Evidence map›Paper›PMID 38686862›Full record

ArticleJournal of the American Heart Association2024

Sleep Patterns and Traditional Cardiovascular Health Metrics: Joint Impact on Major Adverse Cardiovascular Events in a Prospective Cohort Study.

Si You, Hai-Feng Zhang, Shao-Ling Zhang, Qing-Yuan Gao, Yang-Wei Cai, Ze-Gui Huang, Yu-Biao Wu, Yang-Xin Chen, Jing-Feng Wang, Jing-Wei Gao and 1 more

Abstract read
In one paragraph

Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Longitudinal Psychosocial and Sleep Assessments for Long-Term Cardiovascular Risk Stratification after First Myocardial Infarction in Rural India.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. 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

11 authors.

Si YouDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0002-6436-9187
Hai-Feng ZhangDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0003-1671-3315
Shao-Ling ZhangDepartment of Endocrinology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0002-9906-5474
Qing-Yuan GaoDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0001-9452-6289
Yang-Wei CaiDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0002-9804-3302
Ze-Gui HuangDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.
Yu-Biao WuDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.
Yang-Xin ChenDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.ORCID 0000-0003-2051-9320
Jing-Feng WangDepartment of Cardiology, Sun Yat-sen Memorial Hospital Sun Yat-sen University Guangzhou China.
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

backgroundThis study examines the association between traditional cardiovascular health (CVH) metrics and major adverse cardiovascular events (MACE) incidence in individuals with diverse sleep patterns. METHODS AND

resultsWe analyzed data from 208 621 participants initially free of cardiovascular disease (CVD) in the UK Biobank study. Sleep patterns were assessed using scores for chronotype, duration, insomnia, snoring, and daytime dozing. Traditional CVH scores were derived from the Life's Simple 7 metrics. Cox proportional hazards multivariate regression assessed associations between distinct combinations of CVH and sleep scores and MACE, including nonfatal myocardial infarction, nonfatal stroke, and CVD mortality. Over a mean follow-up of 12.73 years, 9253 participants experienced incident MACE. Individuals with both a healthy sleep pattern and ideal CVH levels had the lowest MACE risk compared with those with a poor sleep pattern and poor CVH levels (hazard ratio, 0.306 [95% CI, 0.257-0.365];

conclusionsIn individuals without known CVD, maintaining a favorable sleep pattern and achieving optimal CVH levels, as measured by traditional metrics, were associated with the lowest MACE risk. Enhanced CVH significantly reduced CVD risk, even in individuals with a poor sleep pattern. These results emphasize the importance of considering multiple dimensions of sleep health alongside CVH to mitigate CVD risk. REGISTRATION: URL: https://www.ukbiobank.ac.uk; Unique identifier: 91090.

Indexed as

Cardiovascular DiseasesSleepAdultAgedFemaleHealth StatusHeart Disease Risk FactorsHumansIncidenceMaleMiddle AgedProspective StudiesRisk AssessmentRisk FactorsSleep QualityTime Factorscardiovascular diseasecardiovascular healthLife's Simple 7major adverse cardiovascular eventssleep patterns

Identifiers

PMID38686862
PMCPMC11179879

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.