Evidence map›Paper›PMID 41407406›Full record

ArticleBMJ open2025

Real-world analysis and future trends of stroke-related mortality and burden in Pudong: a comprehensive study from 2005 to 2035.

Zheng Luo, Chunyan Kuang, Yan Zhang, Yichen Chen, Wenchang Jia, Xiaoling Wu, Mengcen Qian, Huihui Lv, Xiaopan Li

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Zheng Luo *Department of Neurology, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Chunyan Kuang *Department of Rehabilitation, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China.
Yan Zhang *Department of Neurology, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Yichen ChenOffice of Scientific Research and Information Management, Centre for Disease Control and Prevention, Shanghai, China.
Wenchang JiaSchool of Public Health, Fudan University, Shanghai, China.
Xiaoling WuDepartment of Health Management Center, Zhongshan Hospital, Shanghai Medical College of Fudan University, Shanghai, China.
Mengcen QianSchool of Public Health, Fudan University, Shanghai, China xiaopanli0224@126.com lvhuihui@shutcm.edu.cn qianmengcen@fudan.edu.cn.
Huihui LvDepartment of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China xiaopanli0224@126.com lvhuihui@shutcm.edu.cn qianmengcen@fudan.edu.cn.
Xiaopan LiDepartment of Health Management Center, Zhongshan Hospital, Shanghai Medical College of Fudan University, Shanghai, China xiaopanli0224@126.com lvhuihui@shutcm.edu.cn qianmengcen@fudan.edu.cn.ORCID http://orcid.org/0000-0002-9625-478X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesStroke is a major global health issue with rising incidence in China. Current estimates often focus on specific deaths, underestimating their impact. This study aimed to quantify and predict the all-cause and cause-specific burden of stroke using real-world data.

designPopulation-based study. PARTICIPANTS AND

settingResidents in Shanghai Pudong, which covers an area of 1210.41 km² (467.34 mi²) and has a population of 3.17 million, spanning from 2005 to 2021. OUTCOMES: Stroke-related deaths in Pudong (2005-2021) were analysed by gender, age and subtype. Metrics included crude mortality rates (CMR), age-standardised mortality rates (ASMRW) and years of life lost (YLL). The Joinpoint Regression Programme determined average annual per cent change (AAPC), while the decomposition method assessed ageing's impact. The AutoRegressive Integrated Moving-Average (ARIMA) model projected trends from 2022 to 2035.

resultsAmong the 92 779 stroke-related deaths, the top three causes were stroke, heart disease and diabetes mellitus. From 2005 to 2021, the CMR for stroke-related deaths (AAPC=1.65%), stroke-specific deaths (AAPC=0.60%) and YLL rates (AAPC=0.36%) increased significantly (all p<0.05), and the ASMRW of both stroke-related and stroke-specific deaths showed significant decreases among males, females and the total population (all p<0.05). The proportion of stroke-related or specific deaths in individuals aged 60-69 and ≥80 years also increased significantly (all p<0.001). Ageing contributed to a 36.95% and 35.54% increase in CMR for stroke-related and stroke-specific deaths, respectively (all p<0.001). Projections indicate that from 2022 to 2035, the CMR for stroke-specific deaths will rise at an AAPC of 0.24%, reaching 141.96 per 100 000 by 2035 (p=0.008), while the CMR for stroke-related deaths will increase at an AAPC of 0.69%, reaching 235.44 per 100 000 by 2035 (p<0.001).

conclusionStroke's real-world burden is substantial, with ageing exacerbating mortality. Urgent action is needed to manage risk factors and prevent stroke.

Indexed as

StrokeAdultAgedAged, 80 and overAge DistributionCause of DeathChinaCost of IllnessDiabetes MellitusFemaleForecastingHumansLife ExpectancyMaleMiddle AgedMortalityAgingEpidemiologyMortalityStroke

Identifiers

PMID41407406
PMCPMC12716573

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.