Evidence map›Paper›PMID 39669926›Full record

ArticleJournal of arrhythmia2024

Utility of cardiac implantable electronic device algorithm for detecting severe sleep-disordered breathing in cardiomyopathy.

Jiaqi Li, Yingjuan Mok, Vern Hsen Tan, Hang Siang Wong, Yue Wang, Ying Zi Oh, Ai Ling Him, Sherida Syed Hamid, Prunella Ting Lee, Lisa Jie Ting Teo and 3 more

Abstract read
In one paragraph

Article in Journal of arrhythmia, 2024. 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

13 authors.

Jiaqi LiSchool of Clinical Medicine University of Cambridge Cambridge UK.ORCID https://orcid.org/0000-0002-4807-0978
Yingjuan MokDepartment of Sleep Medicine, Surgery & Science Changi General Hospital Singapore Singapore.
Vern Hsen TanDepartment of Cardiology Changi General Hospital Singapore Singapore.
Hang Siang WongDepartment of Sleep Medicine, Surgery & Science Changi General Hospital Singapore Singapore.
Yue WangDepartment of Cardiology Changi General Hospital Singapore Singapore.ORCID https://orcid.org/0000-0001-7455-6405
Ying Zi OhDepartment of Cardiology Changi General Hospital Singapore Singapore.
Ai Ling HimDepartment of Cardiology Changi General Hospital Singapore Singapore.
Sherida Syed HamidDepartment of Cardiology Changi General Hospital Singapore Singapore.
Prunella Ting LeeClinical Measurement Unit Changi General Hospital Singapore Singapore.
Lisa Jie Ting TeoClinical Measurement Unit Changi General Hospital Singapore Singapore.
Leng Leng LeeClinical Measurement Unit Changi General Hospital Singapore Singapore.
Andrew Kieran Ming Hui ChanSchool of Clinical Medicine University of Cambridge Cambridge UK.
Colin YeoDepartment of Cardiology Changi General Hospital Singapore Singapore.ORCID https://orcid.org/0000-0002-1888-2246

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Half of patients with heart failure are estimated to have sleep-disordered breathing (SDB). However, many are undiagnosed as they do not report typical symptoms. This study aims to evaluate the implantable cardiac defibrillator (ICD) sleep-disordered breathing algorithm in a cohort of multi-racial Asian patients for detection of SDB against polysomnography (PSG). Methods: In this prospective pilot study, participants who fulfill the American College of Cardiology (ACC) indication for ICD were recruited. The ICD algorithm uses transthoracic impedance sensing to calculate respiratory disturbance index (RDI). Results: Twenty-four patients were enrolled between August 2020 and December 2021. All patients underwent PSG exams and were followed up for up to 12 months. Eighteen participants completed the PSG study as of August 23, 2022. Severe SDB (defined as PSG-AHI ≥30 episodes/h) was diagnosed in 66.7% of the patients. No significant direct linear correlation was found between the PSG-AHI measurements and the RDI measurements (adjusted Conclusions: Transthoracic impedance sensing with an advanced inbuilt algorithm may be helpful as a screening test in detecting severe SDB in patients with heart failure and cardiomyopathy, potentially by applying a binary threshold cut-off value. This is the first study known to validate the algorithm in an exclusively multi-ethnic Asian population with heart failure.

Indexed as

CIEDheart failureICDsleep‐disordered breathing

Identifiers

PMID39669926
PMCPMC11632263

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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.