Evidence map›Paper›PMID 39438792›Full record

ArticleBMC cardiovascular disorders2024

Kidney function, uric acid, and risk of atrial fibrillation: experience from the AMORIS cohort.

Mozhu Ding, Katharina Schmidt-Mende, Juan-Jesus Carrero, Gunnar Engström, Niklas Hammar, Karin Modig

Abstract read
In one paragraph

Article in BMC cardiovascular disorders, 2024. 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. Review
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

6 authors.

Mozhu DingUnit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Nobelsväg 13, Stockholm, 17177, Sweden. mozhu.ding@ki.se.
Katharina Schmidt-MendeAcademic Primary Health Care Centre, Stockholm Region, Stockholm, Sweden.
Juan-Jesus CarreroDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Gunnar EngströmDepartment of Clinical Sciences, Lund University, Malmö, Sweden.
Niklas HammarUnit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Nobelsväg 13, Stockholm, 17177, Sweden.
Karin ModigUnit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Nobelsväg 13, Stockholm, 17177, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUric acid closely relates to both kidney disease and atrial fibrillation (AF), yet the extent to which it influences the kidney-AF association remains uncertain. We examined the relationship between kidney function and risk of AF, accounting for uric acid levels.

methodsA total of 308,509 individuals in the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) cohort were included and their serum creatinine and uric acid were measured during 1985-1996. Ten-year incident AF was identified via linkage with the national registers. Glomerular filtration rate (eGFR) (ml/min/1.73 m

resultsOver a mean follow-up of 9.4 years, 10,007 (3.2%) incident AF cases occurred. After adjusting for age, sex, cardiovascular diseases, total cholesterol, triglycerides, and glucose, individuals with low eGFR (< 30 and 30-59 ml/min/1.73 m

conclusionUric acid largely accounted for the relationship between eGFR and AF in this study. However, in individuals without hyperuricemia, eGFR in the lowest range (< 30 ml/min/1.73 m

Indexed as

Atrial FibrillationBiomarkersGlomerular Filtration RateHyperuricemiaKidneyUric AcidAgedCreatinineFemaleHumansIncidenceKidney DiseasesMaleMiddle AgedRegistriesRisk AssessmentBiomarkersCreatinineUric AcidAtrial fibrillationCohort studyHyperuricemiaKidney functionUric acid

Identifiers

PMID39438792
PMCPMC11494868

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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.