Evidence map›Paper›PMID 27166303›Full record

ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2016

Residual Events during Use of CPAP: Prevalence, Predictors, and Detection Accuracy.

Joel Reiter, Bashar Zleik, Mihaela Bazalakova, Pankaj Mehta, Robert Joseph Thomas

Open access · bronzeAbstract read
In one paragraph

Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 13% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. The combination of physiology and machine learning for prediction of CPAP pressure and residual AHI in OSA.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Article
  11. Inspiratory positive pressure modulation to minimize respiratory control instability.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Article
  12. Article
  13. Observational
  14. Article
  15. A longitudinal study of the accuracy of positive airway pressure therapy machine-detected apnea-hypopnea events.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2022
    Article
  16. Electronic health record-derived outcomes in obstructive sleep apnea managed with positive airway pressure tracking systems.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2022
    Article
  17. Review
  18. Interpreting CPAP device respiratory indices in children.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2020
    Article
  19. Use of the WatchPAT to detect occult residual sleep-disordered breathing in patients on CPAP for obstructive sleep apnea.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2020
    Article
  20. DISE-PAP: a method for troubleshooting residual AHI elevation despite positive pressure therapy.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2020
    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

5 authors at 1 institution in 2 countries.

Joel ReiterSleep Disorders Clinic, Departments of Medicine & Neurology, Beth Israel Deaconess Medical Center, Boston, MA.
Bashar ZleikSleep Disorders Clinic, Departments of Medicine & Neurology, Beth Israel Deaconess Medical Center, Boston, MA.
Mihaela BazalakovaSleep Disorders Clinic, Departments of Medicine & Neurology, Beth Israel Deaconess Medical Center, Boston, MA.
Pankaj MehtaSleep Disorders Clinic, Departments of Medicine & Neurology, Beth Israel Deaconess Medical Center, Boston, MA.
Robert Joseph ThomasSleep Disorders Clinic, Departments of Medicine & Neurology, Beth Israel Deaconess Medical Center, Boston, MA.
Beth Israel Deaconess Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

objectivesTo assess the frequency, severity, and determinants of residual respiratory events during continuous positive airway therapy (CPAP) for obstructive sleep apnea (OSA) as determined by device output.

methodsSubjects were consecutive OSA patients at an American Academy of Sleep Medicine accredited multidisciplinary sleep center. Inclusion criteria included CPAP use for a minimum of 3 months, and a minimum nightly use of 4 hours. Compliance metrics and waveform data from 217 subjects were analyzed retrospectively. Events were scored manually when there was a clear reduction of amplitude (≥ 30%) or flow-limitation with 2-3 larger recovery breaths. Automatically detected versus manually scored events were subjected to statistical analyses included Bland-Altman plots, correlation coefficients, and logistic regression exploring predictors of residual events.

resultsThe mean patient age was 54.7 ± 14.2 years; 63% were males. All patients had a primary diagnosis of obstructive sleep apnea, 26% defined as complex sleep apnea. Residual flow measurement based apnea-hypopnea index (AHIFLOW) > 5, 10, and 15/h was seen in 32.3%, 9.7%, and 1.8% vs. 60.8%, 23%, and 7.8% of subjects based on automated vs. manual scoring of waveform data. Automatically detected versus manually scored average AHIFLOW was 4.4 ± 3.8 vs. 7.3 ± 5.1 per hour. In a logistic regression analysis, the only predictors for a manual AHIFLOW > 5/h were the absolute central apnea index (CAI), (odds ratio [OR]: 1.5, p: 0.01, CI: 1.1-2.0), or using a CAI threshold of 5/h of sleep (OR: 5.0, p: < 0.001, CI: 2.2-13.8). For AHIFLOW > 10/h, the OR was 1.14, p: 0.03 (CI: 1.1-1.3) per every CAI unit of 1/hour.

conclusionsResidual respiratory events are common during CPAP treatment, may be missed by automated device detection and predicted by a high central apnea index on the baseline diagnostic study. Direct visualization of flow data is generally available and improves detection.

Indexed as

Continuous Positive Airway PressureFemaleHumansMaleMiddle AgedPolysomnographyPrevalenceReproducibility of ResultsRespiratory SystemRetrospective StudiesSeverity of Illness IndexSleep Apnea, Obstructiveauto-CPAPresidual apneasleep

Identifiers

PMID27166303
PMCPMC4957193
OpenAlexW2412867340

What OpenQuestion 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 OpenQuestion graph.