Evidence map›Paper›PMID 41086225›Full record

ArticlePloS one2025

High unawareness of kidney dysfunction in European older adults and the importance of early detection through comorbidities.

Hannah Marie Horton, Martina Börsch-Supan

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Hannah Marie HortonTechnical University of Munich, Munich, Bavaria, Germany.ORCID https://orcid.org/0000-0001-5121-9684
Martina Börsch-SupanDepartment of Health Econometrics, Munich Research Institute for the Economics of Aging and SHARE Analyses, Munich, Bavaria, Germany.

Funding

Understanding Cross-National Health Differences at Older Ages and Their CausesR01AG063944 · NIA · NATIONAL BUREAU OF ECONOMIC RESEARCH · PI BOERSCH-SUPAN, AXEL H, CRIMMINS, EILEEN M · 2019 to 2024
$3.2M
NIA NIH HHS R01 AG063944
6 · The paper itself

Abstract

introductionChronic kidney disease (CKD) continues to go undiagnosed at significant rates in Europe, with few exploring the underlying mechanisms which prompt detection. Considering the causal link of numerous health conditions and CKD, this study investigates how individual and combined comorbidities are associated with the likelihood of CKD detection. MATERIALS AND

methodsIn a large population study (n = 22,386) of older adults (50+) among 11 European countries and Israel, we calculate the prevalence of undiagnosed CKD using serum-equivalent cystatin C values, derived from dried blood spots. Logistic regressions are estimated to predict factors related to CKD diagnosis among the population and among those with diagnosed vs. undiagnosed CKD.

resultsUnawareness of CKD among older adults is estimated at 11% in the population and ~85% among CKD cases, with country heterogeneity. Common conditions which should prompt screening, such as hypertension and diabetes, do not increase the likelihood of CKD diagnosis among those with reported and measured CKD. Instead, conditions which are demanding in terms of pain and continuous care, such as cancer and arthritis, are associated with an increased likelihood of CKD detection. However, even in the case of four or more comorbidities, the likelihood of CKD detection is only 27.3%. Women and older individuals are more likely to remain undiagnosed.

conclusionsIn order to increase the chance of detection, comorbidities need to be better interpreted as early warning signals of CKD.

Indexed as

Renal Insufficiency, ChronicAgedAged, 80 and overComorbidityCystatin CEarly DiagnosisEuropeFemaleHumansMaleMiddle AgedPrevalenceCystatin C

Identifiers

PMID41086225
PMCPMC12520349

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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.