Evidence map›Paper›PMID 40029281›Full record

ArticleJMIR formative research2025

Assessment of the Sensitivity of a Smartphone App to Assist Patients in the Identification of Stroke and Myocardial Infarction: Cross-Sectional Study.

Amar Dhand, Rama Mangipudi, Anubodh S Varshney, Jonathan R Crowe, Andria L Ford, Nancy K Sweitzer, Min Shin, Samuel Tate, Haissam Haddad, Michael E Kelly and 2 more

Abstract read
In one paragraph

Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

12 authors.

Amar DhandDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, 65 Landsdowne Street, Cambridge, MA, 02139, United States, 1 617 732 5330.ORCID 0000-0001-6470-7548
Rama MangipudiDivision of Cardiology, Department of Medicine, Unversity of Saskatchewan, Saskatoon, SK, Canada.ORCID 0009-0009-7483-2006
Anubodh S VarshneyDivision of Cardiovascular Medicine, Department of Medicine, Stanford University, Palo Alto, CA, United States.ORCID 0000-0002-9697-8948
Jonathan R CroweDepartment of Neurology, University of Virgina, Charlottesville, VA, United States.ORCID 0000-0003-3670-5566
Andria L FordDepartment of Neurology, Washington University School of Medicine, St. Louis, MO, United States.ORCID 0000-0003-0605-8943
Nancy K SweitzerDivision of Cardiology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States.ORCID 0000-0002-8117-6678
Min ShinDepartment of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, United States.ORCID 0000-0002-5205-9552
Samuel TateDepartment of Computer Science, University of North Carolina at Charlotte, Charlotte, NC, United States.ORCID 0009-0009-6456-9128
Haissam HaddadDivision of Cardiology, Department of Medicine, Unversity of Saskatchewan, Saskatoon, SK, Canada.ORCID 0000-0003-4821-3577
Michael E KellyDivision of Neurosurgery, Department of Surgery, University of Saskatchewan, Saskatoon, SK, Canada.ORCID 0000-0002-3278-2620
James MullerDivision of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.ORCID 0000-0002-4427-2871
Jay S ShavadiaDivision of Cardiology, Department of Medicine, Unversity of Saskatchewan, Saskatoon, SK, Canada.ORCID 0000-0001-9733-4485

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Most people do not recognize symptoms of neurological and cardiac emergencies in a timely manner. This leads to delays in hospital arrival and reduced access to therapies that can open arteries. We created a smartphone app to help patients and families evaluate if symptoms may be high risk for stroke or heart attack (myocardial infarction, MI). The ECHAS (Emergency Call for Heart Attack and Stroke) app guides users to assess their risk through evidence-based questions and a test of weakness in one arm by evaluating finger-tapping on the smartphone. Objective: This study is an initial step in the accuracy evaluation of the app focused on sensitivity. We evaluated whether the app provides appropriate triage advice for patients with known stroke or MI symptoms in the Emergency Department. We designed this study to evaluate the sensitivity of the app, since the most dangerous output of the app would be failure to recognize the need for emergency evaluation. Specificity is also important, but the consequences of low specificity are less dangerous than those of low sensitivity. Methods: In this single-center cross-sectional study, we enrolled patients presenting with symptoms of possible stroke or MI. The ECHAS app assessment consisted of a series of evidence-based questions regarding symptoms and a test of finger-tapping speed and accuracy on the phone's screen to detect unilateral arm weakness. The primary outcome was the sensitivity of the ECHAS app in detecting the need for ED evaluation. The secondary outcome was the sensitivity of the ECHAS app in detecting the need for hospital admission. Two independent and blinded board-certified physicians reviewed the medical record and adjudicated the appropriateness of the ED visit based on a 5-point score (ground truth). Finally, we asked patients semistructured questions about the app's ease of use, drawbacks, and benefits. Results: We enrolled 202 patients (57 with stroke and 145 with MI). The ECHAS score was strongly correlated with the ground truth appropriateness score (Spearman correlation 0.41, P<.001). The ECHAS app had a sensitivity of 0.98 for identifying patients in whom ED evaluation was appropriate. The app had a sensitivity of 1.0 for identifying patients who were admitted to the hospital because of their ED evaluation. Patients completed an app session in an average of 111 (SD 60) seconds for the stroke pathway and 60 (SD 33) seconds for the MI pathway. Patients reported that the app was easy to use and valuable for personal emergency situations at home. Conclusions: The ECHAS app demonstrated a high sensitivity for the detection of patients who required emergency evaluation for symptoms of stroke or MI. This study supports the need for a study of specificity of the app, and then a prospective trial of the app in patients at increased risk of MI and stroke.

Indexed as

Mobile ApplicationsMyocardial InfarctionSmartphoneStrokeAdultAgedCross-Sectional StudiesEmergency Service, HospitalFemaleHumansMaleMiddle AgedSensitivity and SpecificityTriageaccuracyappscross-sectional studydigital healtheHealth appsemergency departmentfinger-tapping testheart attackhospital admissionmedical recordsmhealthmobile healthmobile phonemyocardial infarctionneurological assessmentneurologypatient-centered carephysicianssmartphonesstrokesymptom recognitiontime-to-treatment

Identifiers

PMID40029281
PMCPMC11892415

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Registered trials

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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.