Evidence map›Paper›PMID 41310617›Full record

ArticleBMC public health2025

Fasting plasma glucose trajectories are associated with ischemic stroke in the elderly: a longitudinal study using group-based trajectory modeling in Chinese communities.

Qingwen Zhao, Ling Zhang, Xia Jiang, Xingyue Li, Xin Chen, Tianpei Ma, Xinyang Dui, Liang Lv, Xingyu Zhang, Haiyu Yan and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

18 authors.

Qingwen Zhao *Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Ling Zhang *Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Xia JiangDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Xingyue LiDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Xin ChenDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Tianpei MaDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Xinyang DuiDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Liang LvDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Xingyu ZhangDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Haiyu YanDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Wanting FengDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Huifang YangDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Jinyu XiaoDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Lu LongDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Jiaqiang LiaoDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Tao ZhangDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Yuqin YaoDepartment of Occupational and Environmental Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China.
Jiayuan LiDepartment of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China. lijiayuan@scu.edu.cn.

Funding

Sichuan Science and Technology Program 2024NSFSC0050the Science Fund for Creative Research Groups of the Science and Technology Bureau of Sichuan Province 2024NSFTD0030
6 · The paper itself

Abstract

backgroundIschemic stroke (IS) has emerged as a severe health concern, particularly among the elderly. Although baseline fasting plasma glucose (FPG) has been linked to IS, research on the relationship between longitudinal FPG and IS risk is scarce. We aimed to investigate the association between FPG trajectories and IS incidence among the elderly using group-based trajectory modeling (GBTM).

methodsThis longitudinal study in China enrolled 9,426 elderly individuals aged 65 and above, who had participated in health check-ups from 2017 to 2022. Employing a multivariable Cox proportional hazards regression model, we investigated the link between baseline FPG and IS incidence. GBTM was used to identify FPG trajectory patterns from the longitudinal data, which were then correlated with IS risk through further multivariable Cox regression analysis. We also performed stratified analyses and sensitivity analyses to explore these associations.

resultsDiabetes FPG level in elderly individuals was significantly associated with an increased risk of IS at baseline, as indicated by both WHO criteria and ADA criteria. Longitudinal analysis revealed that individuals in the moderate increasing group and high stable group had 1.28 times (HR = 1.28, 95% CI 1.01‒1.62, P < 0.05) and 1.60 times (HR = 1.60, 95% CI 1.20‒2.15, P < 0.05) higher risks of IS, respectively, compared to the low stable group.

conclusionsRegular health screenings should emphasize monitoring FPG trends among the elderly to aid in IS prevention. Public health efforts targeting impaired fasting glucose control may reduce the risk of IS.

Indexed as

Blood GlucoseFastingIschemic StrokeAgedAged, 80 and overChinaEast Asian PeopleFemaleHumansIncidenceLongitudinal StudiesMaleRisk FactorsBlood GlucoseElderly populationFasting plasma glucoseIschemic strokeStroke

Identifiers

PMID41310617
PMCPMC12751438

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.