Evidence map›Paper›PMID 30373110›Full record

ArticleJournal of clinical medicine2018

Propensity Score-Matched Analysis of the Survival Benefit from Kidney Transplantation in Patients with End-Stage Renal Disease.

Ming-Ju Wu, Tung-Min Yu, Cheng-Li Lin, Chia-Hung Kao

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 37% of its field
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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
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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

4 authors at 3 institutions in 1 country.

Ming-Ju WuDivision of Nephrology, Department of Medicine, Taichung Veterans General Hospital, Taichung 400, Taiwan. wmj530@gmail.com.
Tung-Min YuDivision of Nephrology, Department of Medicine, Taichung Veterans General Hospital, Taichung 400, Taiwan. yu5523@gmail.com.
Cheng-Li LinManagement Office for Health Data, China Medical University Hospital, Taichung 404, Taiwan. orangechengli@gmail.com.
Chia-Hung KaoGraduate Institute of Biomedical Sciences and School of Medicine, China Medical University, Taichung 404, Taiwan. d10040@mail.cmuh.org.tw.ORCID 0000-0002-6368-3676
China Medical University · TWAsia University · TWNational Chung Hsing University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral comparison studies have suggested that kidney transplantation (KT) could reduce mortality in patients with end-stage renal disease (ESRD). Selection criteria bias is common in the selection of dialysis patients for control groups. In this study, we compared the survival outcome between KT recipients and comparable propensity score-matched dialysis patients.

methodsWe used Taiwan's National Health Insurance Research Database to identify patients newly diagnosed with ESRD between 2000 and 2010. We separated them into two groups: a KT group and non-KT dialysis-only group. To evaluate the survival outcome, we compared each patient with KT to a patient on dialysis without KT using propensity score matching.

resultsIn total, 1276 KT recipients and 1276 propensity score-matched dialysis patients were identified. Compared with the propensity score-matched dialysis patients, the patients who underwent KT exhibited significantly higher 5-year and 10-year survival rates (88% vs. 92% and 74% vs. 87%, both

conclusionThis study used a propensity score-matched cohort to confirm that KT is associated with lower risk of mortality than dialysis alone in patients newly diagnosed with ESRD.

Indexed as

dialysiskidney transplantationpropensity score matchingsurvival

Identifiers

PMID30373110
PMCPMC6262546
OpenAlexW2898108984

What OpenQuestion holds

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LicenceCC BY
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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.