Evidence map›Paper›PMID 32506203›Full record

Trial reportSleep & breathing = Schlaf & Atmung2021

Breath variability increases in the minutes preceding obstructive sleep apneic events.

Tharun Niranjan Gomudurai Pandian, Ruchir Sehra, Sanjiv Narayan

Registry-linked trialAbstract readClinical Trial
PubMed Publisher
In one paragraph

Trial report in Sleep & breathing = Schlaf & Atmung, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03288376 (SNORE), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 53% 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.

NCT03288376 completednot on this map

SNORE (Smartphone Analyses of Nocturnal Obstruction by Respiratory Evaluation) SOUNDS

TypeobservationalSponsorIncyphae, Inc.Ran2015 to 2017Enrolled272ConditionsSleep Apnea, Obstructive, Chronic Obstructive Pulmonary Disease
3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

Tharun Niranjan Gomudurai PandianResonea Inc., 16580 N. 92nd Street #3001, Scottsdale, AZ, 85260, USA.
Ruchir SehraResonea Inc., 16580 N. 92nd Street #3001, Scottsdale, AZ, 85260, USA.
Sanjiv NarayanResonea Inc., 16580 N. 92nd Street #3001, Scottsdale, AZ, 85260, USA. sanjivnarayan@resonea.com.
Scottsdale Research Institute (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIt is unclear if there is a consistent signature in breath patterns prior to an impending obstructive apneic event in patients with sleep-disordered breathing (SDB).

objectiveTo use continuous recordings of ambient sound in sleep using a smartphone to track auditory signatures of breaths and measure their regularity preceding apneic events.

methodsWe studied 50 patients evaluated for SDB in whom sound was recorded using smartphones concurrently with polysomnography (PSG). Whole-night sound files were analyzed for time and frequency domain analyses of breath periodicity during periods of normal and sleep-disordered breathing.

resultsFifty patients (44% women, 42.0 ± 9.4 years old, BMI 32.8 ± 10.8 kg/m

conclusionsBreaths increase in variability minutes before proven obstructive apnea in patients with suspected SDB. These results suggest that it may be possible to predict and thus potentially avert apneic events and provide insights into events leading to SDB.

trial registrationNCT03288376, clinicaltrials.org.

Indexed as

AdultFemaleHumansMaleMiddle AgedMonitoring, PhysiologicPolysomnographyPrognosisRespiratory RateRespiratory SoundsSleep Apnea, ObstructiveSmartphoneBreath periodicitySignal processingSleep apneaSmartphoneSound

Identifiers

PMID32506203
OpenAlexW3034044124

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.