Evidence map›Paper›PMID 40395423›Full record

ArticleEuropean heart journal. Digital health2025

Evaluation of real-world application of cardiac implantable electronic device-based multi-sensor algorithm for heart failure management.

Jennifer Llewellyn, Rachel Goode, Matthew Kahn, Sergio Valsecchi, Archana Rao

Abstract read
In one paragraph

Article in European heart journal. Digital health, 2025. 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

5 authors.

Jennifer LlewellynDepartment of Cardiology, Liverpool Heart and Chest Hospital, Liverpool L14 3PE, UK.ORCID https://orcid.org/0000-0002-9217-2015
Rachel GoodeDepartment of Cardiology, Liverpool Heart and Chest Hospital, Liverpool L14 3PE, UK.
Matthew KahnDepartment of Cardiology, Liverpool Heart and Chest Hospital, Liverpool L14 3PE, UK.
Sergio ValsecchiBoston Scientific, Viale Forlanini, 23, Milan 20134, Italy.ORCID https://orcid.org/0000-0001-7055-6942
Archana RaoDepartment of Cardiology, Liverpool Heart and Chest Hospital, Liverpool L14 3PE, UK.ORCID https://orcid.org/0000-0002-3893-3944

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Remote monitoring of cardiac implantable electronic devices enables pre-emptive management of heart failure (HF) without additional patient engagement. The HeartLogic™ algorithm in implantable cardioverter defibrillators (ICDs) combines physiological parameters to predict HF events, facilitating earlier interventions. This study evaluated its diagnostic performance and resource implications within an HF management service. Methods and results: In a single-centre study, 212 patients with cardiac resynchronization therapy ICDs (CRT-Ds) were monitored for 12-months. During follow-up, 18 (8%) patients died, and 15 HF hospitalizations occurred in 13 (6%) patients. Outpatient visits totalled 37 in 34 (16%) patients. HeartLogic™ alerts occurred in 58% of patients, with 100% sensitivity for HF-related hospitalizations. The positive predictive value was 29% including only alerts associated with HF events, while it was 51% including HF events and explained alerts. Unexplained alert rate was 0.46 per patient-year. Clinical interventions, mainly medication adjustments, followed 82 alerts. Total management time was 257 h/year, equivalent to 0.57 full-time equivalents for managing 1000 CRT-D patients. Conclusion: The integration of HeartLogic™ into routine care demonstrated its utility in optimizing HF management, improving healthcare resource allocation. The algorithm can enhance proactive patient management and provide holistic care within the existing healthcare infrastructure.

Indexed as

CRTHeart failureRemote monitoringRisk stratification

Identifiers

PMID40395423
PMCPMC12088722

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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.