Evidence map›Paper›PMID 41894417›Full record

ArticleJMIR formative research2026

Development of a Novel Mobile App on Emergency Management Among Patients With Acute Ischemic Stroke at County-Level Hospitals in China.

Qikai Wang, Conghua Fan, Yan Gu, Wen Zuo, Hu Lv, Danyang Yang, Libing Yun, Zhi Yan

Abstract read
In one paragraph

Article in JMIR formative research, 2026. 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. Article
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

8 authors.

Qikai Wang *West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, No. 17, Section 3, Renmin South Road, Chengdu, 610044, China, 86 13880613969.ORCID 0009-0005-4834-8932
Conghua Fan *Xichang People's Hospital, Xichang, China.ORCID 0009-0003-3217-1496
Yan GuWest China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, No. 17, Section 3, Renmin South Road, Chengdu, 610044, China, 86 13880613969.ORCID 0000-0001-7241-2440
Wen ZuoXichang People's Hospital, Xichang, China.ORCID 0009-0006-2636-2028
Hu LvXichang People's Hospital, Xichang, China.ORCID 0009-0001-0248-8148
Danyang YangSchool of Medical Technology, Sichuan College of Traditional Chinese Medicine, No.1, Education Middle Road, Miangyang, 621000, China, 86 13681482661.ORCID 0009-0003-0860-5645
Libing Yun *West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, No. 17, Section 3, Renmin South Road, Chengdu, 610044, China, 86 13880613969.ORCID 0000-0003-2613-603X
Zhi Yan *School of Medical Technology, Sichuan College of Traditional Chinese Medicine, No.1, Education Middle Road, Miangyang, 621000, China, 86 13681482661.ORCID 0009-0008-3881-5471

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlabelled: This retrospective study of 428 patients with acute ischemic stroke at a county-level hospital in China found that implementing the Xheart novel mobile app significantly reduced the median door-to-needle time from 52 to 38 minutes (P<.001) and was associated with lower National Institutes of Health Stroke Scale scores 24 hours after thrombolysis (P=.02), indicating the potential of mobile health technologies to improve the emergency management of patients with acute ischemic stroke in resource-constrained settings.

Indexed as

Emergency Medical ServicesIschemic StrokeMobile ApplicationsAgedChinaFemaleHospitals, CountyHumansMaleMiddle AgedRetrospective Studiesacute ischemic strokecounty-level hospitalsdoor to needle timeemergency managementmobile app

Identifiers

PMID41894417
PMCPMC13026424

What OpenQuestion holds

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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 OpenQuestion graph.