Evidence mapPaperPMID 41310031Full record

SynthesisSleep & breathing = Schlaf & Atmung2025

Diagnostic value of wearable and contactless technologies for detecting obstructive sleep apnea: a systematic review and meta-analysis.

Muhammad Hasanain, Abdullah Akram, Aqsa Kabir, Hadiya Javed, Muhammad Usman, Huda Jaffar, Abdullah Aslam Khan, Ghulam Mustafa Ali Malik, Muzainah Tabassum, Muhammad Faizan and 3 more

Abstract readSystematic ReviewMeta-Analysis
PubMed Publisher
In one paragraph

Synthesis in Sleep & breathing = Schlaf & Atmung, 2025. 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. Review
  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.

Muhammad HasanainDow Medical College, Karachi, Pakistan. muhammad.hasanain.mh@gmail.com.ORCID 0000-0001-9214-7840
Abdullah AkramDow Medical College, Karachi, Pakistan.
Aqsa KabirDow Medical College, Karachi, Pakistan.
Hadiya JavedDow Medical College, Karachi, Pakistan.
Muhammad UsmanDow Medical College, Karachi, Pakistan.
Huda JaffarSUNY Upstate Medical University, Syracuse, NY, USA.
Abdullah Aslam KhanRawal Institute of Health Sciences, Islamabad, Pakistan.
Ghulam Mustafa Ali MalikDow International Medical College, Karachi, Pakistan.
Muzainah TabassumJinnah Sindh Medical University, Karachi, Pakistan.
Muhammad FaizanDow Medical College, Karachi, Pakistan.
Muhammad Umair AnjumDow Medical College, Karachi, Pakistan.
Muhammed UmerSaint Michael's Medical Center, Newark, NJ, USA.
Salim SuraniTexas A&M University, College Station, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND​: Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder, affecting an estimated 1 billion adults worldwide. This study evaluates the diagnostic accuracy of wearable and contactless sleep technologies as alternatives to Polysomnography (PSG) for the detection of OSA.

methodsA comprehensive search was conducted from inception to September 2025 on PubMed, Cochrane Library, ClinicalTrials.gov, and ScienceDirect. Studies including adults diagnosed with OSA using PSG or HSAT and evaluated with wearable or contactless devices were included. Studies assessing the diagnostic performance of these consumer devices and reporting diagnostic accuracy measures were included. QUADAS-2 was used to assess the risk of bias, and meta-analysis was performed.

resultsA total of 59 studies were included, with 3,768 participants in the contactless group and 2,743 participants in the wearable group. For AHI > 15, contactless devices demonstrated a pooled sensitivity of 0.88 (95% CI: 0.86-0.90) and specificity of 0.87 (95% CI: 0.82-0.91), with an AUC of 0.92 (95% CI: 0.89-0.94). Wearable devices showed a pooled sensitivity of 0.87 (95% CI: 0.81-0.92), specificity of 0.86 (95% CI: 0.78-0.91), and an AUC of 0.93 (95% CI: 0.90-0.95).

conclusionWearable and contactless sleep technologies demonstrate strong diagnostic accuracy. Their role is likely going to be to screen, and compliment PSG rather than replacing it, and providing utility in settings where access to traditional sleep testing is limited. More validation studies across populations, care settings, and comorbidities are needed to make clinical guidelines.

Indexed as

Sleep Apnea, ObstructiveWearable Electronic DevicesHumansPolysomnographySensitivity and SpecificityContactless technologyDiagnostic accuracyDigital healthMeta-AnalysisObstructive sleep apneaPolysomnographyWearable devices

Identifiers

PMID41310031

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.