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ArticleFrontiers in neurology2025

Polysomnography validation of SANSA to detect obstructive sleep apnea.

Cathy Goldstein, Hamid Ghanbari, Surina Sharma, Nancy Collop, Andrew Namen, Douglas B Kirsch, Michael Drucker, Rami Khayat, Mark Pollock, Brennan Torstrick and 4 more

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06070389 (Polysomnography Validation of the Sansa Device), which is not on this 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.

NCT06070389 nacompletednot on this map

Polysomnography Validation of the Sansa Device

TypeinterventionalSponsorHuxley Medical, Inc.Ran2023 to 2023Enrolled533ConditionsSleep-Disordered BreathingArmsSansa device
3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. From classic to cutting-edge: technological approaches to respiratory physiological signals in assessing sleep-disordered breathing.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026
    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

14 authors.

Cathy GoldsteinDepartment of Neurology, University of Michigan, Ann Arbor, MI, United States.
Hamid GhanbariDivision of Cardiovascular Medicine, University of Michigan, Ann Arbor, MI, United States.
Surina SharmaEmory Sleep Center, Emory University, Atlanta, GA, United States.
Nancy CollopEmory Sleep Center, Emory University, Atlanta, GA, United States.
Andrew NamenAtrium Wake Forest Baptist, Winston-Salem, NC, United States.
Douglas B KirschAtrium Health Sleep Medicine, Charlotte, NC, United States.
Michael DruckerNovant Health Cardiology, Winston-Salem, NC, United States.
Rami KhayatDivision of Pulmonary, Allergy, and Critical Care, Penn State Health and the Sleep Research and Treatment Center, Pennsylvania State University, Hershey, PA, United States.
Mark PollockPulmonary & Sleep Specialists, Atlanta, GA, United States.
Brennan TorstrickHuxley Medical, Inc., Atlanta, GA, United States.
Colleen WalshDivision of Sleep Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Emily HerreshoffDepartment of Neurology, University of Michigan, Ann Arbor, MI, United States.
David S FrankelDivision of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
Ilene M RosenDivision of Sleep Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Study objectives: Evaluate the performance of a novel home sleep apnea test with embedded ECG (SANSA, Huxley Medical, Inc.) in the diagnosis of obstructive sleep apnea (OSA). Methods: This prospective multicenter validation study included 340 participants who underwent simultaneous polysomnography (PSG) and SANSA recordings across 7 clinical sites. Participants were diverse across age, sex, race, skin tone, and body mass index. Diagnostic performance was assessed with the apnea-hypopnea index (AHI) using both Rule 1A and Rule 1B across standard cutoffs for mild, moderate, or severe (≥5 events/h), moderate-to-severe (≥15 events/h), and severe (≥30 events/h) OSA. The agreement for AHI and total sleep time (TST) between SANSA and consensus PSG scores from three independent scorers was evaluated using Pearson's correlation and Bland-Altman analysis. Sensitivity and specificity were calculated at each OSA severity level. Performance of participating site PSG scores were also evaluated against consensus PSG scores for comparison. Results: SANSA demonstrated excellent agreement with PSG for most performance parameters. AHI correlation was 0.91 (95% CI: 0.89, 0.93) using Rule 1B and 0.90 (95% CI: 0.87, 0.92) using Rule 1A. Compared to consensus scored PSG, the device detected moderate-to-severe OSA using Rule 1B (the primary endpoint) with a sensitivity of 88% (95% CI: 81, 93%) and specificity of 87% (95% CI: 82, 91%), while site PSG sensitivity was 89% (95% CI: 82, 94%) and specificity was 93% (95% CI: 88, 96%). SANSA TST highly correlated with PSG TST ( Conclusion: The SANSA home sleep apnea test demonstrated robust diagnostic performance for OSA detection including measurement of sleep compared to PSG. Its patch morphology and embedded ECG confer ease of use and multi-diagnostic potential in sleep medicine and cardiology for the detection of OSA and cardiac arrhythmias across diverse clinical populations. Clinical trial registration: [https://www.clinicaltrials.gov/study/NCT06070389], identifier [NCT06070389].

Indexed as

atrial fibrillationcardiac arrhythmiahome sleep apnea testingsleep apneasleep disordered breathingwearable diagnostic devices

Identifiers

PMID40589991
PMCPMC12206633

What OpenQuestion holds

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Registered trials

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.