Evidence map›Paper›PMID 40611497›Full record

ArticleJournal of the American Heart Association2025

Interplay of Acquired Risk Factors, Age, and Genetic Predisposition in Incident Stroke: A Prospective Cohort Study.

Yu-Biao Wu, Ze-Gui Huang, Wan-Bing He, Si You, Shao-Ling Zhang, Yang-Wei Cai, Yuan-Li Meng, Qing-Yuan Gao, Jing-Feng Wang, Hai-Feng Zhang and 2 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

12 authors.

Yu-Biao WuDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.
Ze-Gui HuangDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.
Wan-Bing HeDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0001-5892-9822
Si YouDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0002-6436-9187
Shao-Ling ZhangDepartment of Endocrinology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0002-9906-5474
Yang-Wei CaiDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0002-9804-3302
Yuan-Li MengDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.
Qing-Yuan GaoDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0001-9452-6289
Jing-Feng WangDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0002-5827-7876
Hai-Feng ZhangDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0003-1671-3315
Jing-Wei GaoDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0001-7917-2806
Pin-Ming LiuDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0002-4142-6863

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStroke is the leading cause of disability and death worldwide, and its pathogenesis involves various risk factors. This study aimed to investigate the associations between acquired risk factors, age, and genetic predisposition in the incidence of stroke. METHODS AND

resultsWe analyzed 404 873 participants (age, mean±SD, 56.46±8.10 years; 45.97% men) from the UK Biobank cohort, all without a history of stroke at baseline and with complete information on risk factors. Hazard ratios and population-attributable risk percentages for incident stroke were calculated for 21 risk factors, including 3 social determinants, 8 unhealthy behaviors, 4 metabolic factors, 5 clinical comorbidities, and 1 genetic risk score. Participants were stratified by age and genetic risk. During a 4.8 million person-year follow-up, 8287 participants (2.05%) experienced a stroke. Metabolic factors, particularly hypertension, were key contributors to stroke risk across all age and genetic groups (population-attributable risk percentages, 26.53-38.63 and 28.05-37.09). Stroke risk due to overall metabolic factors increased with higher genetic risk (population-attributable risk percentages, 28.05 in low-risk and 37.09 in high-risk groups). The effects of certain risk factors, such as dietary risk and hypertension, were more pronounced in participants with higher genetic risk. The contributions of social factors and clinical comorbidities to stroke risk were relatively low across genetic risk groups.

conclusionsMetabolic factors, especially hypertension, are critical targets for stroke prevention across diverse age and genetic risk profiles. Tailored prevention strategies that address modifiable risk factors, considering individual age and genetic predisposition, have the potential to significantly reduce stroke incidence.

Indexed as

Genetic Predisposition to DiseaseStrokeAdultAgedAge FactorsComorbidityFemaleHumansIncidenceMaleMiddle AgedProspective StudiesRisk AssessmentRisk FactorsUnited Kingdomagegenetic predispositionhypertensionrisk factorsstroke

Identifiers

PMID40611497
PMCPMC12533630

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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.