Evidence map›Paper›PMID 35999302›Full record

ArticleClinical and experimental nephrology2022

Prediction of cardiovascular outcome by estimated glomerular filtration rate among high-risk patients: a Thai nationwide cohort study.

Noppawit Aiumtrakul, Annop Kittithaworn, Ouppatham Supasyndh, Rungroj Krittayaphong, Arintaya Phrommintikul, Bancha Satirapoj

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Article in Clinical and experimental nephrology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

1 citing paper in PubMed.

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4 · The record

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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

6 authors.

Noppawit AiumtrakulDivision of Nephrology, Department of Medicine, Phramongkutklao Hospital and College of Medicine, Bangkok, Thailand. noppawit.aiumtrakul@gmail.com.ORCID http://orcid.org/0000-0003-0479-7785
Annop KittithawornDivision of Nephrology, Department of Medicine, Phramongkutklao Hospital and College of Medicine, Bangkok, Thailand.
Ouppatham SupasyndhDivision of Nephrology, Department of Medicine, Phramongkutklao Hospital and College of Medicine, Bangkok, Thailand.
Rungroj KrittayaphongDivision of Cardiology, Department of Medicine, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand.
Arintaya PhrommintikulDivision of Cardiology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Bancha SatirapojDivision of Nephrology, Department of Medicine, Phramongkutklao Hospital and College of Medicine, Bangkok, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDecline of estimated glomerular filtration rate (eGFR) is associated with increased cardiovascular (CV) morbidity and mortality, but the predictive value of different eGFR on CV outcomes is limited in Southeast Asian populations.

aimsWe aimed to stratify CV outcomes according to renal function among Thai patients with high atherosclerosis risk.

methodsWe performed a secondary analysis in a 5-year national cohort entitled "CORE-Thailand study." Subjects were classified in 6 groups according to baseline kidney function: group I, eGFR ≥ 90; group II, eGFR 60-89; group IIIa, eGFR 45-59; group IIIb, eGFR 30-44; group IV, eGFR 15-29; group V, eGFR < 15 ml/min/1.73 m

resultsA total of 6376 subjects (3467 men and 2909 women) were categorized in 6 groups. After adjusting covariates in the Cox proportional hazards model, compared to group I, subjects in groups II-V had a 1.65-fold, 2.17-fold, 2.67-fold, 4.24-fold, and 4.87-fold risk for 4-point MACE, respectively, with statistical significance at P < 0.05 in all groups. Kaplan-Meier analysis illustrated stepwise lower survivals from 4-point MACE following the groups with lower baseline eGFR (log-rank test with P < 0.001). All secondary outcomes showed similar trends as the primary outcome, except nonfatal stroke.

conclusionLower baseline kidney function was independently associated with increased risk of CV events and all-cause mortality in Thai populations at high CV risk.

Indexed as

Cardiovascular DiseasesCardiovascular SystemStrokeCohort StudiesFemaleGlomerular Filtration RateHumansMaleRisk FactorsThailandAtherosclerosisChronic kidney diseaseGlomerular filtration rateHigh cardiovascular risk

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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.