Student or educator? Sign up with your school email and get 6 months of Pro free.

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index; none of the 51 sources its claims cite is checked for support yet.

Clinician-Focused Overview and Developments in Polysomnography

Open access
Markun, Leslie C., Sampat, Ajay·2020·Current Sleep Medicine Reports

Abstract

Polysomnography (PSG) represents a fundamental diagnostic tool used in the evaluation of sleep disorders. It represents a simultaneous recording of sleep staging, eye movements, electromyographic tone, respiratory parameters, and electrocardiogram. It is particularly helpful in the assessment of sleep-disordered breathing and its management, propensity for excessive sleepiness, complex behaviors during sleep, including motor disturbances of sleep, sleep-related epilepsy, and parasomnias. This review is intended to summarize the indications for PSG, the limitations and challenges of this diagnostic tool, indications for home sleep apnea testing options, and new developments and trends in polysomnography. The polysomnogram is fundamentally important in the evaluation of sleep-disordered breathing in the setting of cardiovascular comorbidities and neurologic conditions such as neuromuscular disease, stroke, and epilepsy and in the evaluation of dream enactment behavior in the setting of REM sleep behavior disorder (RBD). Because RBD is predictive of neurodegenerative disorders, recent data highlights the importance of PSG in corroborating the diagnosis of RBD and identifying people who may be at risk. However, due to cost as well as limitations in access to care, further testing has been developed and implemented including the home sleep apnea test (HSAT). The evolution of consumer wearable devices has also been a growing trend in sleep medicine; however, few have received appropriate validation. PSG has been used in both the clinical and research settings and remains the gold standard clinical diagnostic test for suspected obstructive sleep apnea (OSA) or central sleep apnea (CSA). Clinicians must be familiar with the basic indications for a PSG but also recognize when it is absolutely required. At this time, the PSG is essential in the evaluation of nocturnal hypoventilation disorders of sleep, periodic limb movements of sleep, and central nervous system hypersomnia (in the absence of CSF hypocretin) when combined with the multiple sleep latency test (MSLT) and is probably the only way to help differentiate among complex behaviors during sleep, especially in the setting of RBD. The capacity to establish an early diagnostic risk of potential dementia would be of critical importance once neuroprotective agents become available.

Overview

CoChat Summary

TL;DR

This clinician-focused narrative review summarizes the indications, technical components, and limitations of polysomnography (PSG), and situates it against home sleep apnea testing (HSAT) and emerging consumer/wearable and precision-medicine trends. PSG remains the gold-standard diagnostic test for suspected obstructive or central sleep apnea and is essential for nocturnal hypoventilation, periodic limb movements, central hypersomnias, and REM sleep behavior disorder, though cost, access, and night-to-night variability constrain its use.

Key findings

  • PSG is required (not merely helpful) for several diagnoses: nocturnal hypoventilation disorders, periodic limb movements of sleep, central nervous system hypersomnia (in the absence of CSF hypocretin) when combined with the MSLT, and REM sleep behavior disorder (RBD) — the only parasomnia for which PSG is required, because documentation of REM sleep without atonia plus videographic or historical dream enactment is needed.
  • RBD is described as a prodromal biomarker of neurodegenerative disease (Parkinson's disease, Lewy body dementia, multiple system atrophy), making PSG central to identifying at-risk individuals; video PSG with expanded EMG montage is an essential requirement for the diagnosis.
  • HSAT is acceptable for high-probability OSA without comorbidities, with comparative studies showing similar diagnosis and CPAP treatment rates in patients without cardiovascular disease; PSG is recommended instead for congestive heart failure, neuromuscular weakness, suspected hypoventilation, chronic opioid use, suspected parasomnia or central sleep apnea, stroke history, and evaluation of central hypersomnolence or PLMS/RLS.
  • A cited study of asymptomatic older adults found 75% met SRBD criteria by AHI > 15 alone, with no difference in subjective sleep quality, daytime sleepiness, or cognitive performance, but greater amyloid deposition and altered metabolism in posterior cingulate cortex and precuneus on MRI/PET; separate cited biomarker work found greater amyloid deposition in untreated OSA and lower serum/CSF amyloid versus controls and CPAP-treated patients.
  • Scoring thresholds reported: STOP-BANG ≥ 3 indicates high OSA risk (0–24-point Epworth Sleepiness Scale described, higher = greater sleepiness); abnormal PLMS index is > 15/h in adults and > 5/h in children; PLMD requires PLMSI > 15/h in adults; narcolepsy/IH criteria include mean sleep latency ≤ 8 min and ≥ 2 SOREM on MSLT, with SOREM within 15 min on preceding PSG counting as one; the yield of capturing an epileptiform discharge on PSG is < 50%.
  • Consumer wearables are a growing trend but few have received appropriate validation; only a few commercial devices (e.g., Dreem2) use EEG for staging, and early validation studies show feasible data acquisition with a moderate range of group-level agreement on blinded AASM-scored staging.

