Evidence map›Paper›PMID 32267226›Full record

ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2020

Diagnosis of sleep apnea without sensors on the patient's face.

AbdelKebir Sabil, Caroline Marien, Marc LeVaillant, Guillaume Baffet, Nicole Meslier, Frédéric Gagnadoux

Open access · bronzeAbstract read
In one paragraph

Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
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

4 citing papers in PubMed, 15 citations in OpenAlex.

  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
  3. Tracheal Sound Analysis.Advances in experimental medicine and biology · 2022
    Article
  4. 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

6 authors at 3 institutions in 1 country.

AbdelKebir SabilCloud Sleep Lab, Paris, France.
Caroline MarienDépartement de Pneumologie, Centre Hospitalier Universitaire, Angers, France.
Marc LeVaillantInstitut de Recherche en Santé Respiratoire des Pays de la Loire, Beaucouzé, France.
Guillaume BaffetRecherche et Développement, CIDELEC, Angers, France.
Nicole MeslierDépartement de Pneumologie, Centre Hospitalier Universitaire, Angers, France.
Frédéric GagnadouxDépartement de Pneumologie, Centre Hospitalier Universitaire, Angers, France.
Centre Hospitalier Universitaire d'Angers · FRCidelec (France) · FRInserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

objectivesThermistors, nasal cannulas, and respiratory inductance plethysmography (RIP) are the recommended reference sensors of the American Academy of Sleep Medicine (AASM) for the detection and characterization of apneas and hypopneas; however, these sensors are not well tolerated by patients and have poor scorability. We evaluated the performance of an alternative method using a combination of tracheal sounds (TSs) and RIP signals.

methodsConsecutive recordings of 70 adult patients from the Pays de la Loire Sleep Cohort were manually scored in random order using the AASM standard signals and the combination TS and RIP signals, without respiratory sensors placed on the patient's face. The TS-RIP scoring used the TS and RIP-flow signals for detection of apneas and hypopneas, respectively, and the suprasternal pressure and RIP belt signals for the characterization of apneas.

resultsSensitivity and specificity of the TS-RIP combination were 96.21% and 91.34% for apnea detection and 89.94% and 93.25% for detecting hypopneas, respectively, with a kappa coefficient of 0.87. For the characterization of apneas, sensitivity and specificity were 98.67% and 96.17% for obstructive apneas, 92.66% and 99.36% for mixed apneas, and 96.14% and 98.89% for central apneas, respectively, with a kappa coefficient of 0.94. The TS-RIP scoring revealed a high agreement for classifying obstructive sleep apnea into severity classes (none, mild, moderate, and severe obstructive sleep apnea) with a Cohen's kappa coefficient of 0.96.

conclusionsCompared with the AASM reference sensors, the TS-RIP combination allows reliable noninvasive detection and characterization of respiratory events with a high degree of sensitivity and specificity. TS-RIP combination could be used for diagnosis of obstructive sleep apnea in adults, either as an alternative to the AASM sensors or in combination with the recommended AASM sensors.

Indexed as

Sleep Apnea, ObstructiveSleep Apnea SyndromesAdultHumansPlethysmographyPolysomnographySleeprespiratory event scoringsleep apnea diagnosissuprasternal pressuretracheal sounds

Identifiers

PMID32267226
PMCPMC7954046
OpenAlexW3015173453

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.