ReviewDer Internist2022
[Mobile health for detection of atrial fibrillation-Status quo and perspectives].
Review in Der Internist, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Advancing cardiac arrhythmia management: The integration of wearable technology and remote monitoring.World journal of cardiology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mobile health (mHealth) for the detection of atrial fibrillation is an innovative domestic monitoring of the heart rhythm. The use of mHealth in the context of atrial fibrillation increases the availability of diagnostic technologies and facilitates the integration into telemedical treatment concepts as well as the active participation of patients in the treatment process. The detection of atrial fibrillation with mHealth applications is usually based on electrocardiography (ECG) or by detection of the pulse wave using photoplethysmography (PPG). Some applications require additional sensors, others make use of sensors integrated into smartphones or smartwatches. A high diagnostic accuracy for the detection of atrial fibrillation has been shown for most mHealth applications regardless of the underlying technology (analytical validation); however, the evidence on positive care effects and improvement of medical endpoints (clinical validation) is so far scarce. Screening of symptomatic or asymptomatic patients and the follow-up care after antiarrhythmic measures are possibilities for the integration into the reality of care. The preventive detection of atrial fibrillation is an attractive field of application for mHealth with great potential for the future. Nevertheless, at present mHealth is only integrated to a limited extent into the reality of patient care. Adequate reimbursement and medical remuneration as well as opportunities to derive information and qualification are prerequisites in order to be able to guarantee a comprehensive implementation in the future. The Digital Health Care Act passed in 2019, regulates the reimbursement of digital healthcare applications but issues of primary preventive applications have not yet been included.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.