare DisparitiesHealth Status IndicatorsLiver TransplantationWaiting ListsBlood Grouping and CrossmatchingEnd Stage Liver DiseaseFemaleHistocompatibilityHumansMaleMiddle AgedProportional Hazards ModelsRegistriesResidence CharacteristicsRetrospective Studies

Identifiers

PMID22965903
PMCPMC3518743

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.