Evidence mapPaperPMID 37264382Full record

ArticleBMC public health2023

Association of cardiovascular health score trajectory and risk of subsequent cardiovascular disease in non-diabetic population: a cohort study.

Hui Zhou, Xiong Ding, Shouling Wu, Jin Yan, Jianyun Cao

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. 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
1.1field-weighted citation impact, top 21% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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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

5 authors at 3 institutions in 1 country.

Hui ZhouXiangya School of Nursing, Central South University, Changsha, Hunan, China.
Xiong DingSchool of Public Health, Wuhan University, Wuhan, Hubei, China.
Shouling WuDepartment of Cardiology, Kailuan General Hospital, Tangshan, Hebei, China.
Jin YanXiangya School of Nursing, Central South University, Changsha, Hunan, China.
Jianyun CaoDepartment of Reproductive Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China. 296167131@qq.com.
Central South University · CNKailuan General Hospital · CNWuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetes is an important risk factor for cardiovascular disease (CVD), but in the non-diabetic population, high glucose values within the normal range are also positively associated with CVD risk. There is a lack of concern for people without diabetes and evidence is lacking regarding the association between changes in cardiovascular health score (CVHS) and CVD risk in the non-diabetic population.

methodsThe current study included 37,970 non-diabetic participants free of CVD events in or before 2010 from the Kailuan Study and calculated CVHS according to the overall status of 7 cardiovascular health metrics between the 2006 and 2010 waves. Latent mixture models were used to explore the subgroups with different development trends included in the context of the Kailuan non-diabetic population and to identify the trajectory of each subgroup. The outcomes of the current study were CVD events, including myocardial infarction and stroke. CVHS trajectory was developed to predict subsequent CVD risk from 2010 to 2020. The Cox proportional hazard model was established to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) of CVD across different trajectory patterns.

resultsFive distinct CVHS trajectory patterns were identified, including low-stable pattern (n = 2835), moderate-increasing pattern (n = 3492), moderate-decreasing pattern (n = 7526), high-stable I pattern (n = 17,135), and high-stable II pattern (n = 6982). Compared with the low-stable pattern, participants with the high-stable II pattern had a lower subsequent risk of CVD (HR = 0.22, 95%CI = 0.18-0.28); In stratification analysis, the lower risk for CVD was observed in females (HR = 0.10, 95%CI = 0.05-0.23, P for interaction < 0.05) and those aged < 60 years (HR = 0.16, 95%CI = 0.11 to 0.22, P for interaction < 0.05).

conclusionsCVHS trajectory patterns were associated with an altered CVD risk in the non-diabetic population. When stratified by age and sex, the association was stronger in young adults and females.

Indexed as

Cardiovascular DiseasesDiabetes MellitusCohort StudiesFemaleHumansProspective StudiesRisk FactorsYoung AdultCardiovascular diseaseHealth behaviorLongitudinal studyNon-diabetic populationRisk factors

Identifiers

PMID37264382
PMCPMC10233877
OpenAlexW4378983515

What Socratic holds

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LicenceCC BY
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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 Socratic graph.