Evidence map›Paper›PMID 40547435›Full record

ArticleDigital health

Continuous heart rate measurements in patients with cardiac disease: Device comparison and development of a novel artefact removal procedure.

Paulien Vermunicht, Katsiaryna Makayed, Christophe Buyck, Lieselotte Knaepen, Juan Sebastian Piedrahita Giraldo, Sebastiaan Naessens, Wendy Hens, Emeline Van Craenenbroeck, Kris Laukens, Lien Desteghe and 1 more

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
–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

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. 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

11 authors.

Paulien VermunichtResearch Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0000-0001-5922-2095
Katsiaryna MakayedDepartment of Computer Science, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0009-0004-2704-9530
Christophe BuyckResearch Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0009-0005-4214-9932
Lieselotte KnaepenResearch Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0000-0003-2816-1896
Juan Sebastian Piedrahita GiraldoDepartment of Computer Science, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0000-0002-1691-2915
Sebastiaan NaessensDepartment of Cardiology, Antwerp University Hospital, Antwerp, Belgium.ORCID https://orcid.org/0009-0006-9395-2271
Wendy HensDepartment of Cardiology, Antwerp University Hospital, Antwerp, Belgium.ORCID https://orcid.org/0000-0002-9881-6248
Emeline Van CraenenbroeckResearch Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0000-0001-7686-2668
Kris LaukensDepartment of Computer Science, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0000-0002-8217-2564
Lien DestegheResearch Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0000-0001-8641-4658
Hein HeidbuchelResearch Group Cardiovascular Diseases, University of Antwerp, Antwerp, Belgium.ORCID https://orcid.org/0000-0001-9301-8127

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Heart rate (HR) monitors could objectively measure physical activity intensity in patients with cardiac disease. However, thorough validation of HR monitors in cardiac populations during daily life, compared to gold-standard Holter monitoring, remains limited. Photoplethysmography (PPG)-based HR data provides near-continuous data, spanning longer periods, but improved algorithms to filter unreliable data are needed. Methods: This observational, prospective pilot study compared the accuracy of two wearables for HR monitoring (electrocardiogram [ECG]-based Polar H10 chest strap and PPG-based Fitbit Inspire 2 wrist tracker) against Holter monitoring in 15 patients with atrial fibrillation (AF), heart failure (HF) and coronary artery disease referred for cardiac rehabilitation (CR). All devices were worn simultaneously for 24 h. We developed and assessed an artefact removal procedure (ARP) using logistic regression machine learning models to detect unreliable PPG data. Results: The ECG-based chest strap showed a strong correlation ( Conclusions: While ECG-based monitors provide HR data with clinical acceptable accuracy, PPG-based monitors present accuracy challenges. Our machine learning procedure showed potential to filter unreliable PPG-based HR data, which could help measure physical activity intensity in cardiac disease continuously.

Indexed as

cardiac rehabilitationExercisefitness trackersheart ratemachine learningwearable electronic devices

Identifiers

PMID40547435
PMCPMC12179456

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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.