Evidence map›Paper›PMID 37723974›Full record

ArticleEuropean heart journal2023

Acquired risk factors and incident atrial fibrillation according to age and genetic predisposition.

Ningjian Wang, Yuefeng Yu, Ying Sun, Haojie Zhang, Yuying Wang, Chi Chen, Xiao Tan, Bin Wang, Yingli Lu

Open access · hybridAbstract readComment
In one paragraph

Article in European heart journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
17.8field-weighted citation impact, top 1% 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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.

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  12. Common Methylenetetrahydrofolate Reductase PolymorphismDiagnostics (Basel, Switzerland) · 2025
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  13. Dynamic Increase of the CJournal of the American Heart Association · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 2 countries.

Ningjian WangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China.ORCID 0000-0001-9591-6991
Yuefeng YuInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China.ORCID 0000-0001-7439-4231
Ying SunInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China.ORCID 0000-0002-8529-3521
Haojie ZhangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China.
Yuying WangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China.
Chi ChenInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China.ORCID 0000-0001-8277-0268
Xiao TanSchool of Public Health, Zhejiang University, Hangzhou, China.ORCID 0000-0003-3992-5812
Bin WangInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China.ORCID 0000-0002-4869-1352
Yingli LuInstitute and Department of Endocrinology and Metabolism, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, No. 639 Zhizaoju Road, Huangpu District, Shanghai 200011, China.ORCID 0000-0002-5117-1614
Shanghai Jiao Tong University · CNUppsala University · SE

Funding

Clinical Research Plan of SHDC SHDC2020CR4006Innovative Research Team of High-level Local Universities in Shanghai SHSMU-ZDCX20212501Shanghai Municipal Health Commission 2022XD017Shanghai Municipal Human Resources and Social Security Bureau 2020074UK Biobank Resource
6 · The paper itself

Abstract

BACKGROUND AND

aimsAtrial fibrillation (AF) is the most common sustained arrhythmia in adults. Investigations of risk factor profiles for AF according to age and genetic risk groups are essential to promote individualized strategies for the prevention and control of AF.

methodsA total of 409 661 participants (mean age, 56 years; 46% men) free of AF at baseline and with complete information about risk factors were included from the UK Biobank cohort. The hazard ratios and population-attributable risk (PAR) percentages of incident AF associated with 23 risk factors were examined, including 3 social factors, 7 health behaviours, 6 cardiometabolic factors, 6 clinical comorbidities, and the genetic risk score (GRS), across 3 age groups (40-49, 50-59, and 60-69 years) and 3 genetic risk groups (low, moderate, and high GRS).

resultsAfter a follow-up of 5 027 587 person-years, 23 847 participants developed AF. Most cardiometabolic factors and clinical comorbidities showed a significant interaction with age, whereby the associations were generally strengthened in younger groups (Pinteraction < .002). However, only low LDL cholesterol, renal dysfunction, and cardiovascular disease showed a significant interaction with genetic risk, and the associations with these factors were stronger in lower genetic risk groups (Pinteraction < .002). Cardiometabolic factors consistently accounted for the largest number of incident AF cases across all age groups (PAR: 36.2%-38.9%) and genetic risk groups (34.0%-41.9%), with hypertension and overweight/obesity being the two leading modifiable factors. Health behaviours (PAR: 11.5% vs. 8.7%) and genetic risk factors (19.1% vs. 14.3%) contributed to more AF cases in the 40-49 years group than in the 60-69 years group, while the contribution of clinical comorbidities remained relatively stable across different age groups. The AF risk attributable to overall cardiometabolic factors (PAR: 41.9% in the low genetic risk group and 34.0% in the high genetic risk group) and clinical comorbidities (24.7% and 15.9%) decreased with increasing genetic risk. The impact of social factors on AF was relatively low across the groups by age and genetic risk.

conclusionsThis study provided comprehensive information about age- and genetic predisposition-related risk factor profiles for AF in a cohort of UK adults. Prioritizing risk factors according to age and genetic risk stratifications may help to achieve precise and efficient prevention of AF.

Indexed as

Atrial FibrillationAdultComorbidityFemaleGenetic Predisposition to DiseaseHumansIncidenceMaleMiddle AgedRisk FactorsAgeAtrial fibrillationGenetic riskRisk profileUK Biobank

Identifiers

PMID37723974
PMCPMC10719493
OpenAlexW4386843137

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.