Evidence map›Paper›PMID 39446718›Full record

ArticlePloS one2024

Prevalence and determinants of prehospital delay among stroke patients in mainland China: A systematic review and meta-analysis of the study protocol.

Hui Deng, Xiangming Wang, Li Yin, Xianzhi Li, Yuehui Zhang

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Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper 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

5 authors.

Hui DengNorth Sichuan Medical University, Nanchong, China.
Xiangming WangDepartment of Neurology, Panzhihua Central Hospital, Panzhihua, China.
Li YinMeteorological Medical ResearchCentre, Panzhihua Central Hospital, Panzhihua, China.
Xianzhi LiMeteorological Medical ResearchCentre, Panzhihua Central Hospital, Panzhihua, China.ORCID 0000-0001-5727-9741
Yuehui ZhangDepartment of Neurology, Panzhihua Central Hospital, Panzhihua, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrehospital delay is one of the most serious problems in the treatment of stroke patients. In China, although hospitals at all levels have promoted the construction of stroke centers, pre-hospital delays are still very common. As the primary cause of death and disability, stroke not only brings great harm to patients themselves, but also brings a heavy burden on social progress and economic development, it is important to understand the prevalence and determinants of prehospital delay among stroke patients. Therefore, this review aims to determine the pooled prevalence and determinants of prehospital delay in mainland China.

methodsA systematic review of eligible articles will be conducted using preferred reporting items for systematic reviews and meta-analysis (PRISMA) guidelines. A comprehensive literature search will be conducted in PubMed, Embase, Cochrane, web of science, China National Knowledge Infrastructure (CNKI), Wanfang, Weipu (VIP) and Chinese Biomedicine Iiterature databas (CBM) databases. The quality of the articles included in the review will be evaluated using the Newcastle-Ottawa Scale (NOS). The pooled prevalence of prehospital delay, and odds ratio and their 95% confidence intervals for relevant influencing factors, will be calculated using RevMan 5.3 software. The existence of heterogeneity among studies will be assessed by computing p-values of Higgins's I2 test statistics and Cochran's Q-statistics. Sensitivity analysis and subgroup analysis will be conducted based on study quality to investigate the possible sources of heterogeneity. Publication bias will be evaluated by funnel chart and by Egger's regression test. This review protocol has been registered PROSPERO (CRD42023484580). DISCUSSION: By collecting and summarizing information on prehospital delay among stroke patients can be a step towards a better understanding of the prevalence of prehospital delay among stroke patients in mainland China and how the associated factors influence the prevalence of prehospital delay. Therefore, a rapid, accurate diagnosis Stroke, timely pre-hospital first aid, the treatment process forward, for the patient It has great significance. This summarized finding at the national level will provide new clues for intervention to reduce the rate of pre-hospital delay of stroke patients, and is expected to further improve the treatment effect of stroke patients.

Indexed as

Emergency Medical ServicesStrokeChinaHumansMeta-Analysis as TopicPrevalenceSystematic Reviews as TopicTime-to-Treatment

Identifiers

PMID39446718
PMCPMC11500912

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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.