Evidence map›Paper›PMID 28095966›Full record

ArticleJournal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine2017

Potential Underestimation of Sleep Apnea Severity by At-Home Kits: Rescoring In-Laboratory Polysomnography Without Sleep Staging.

Matt T Bianchi, Balaji Goparaju

Abstract read
In one paragraph

Article in Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
–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

47 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Obstructive sleep apnea in patients with head and neck cancer: a systematic review.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2021
    Pooled it
  2. Trial
  3. Trial
  4. Home Sleep Apnea Testing is a Feasible and Accurate Method to Diagnose Obstructive Sleep Apnea in Stroke Patients During In-Hospital Rehabilitation.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2018
    Trial
  5. Article
  6. Article
  7. Article
  8. Article
  9. Quantifying the sources of discrepancy between total recording time and total sleep time in home sleep apnea testing: insights from home-based polysomnography.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Observational
  10. Article
  11. Article
  12. Article
  13. OSA diagnosis goes wearable: are the latest devices ready to shine?Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024
    Review
  14. Article
  15. The impact of study type and sleep measurement on oxygen desaturation index calculation.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024
    Article
  16. Article
  17. Respiratory event index underestimates severity of sleep apnea compared to apnea-hypopnea index.Sleep advances : a journal of the Sleep Research Society · 2024
    Article
  18. The prevalence of treatment-emergent central sleep apnea with mandibular advancement device therapy.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2023
    Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Matt T BianchiNeurology Department, Massachusetts General Hospital, Boston, MA.
Balaji GoparajuNeurology Department, Massachusetts General Hospital, Boston, MA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

STUDY

objectivesHome sleep apnea testing (HSAT) is increasingly available for diagnosing obstructive sleep apnea (OSA). One key limitation of most HSAT involves the lack of sleep staging, such that the respiratory event index is calculated using the total recording time (TRT) rather than total sleep time (TST).

methodsWe performed a retrospective analysis of n = 838 diagnostic polysomnography (PSG) nights from our center; n = 444 with OSA (4% rule, apneahypopnea index (AHI) ≥ 5), and n = 394 with AHI < 5. We recalculated the AHI using time in bed (TIB) instead of TST, to assess the predicted underestimation risk of OSA severity.

resultsOf all the patients with OSA, 26.4% would be reclassified as having less severe or no OSA after recalculating the AHI using TIB rather than TST. Of the n = 275 with mild OSA, 18.5% would be reclassified as not having OSA. The risk of underestimation was higher in those with moderate or severe OSA. Of the n = 119 moderate OSA cases, 40.3% would be reclassified as mild, and of the n = 50 severe OSA cases, 36.0% would be reclassified as moderate. Age strongly correlated with the degree of underestimation of the AHI, because age was significantly correlated with time awake during PSG.

conclusionsThe risk of sleep apnea underestimation is predicted to be substantial in a tertiary sleep center population. Phenotyping errors included risk of falsely negative results (from mild to normal), as well as category errors: moderate or severe moving to mild or moderate severity, respectively. Clinicians should recognize this underestimation limitation, which directly affects diagnostic phenotyping and thus therapeutic decisions. COMMENTARY: A commentary on this article appears in this issue on page 531.

Indexed as

AdolescentAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPolysomnographyRetrospective StudiesSeverity of Illness IndexSleep Apnea, ObstructiveSleep StagesYoung Adultdiagnosispredictionunderestimation

Identifiers

PMID28095966
PMCPMC5359331

What OpenQuestion holds

Textmetadata
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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.