Evidence map›Paper›PMID 32929467›Full record

ArticleSleep2021

A scalable method of determining physiological endotypes of sleep apnea from a polysomnographic sleep study.

Eysteinn Finnsson, Guðrún H Ólafsdóttir, Dagmar L Loftsdóttir, Sigurður Æ Jónsson, Halla Helgadóttir, Jón S Ágústsson, Scott A Sands, Andrew Wellman

Open access · bronzeAbstract read
In one paragraph

Article in Sleep, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

33 citing papers in PubMed, 60 citations in OpenAlex.

  1. Review
  2. Current Updates on Pharmacotherapy for Obstructive Sleep Apnea.Journal of rhinology : official journal of the Korean Rhinologic Society · 2026
    Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Context-aware analysis enhances autoscoring accuracy of home sleep apnea testing.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2025
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. [Sleep Innovation].Open respiratory archives · 2024
    Review
  17. Observational
  18. Article
  19. Review
  20. Paediatric sleep diagnostics in the 21st century: the era of "sleep-omics"?European respiratory review : an official journal of the European Respiratory Society · 2024
    Review
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

8 authors at 1 institution in 1 country.

Eysteinn FinnssonNox Research, Nox Medical, Reykjavík, Iceland.
Guðrún H ÓlafsdóttirNox Research, Nox Medical, Reykjavík, Iceland.
Dagmar L LoftsdóttirNox Research, Nox Medical, Reykjavík, Iceland.
Sigurður Æ JónssonNox Research, Nox Medical, Reykjavík, Iceland.
Halla HelgadóttirNox Research, Nox Medical, Reykjavík, Iceland.
Jón S ÁgústssonNox Research, Nox Medical, Reykjavík, Iceland.
Scott A SandsDivision of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
Andrew WellmanDivision of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
Brigham and Women's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sleep apnea is caused by several endophenotypic traits, namely pharyngeal collapsibility, poor muscle compensation, ventilatory instability (high loop gain), and arousability from sleep (low arousal threshold). Measures of these traits have shown promise for predicting outcomes of therapies (e.g. oral appliances, surgery, hypoglossal nerve stimulation, CPAP, and pharmaceuticals), which may become an integral part of precision sleep medicine. Currently, the methods Sands et al. developed for endotyping sleep apnea from polysomnography (PSG) are embedded in the original authors' code, which is computationally expensive and requires technological expertise to run. We present a reimplementation and validation of the integrity of the original authors' code by reproducing the endo-Phenotyping Using Polysomnography (PUP) method of Sands et al. The original MATLAB methods were reprogrammed in Python; efficient algorithms were developed to detect breaths, calculate normalized ventilation (moving time-average), and model ventilatory drive (intended ventilation). The new implementation (PUPpy) was validated by comparing the endotypes from PUPpy with the original PUP results. Both endotyping methods were applied to 38 manually scored polysomnographic studies. Results of the new implementation were strongly correlated with the original (p < 10-6 for all): ventilation at eupnea V̇ passive (ICC = 0.97), ventilation at arousal onset V̇ active (ICC = 0.97), loop gain (ICC = 0.96), and arousal threshold (ICC = 0.90). We successfully implemented the original PUP method by Sands et al. providing further evidence of its integrity. Additionally, we created a cloud-based version for scaling up sleep apnea endotyping that can be used more easily by a wider audience of researchers and clinicians.

Indexed as

Sleep Apnea, ObstructiveSleep Apnea SyndromesAdultAgedContinuous Positive Airway PressureFemaleHumansMaleMiddle AgedPolysomnographySleeparousal thresholdcollapsibilityendotypeloop gainpersonalized medicinephenotypesleep apneaupper airway anatomy

Identifiers

PMID32929467
PMCPMC7819840
OpenAlexW3087008266

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.