Implantable cardiac devices in sleep apnoea diagnosis: A systematic review and meta-analysis.


Journal

International journal of cardiology
ISSN: 1874-1754
Titre abrégé: Int J Cardiol
Pays: Netherlands
ID NLM: 8200291

Informations de publication

Date de publication:
01 Feb 2022
Historique:
received: 24 09 2021
revised: 06 12 2021
accepted: 09 12 2021
pubmed: 16 12 2021
medline: 27 1 2022
entrez: 15 12 2021
Statut: ppublish

Résumé

A particularly high burden of sleep apnoea is reported in patients treated with cardiac implants such as pacemakers and defibrillators. Sleep apnoea diagnosis remains a complex procedure mainly based on sleep and respiratory indices captured by polysomnography (PSG) or respiratory polygraphy (PG). We aimed to evaluate the performance of implantable cardiac devices for sleep apnoea diagnosis compared to reference methods. Systematic structured literature searches were performed in PubMed, Embase and. Cochrane Library was performed to identify relevant studies. Quantitative characteristics of the studies were summarized and a qualitative synthesis was performed by a randomized bivariate meta-analysis and completed by pre-specified sensitivity analyses for different implant types and brands. 16 studies involving 999 patients met inclusion criteria and were included in the meta-analysis. The majority of patients were men, of mean age of 64 ± 4.6 years. Sensitivity of cardiac implants for sleep apnoea diagnosis ranged from 60 to 100%, specificity from 50 to 100% with a prevalence of sleep apnoea varying from 22 to 91%. For an apnoea-hypopnoea index threshold ≥30 events/h during polysomnography (corresponding to severe sleep apnoea), the overall performance of the implants was relevant with a sensitivity of 78% and a specificity of 79%. Subgroup analyses on implant type and brand provided no additional information owing to the small number of studies. The respiratory disturbance index provided by cardiac implants is clinically relevant and might improve access to sleep apnoea diagnosis in at-risk cardiovascular populations. PROSPERO Registration number: CRD42020181656.

Sections du résumé

BACKGROUND BACKGROUND
A particularly high burden of sleep apnoea is reported in patients treated with cardiac implants such as pacemakers and defibrillators. Sleep apnoea diagnosis remains a complex procedure mainly based on sleep and respiratory indices captured by polysomnography (PSG) or respiratory polygraphy (PG).
AIM OBJECTIVE
We aimed to evaluate the performance of implantable cardiac devices for sleep apnoea diagnosis compared to reference methods.
METHOD METHODS
Systematic structured literature searches were performed in PubMed, Embase and. Cochrane Library was performed to identify relevant studies. Quantitative characteristics of the studies were summarized and a qualitative synthesis was performed by a randomized bivariate meta-analysis and completed by pre-specified sensitivity analyses for different implant types and brands.
RESULTS RESULTS
16 studies involving 999 patients met inclusion criteria and were included in the meta-analysis. The majority of patients were men, of mean age of 64 ± 4.6 years. Sensitivity of cardiac implants for sleep apnoea diagnosis ranged from 60 to 100%, specificity from 50 to 100% with a prevalence of sleep apnoea varying from 22 to 91%. For an apnoea-hypopnoea index threshold ≥30 events/h during polysomnography (corresponding to severe sleep apnoea), the overall performance of the implants was relevant with a sensitivity of 78% and a specificity of 79%. Subgroup analyses on implant type and brand provided no additional information owing to the small number of studies.
CONCLUSION CONCLUSIONS
The respiratory disturbance index provided by cardiac implants is clinically relevant and might improve access to sleep apnoea diagnosis in at-risk cardiovascular populations. PROSPERO Registration number: CRD42020181656.

Identifiants

pubmed: 34906614
pii: S0167-5273(21)02006-4
doi: 10.1016/j.ijcard.2021.12.014
pii:
doi:

Types de publication

Journal Article Meta-Analysis Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

76-82

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2021 Elsevier B.V. All rights reserved.

Auteurs

Raoua Ben Messaoud (R)

HP2 Laboratory, Inserm U1300, Grenoble Alpes University, Grenoble, France. Electronic address: ext-rbenmessaoud@chu-grenoble.fr.

Charles Khouri (C)

HP2 Laboratory, Inserm U1300, Grenoble Alpes University, Grenoble, France; Regional Pharmacovigilance Center, Grenoble Alpes University Hospital, Grenoble, France. Electronic address: ckhouri@chu-grenoble.fr.

Jean Louis Pépin (JL)

HP2 Laboratory, Inserm U1300, Grenoble Alpes University, Grenoble, France; EFCR Laboratory, Thorax and Vessels division, Grenoble Alpes University Hospital, Grenoble, France. Electronic address: JPepin@chu-grenoble.fr.

Jean Luc Cracowski (JL)

HP2 Laboratory, Inserm U1300, Grenoble Alpes University, Grenoble, France; Regional Pharmacovigilance Center, Grenoble Alpes University Hospital, Grenoble, France. Electronic address: JLCracowski@chu-grenoble.fr.

Renaud Tamisier (R)

HP2 Laboratory, Inserm U1300, Grenoble Alpes University, Grenoble, France; EFCR Laboratory, Thorax and Vessels division, Grenoble Alpes University Hospital, Grenoble, France. Electronic address: RTamisiser@chu-grenoble.fr.

Fabian Barbieri (F)

University Hospital for Internal Medicine III (Cardiology and Angiology), Medical University Innsbruck, Austria. Electronic address: fabian.barbieri@i-med.ac.at.

Anna Heidbreder (A)

Sleep Disorders Clinic, Department of Neurology, Medical University Innsbruck, Austria. Electronic address: anna.heidbreder@i-med.ac.at.

Marie Joyeux-Faure (M)

HP2 Laboratory, Inserm U1300, Grenoble Alpes University, Grenoble, France; EFCR Laboratory, Thorax and Vessels division, Grenoble Alpes University Hospital, Grenoble, France. Electronic address: MJoyeuxfaure@chu-grenoble.fr.

Pascal Defaye (P)

Arrhythmia Unit, Cardiology Department, Grenoble Alpes University Hospital, Grenoble, France. Electronic address: PDefaye@chu-grenoble.fr.

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Classifications MeSH