Evidence map›Paper›PMID 34430385›Full record

ArticleWorld journal of nephrology2021

Prediction of mortality among patients with chronic kidney disease: A systematic review.

Panupong Hansrivijit, Yi-Ju Chen, Kriti Lnu, Angkawipa Trongtorsak, Max M Puthenpura, Charat Thongprayoon, Tarun Bathini, Michael A Mao, Wisit Cheungpasitporn

Abstract read
In one paragraph

Article in World journal of nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
–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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  18. Pharmacokinetics and Drug-Drug Interaction of Ocedurenone (KBP-5074) in vitro and in vivo.European journal of drug metabolism and pharmacokinetics · 2023
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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

9 authors.

Panupong HansrivijitDepartment of Internal Medicine, UPMC Pinnacle, Harrisburg, PA 17104, United States.
Yi-Ju ChenDepartment of Internal Medicine, UPMC Pinnacle, Harrisburg, PA 17104, United States.
Kriti LnuDepartment of Internal Medicine, UPMC Pinnacle, Harrisburg, PA 17104, United States.
Angkawipa TrongtorsakDepartment of Internal Medicine, Amita Health Saint Francis Hospital, Evanston, IL 60202, United States.
Max M PuthenpuraDepartment of Medicine, Drexel University College of Medicine, Philadelphia, PA 19129, United States.
Charat ThongprayoonDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, United States.
Tarun BathiniDepartment of Internal Medicine, University of Arizona, Tucson, AZ 85721, United States.
Michael A MaoDivision of Nephrology and Hypertension, Mayo Clinic, Jacksonville, FL 32224, United States.
Wisit CheungpasitpornDivision of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, United States. wcheungpasitporn@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) is a common medical condition that is increasing in prevalence. Existing published evidence has revealed through regression analyses that several clinical characteristics are associated with mortality in CKD patients. However, the predictive accuracies of these risk factors for mortality have not been clearly demonstrated.

aimTo demonstrate the accuracy of mortality predictive factors in CKD patients by utilizing the area under the receiver operating characteristic (ROC) curve (AUC) analysis.

methodsWe searched Ovid MEDLINE, EMBASE, and the Cochrane Library for eligible articles through January 2021. Studies were included based on the following criteria: (1) Study nature was observational or conference abstract; (2) Study populations involved patients with non-transplant CKD at any CKD stage severity; and (3) Predictive factors for mortality were presented with AUC analysis and its associated 95% confidence interval (CI). AUC of 0.70-0.79 is considered acceptable, 0.80-0.89 is considered excellent, and more than 0.90 is considered outstanding.

resultsOf 1759 citations, a total of 18 studies (

conclusionSeveral factors were found to predict mortality in CKD patients. Echocardiography is an important tool for mortality prognostication in CKD patients by evaluating left atrial reservoir strain, systolic pulmonary artery pressure, diastolic function, and left ventricular mass index.

Indexed as

Chronic kidney diseaseDeathDialysisEnd stage kidney diseaseEnd stage renal diseaseMortalityPredictors

Identifiers

PMID34430385
PMCPMC8353601

What OpenQuestion holds

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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.