Evidence map›Paper›PMID 28822017›Full record

Trial reportSleep & breathing = Schlaf & Atmung2018

Validation of a non-contact screening device for the combination of sleep-disordered breathing and periodic limb movements in sleep.

Gerhard Weinreich, Sarah Terjung, Yi Wang, Stefanie Werther, Alberto Zaffaroni, Helmut Teschler

Abstract readClinical Trial
PubMed Publisher
In one paragraph

Trial report in Sleep & breathing = Schlaf & Atmung, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Trial
  2. Long-term night-to-night variability of sleep-disordered breathing using a radar-based home sleep apnea test: a prospective cohort study.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024
    Trial
  3. Review
  4. Article
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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

6 authors.

Gerhard WeinreichDepartment of Pneumology, Ruhrlandklinik, West German Lung Center, University Hospital Essen, University-Duisburg Essen, Essen, Germany. gerhard.weinreich@ruhrlandklinik.uk-essen.de.
Sarah TerjungDepartment of Pneumology, Ruhrlandklinik, West German Lung Center, University Hospital Essen, University-Duisburg Essen, Essen, Germany.
Yi WangDepartment of Pneumology, Ruhrlandklinik, West German Lung Center, University Hospital Essen, University-Duisburg Essen, Essen, Germany.
Stefanie WertherDepartment of Pneumology, Ruhrlandklinik, West German Lung Center, University Hospital Essen, University-Duisburg Essen, Essen, Germany.
Alberto ZaffaroniResmed Sensor Technologies, Dublin, Ireland.
Helmut TeschlerDepartment of Pneumology, Ruhrlandklinik, West German Lung Center, University Hospital Essen, University-Duisburg Essen, Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeRecent studies found that the non-contact screening device SleepMinder (ResMed Sensor Technologies, Dublin, Ireland) detects sleep-disordered breathing (SDB) with high diagnostic accuracy in cohorts suspected of this disorder. However, it was reported that in patients with periodic limb movement in sleep (PLMS), this non-contact device overestimates the apnea-hypopnea index (AHI). We aimed to overcome this limitation by introducing the novel sleep disorder index (SDI) which is sum of the AHI and the period limb movement index (PLMI).

methodsBetween January 2011 and December 2013, we studied a mixed cohort of 57 patients (31 OSA, 19 PLMS). The easy-to-use non-contact device emits a very weak electromagnetic radiation and detects body movement by measuring the Doppler effect. We interpreted the device-generated movement index as the SDI and validated the diagnostic accuracy against simultaneous application of the gold-standard polysomnography (PSG).

resultsWe found that the SDI of the non-contact device correlated well with the sum of AHI and PLMI derived from PSG (r = 0.79, p = 0.01). For PSG-derived SDI cutoff ≥ 15/h, we obtained a sensitivity of 92.2% and a specificity of 95.8%. Positive likelihood ratio was 23.3 and negative likelihood ratio 0.03.

conclusionsThe studied non-contact screening device detects accurately the combination of the sleep disorders SDB and/or PLM. However, further testing is required in order to specify the nature of the underlying sleep disorder. At the current stage of algorithm development, the clinical strength is that the studied non-contact device can be used as a rule-out screening device for SDB and PLM.

Indexed as

FemaleHumansMaleMiddle AgedNocturnal Myoclonus SyndromePolysomnographyReproducibility of ResultsSleepSleep Apnea SyndromesAmbulatory monitoringCheyne-Stokes respirationCSRObstructive sleep apneaOSAPeriodic limb movementPLMPolysomnography

Identifiers

PMID28822017

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Registered trials

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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.