OSA diagnosis goes wearable: are the latest devices ready to shine?

accelerometry acoustic apnea-hypopnea index (AHI) artificial intelligence (AI) home sleep apnea testing (HSAT) obstructive sleep apnea (OSA) peripheral arterial tonometry (PAT) photoplethysmography (PPG) sleep technology wearable

Journal

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
ISSN: 1550-9397
Titre abrégé: J Clin Sleep Med
Pays: United States
ID NLM: 101231977

Informations de publication

Date de publication:
12 Aug 2024
Historique:
medline: 12 8 2024
pubmed: 12 8 2024
entrez: 12 8 2024
Statut: aheadofprint

Résumé

Since 2019, the FDA has cleared nine novel obstructive sleep apnea (OSA)-detecting wearables for home sleep apnea testing, with many now commercially available for sleep clinicians to integrate into their clinical practices. To help clinicians comprehend these devices and their functionalities, we meticulously reviewed their operating mechanisms, sensors, algorithms, data output, and related performance evaluation literature. We collected information from PubMed, FDA clearance documents, ClinicalTrial.gov, and web sources, with direct industry input whenever feasible. In this "device-centered" review, we broadly categorized these wearables into two main groups: those that primarily harness Photoplethysmography (PPG) data and those that do not. The former include the peripheral arterial tonometry (PAT)-based devices. The latter was further broken down into two key subgroups: acoustic-based and respiratory effort-based devices. We provided a performance evaluation literature review and objectively compared device-derived metrics and specifications pertinent to sleep clinicians. Detailed demographics of study populations, exclusion criteria, and pivotal statistical analyses of the key validation studies are summarized. In the foreseeable future, these novel OSA-detecting wearables may emerge as primary diagnostic tools for patients at risk for moderate-to-severe OSA without significant comorbidities. While more devices are anticipated to join this category, there remains a critical need for cross-device comparison studies as well as independent performance evaluation and outcome research in diverse populations. Now is the moment for sleep clinicians to immerse themselves in understanding these emerging tools to ensure our patient-centered care is improved through the appropriate implementation and utilization of these novel sleep technologies.

Identifiants

pubmed: 39132687
doi: 10.5664/jcsm.11290
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 American Academy of Sleep Medicine.

Auteurs

Ambrose A Chiang (AA)

Sleep Medicine Section, Louis Stokes Cleveland VA Medical Center; Division of Pulmonary, Critical Care, and Sleep Medicine, University Hospitals Cleveland Medical Center; Department of Medicine, Case Western Reserve University, Cleveland, Ohio.

Evin Jerkins (E)

Department of Primary Care, Ohio University Heritage College of Osteopathic Medicine, Dublin, Ohio; Medical Director, Fairfield Medical Sleep Center, Lancaster, Ohio.

Steven Holfinger (S)

Division of Pulmonary, Critical Care, and Sleep Medicine, Ohio State University, Columbus, Ohio.

Sharon Schutte-Rodin (S)

Division of Sleep Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.

Arvind Chandrakantan (A)

Department of Anesthesiology & Pediatrics, Texas Children's Hospital and Baylor College of Medicine, Houston, Texas.

Laura Mong (L)

Fairfield Medical Center, Lancaster, Ohio.

Steve Glinka (S)

MedBridge Healthcare, Greenville, South Carolina.

Seema Khosla (S)

North Dakoda Center for Sleep, Fargo, North Dakoda.

Classifications MeSH