Evidence map›Paper›PMID 38783249›Full record

ArticleBMC neurology2024

Gender differences in risk factors for ischemic stroke: a longitudinal cohort study in East China.

Xinping Bai, Zifeng Li, Zhuo Cai, Mingren Yao, Lin Chen, Youmeng Wang

Abstract read
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Article in BMC neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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.

Xinping Bai *Department of Neurology, Fuyang People's Hospital, Anhui, 236000, People's Republic of China.
Zifeng Li *Department of Neurology, Fuyang People's Hospital, Anhui, 236000, People's Republic of China.
Zhuo CaiDepartment of Neurology, Fuyang Hospital Affiliated to Bengbu Medical University, Anhui, 236000, People's Republic of China.
Mingren YaoDepartment of Neurology, Fuyang People's Hospital, Anhui, 236000, People's Republic of China.
Lin ChenDepartment of Neurology, Fuyang People's Hospital, Anhui, 236000, People's Republic of China.
Youmeng WangDepartment of Neurology, Fuyang People's Hospital, Anhui, 236000, People's Republic of China. 3527743266@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesEpidemiological studies of stroke and its risk factors can help develop strategies to prevent stroke. We aimed to explore the current gender-specific prevalence of stroke and associated risk factors.

methodsData were collected using a structured precoded questionnaire designed by the Stroke Screening and Prevention Programme of the National Health and Wellness Commission Stroke Prevention and Control Project Committee, between June 2020 and November 2021. A total of 7394 residents took part in the study, 187 of whom had a stroke. The baseline information of each participant was obtained and included in this study. The chi-square test and Kruskal-Wallis tests were used to examine the relationship between these indicators and stroke, and then multivariate logistic regression was used to construct the prediction scale between different genders.

resultsof 7394 participants,4571 (61.82%) were female. The overall prevalence of stroke patients in the study population was 2.53%, Multivariate analysis found that residence status (OR = 0.43, p = 0.002) 、HCY (OR = 0.962, p = 0.000)、Previous TIA (OR = 0.200, p = 0.002) 、Hypertension (OR = 0.33, p = 0.000) and Dyslipidemia (OR = 0.668, p = 0.028) were significant predictors of stroke. there are gender differences in the traditional risk factors for stroke, and women have more risk factors. ROC analysis confirmed the accuracy of the stroke risk model, and the AUC of the stroke risk model for the general population was 0.79 with p < 0.05. In the gender model, the female AUC was 0.796 (p < 0.05). and the male AUC was 0.786 with p < 0.05.

conclusionThe prevalence of stroke in adults aged 40 years and above is high in eastern China were high. management of risk factors can effectively prevent the occurrence of most strokes. more attention should be paid to gender differences associated with stroke.

Indexed as

Ischemic StrokeAdultAgedChinaCohort StudiesFemaleHumansHypertensionLongitudinal StudiesMaleMiddle AgedPrevalenceRisk FactorsSex CharacteristicsSex FactorsGenderPrevalenceRisk factorsRoc analysisStroke

Identifiers

PMID38783249
PMCPMC11112765

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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.