Evidence map›Paper›PMID 39906073›Full record

ArticleJournal of multidisciplinary healthcare2025

Accuracy of Apple Watch in Measuring 30-Second Resting Electrocardiography in Patients with Cardiac Diseases and Comorbidity: An Observational Cross-Sectional Study.

Alaa Abdulhafiz Khushhal, Ashraf Abdelaal Mohamed, Mohammad Matook Alsegame, Atif Mohammed Alsaedi

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 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. 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

4 authors.

Alaa Abdulhafiz KhushhalDepartment of Medical Rehabilitation Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.ORCID 0000-0003-4690-1042
Ashraf Abdelaal MohamedDepartment of Medical Rehabilitation Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.
Mohammad Matook AlsegameDepartment of Nursing, Umm Al-Qura University Medical Center, Umm Al-Qura University, Makkah, Saudi Arabia.ORCID 0009-0008-0724-8443
Atif Mohammed AlsaediDepartment of Nursing, Umm Al-Qura University Medical Center, Umm Al-Qura University, Makkah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electrocardiography (ECG) is a standard method for studying the heart rate and heart electricity. The Apple Watch has recently been used to measure heart electricity via 30 seconds of ECG monitoring, but its validity is not known. Methods: A cross-sectional study included a sample of 112 patients with chronic disorders, including cardiac patients with sinus rhythm, cardiac patients with irregular heart rhythm, and patients with diabetes, hypertension, and dyslipidemia; their cardiac activity was investigated using the Apple Watch and ECG. Results: The correlations were strong between the Apple Watch and the 12-lead ECG in the heart rate, PR intervals, QT intervals, QRS complex, and RR intervals in all patients' subcategories (cardiac, hypertension, diabetic, and dyslipidemia patients). Conclusion: The Apple Watch is valid for carrying out ECG in measuring the heart rate, PR intervals, QT intervals, QRS complex, and RR intervals of patients with cardiac and chronic diseases at rest; this may help in initial diagnosis for patients with cardiac diseases or those who are at risk of developing cardiac disease in the future.

Indexed as

Apple Watchcardiac diseaseschronic diseaseselectrocardiography

Identifiers

PMID39906073
PMCPMC11790806

What OpenQuestion 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 OpenQuestion graph.