Evidence map›Paper›PMID 37213466›Full record

ArticleJournal of research in medical sciences : the official journal of Isfahan University of Medical Sciences2023

The effects of prognostic factors on transplant and mortality of patients with end-stage liver disease using Markov multistate model.

Elham Madreseh, Mahmood Mahmoudi, Mohssen Nassiri Toosi, Jamileh Abolghasemi, Hojjat Zeraati

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In one paragraph

Article in Journal of research in medical sciences : the official journal of Isfahan University of Medical Sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed, 0 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Elham MadresehDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mahmood MahmoudiDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Mohssen Nassiri ToosiLiver Transplantation Research Center, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
Jamileh AbolghasemiDepartment of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Hojjat ZeraatiDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Tehran University of Medical Sciences · IRIran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Decompensated cirrhosis patients have a high risk of death which can be considerably reduced with liver transplantation (LT). This study aimed to simultaneously investigate the effect of some patients' characteristics on mortality among those with/without LT and also LT incident. Materials and Methods: In this historical cohort study, the information from 780 eligible patients aged 18 years or older was analyzed by the Markov multistate model; they had been listed between 2008 and 2014, needed a single organ for initial orthotopic LT, and followed at least for up to 5 years. Results: With a median survival time of 6 (5-8) years, there were 275 (35%) deaths. From 255 (33%) patients who had LT, 55 (21%) subsequently died. Factors associated with a higher risk of mortality and LT occurrence were included: higher model for end-stage liver disease (MELD) score (hazard ratio [HR] = 1.16, confidence interval [CI]: 1.09-1.24 and HR = 1.22, CI: 1.41-1.30) and ascites complication (HR = 2.34, CI: 1.74-3.16 and HR = 11.43, CI: 8.64-15.12). Older age (HR = 1.03, CI: 1.01-1.06), higher creatinine (HR = 6.87, CI: 1.45-32.56), and autoimmune disease versus hepatitis (HR = 2.53, CI: 1.12-5.73) were associated with increased risk of mortality after LT. Conclusion: The MELD and ascites are influential factors on waiting list mortality and occurrence of LT. Total life expectancy is not influenced by higher MELD.

Indexed as

Cirrhosislife expectancymodel for end-stage liver diseasesurvival

Identifiers

PMID37213466
PMCPMC10199371
OpenAlexW4362650435

What OpenQuestion holds

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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.