Methods

  • Design: narrative, clinician-focused review summarizing indications for PSG, its limitations and challenges, HSAT options, and new developments and trends.
  • Data/sample: no primary data; the paper synthesizes published literature, AASM practice parameters and the AASM Scoring Manual (version 2.6), ICSD-3 diagnostic criteria, and the 2017 USPSTF OSA screening recommendation, illustrated with example PSG tracings, hypnograms, and figures from the authors' practice.
  • Analysis: descriptive synthesis organized by indication (excessive daytime sleepiness, sleep apnea, narcolepsy, movement disorders, parasomnias, nocturnal seizure), limitations, and trends; includes tables comparing standard versus additional PSG channels, STOP-BANG scoring, HSAT versus PSG indications, central hypersomnolence criteria, and HSAT versus PSG elements.

Limitations

  • Stated by the paper: a single night may not reflect an individual's normal sleep due to night-to-night variability in many sleep disorders; the "first-night" effect can produce limited sleep time and worsened quality with less deep sleep; HSAT lacks a sleep technologist to correct technical issues mid-study, cannot be used with auto-PAP in CSA, hypoventilation syndromes, CHF, or COPD, and lacks EEG so cannot assess cortical arousals or RERAs, meaning it should not be used to "rule out" OSA; accuracy and quality of portable testing remain to be studied.
  • Stated by the paper: PSG practice variations persist in technical and interpretation practices despite AASM standardization.
  • Evident from the text (not framed as a limitation by the authors): this is a narrative review without a stated search strategy, inclusion/exclusion criteria, or systematic appraisal; several cited findings (e.g., the 75% SRBD figure and amyloid results) are drawn from single external studies cited in brief rather than synthesized quantitatively, and the review notes that a full discussion of MSLT/MWT is beyond its scope.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1007/s40675-020-00197-5

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 Valid · 8 Not valid · 48 Not checked · 39 Own results and interpretations

25 more claims

Create a free account to see all 95 claims and to verify the 30 references still open.

See all claims — free account
  • It may state two separate claims as one. 44
  • Probably not a substantial claim. 34

Create a free account to see these claims.

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

1 of 1

Citations

Cites

Show all 40 references

Research works printed but not linked: 1

  1. Berry RB, Wagner MH. Sleep medicine pearls book. Elsevier Health Sciences; 2014.

Cited by

See all 137

Metadata

Authors
Markun, L. C., & Sampat, A.
Affiliations
University of California Davis Medical Center (US)
Corresponding author
Sampat, Ajay
Venue
Current Sleep Medicine Reports
Published
2020-11-23
Volume
6
Issue
4
Pages
309-321
ISSN
2198-6401 (ISSN-L)
OpenAlex
W3108326899
Cited by
136
References
40
Citations by year
2026: 36 · 2025: 34 · 2024: 31 · 2023: 18 · 2022: 11 · 2021: 6
FWCI
1.04
Type
journal article
Language
en
Open access
Licence
Locations
  • Current Sleep Medicine Reports (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion)
Topics
  • Health Sciences › Medicine › Physiology (medical) › Obstructive Sleep Apnea Research
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Sleep and Wakefulness Research
Keywords
polysomnography, sleep disorders, sleep-disordered breathing, obstructive sleep apnea, central sleep apnea, REM sleep behavior disorder, home sleep apnea testing, wearable devices, periodic limb movements, nocturnal hypoventilation, parasomnias, sleep-related epilepsy, neurodegenerative diseases, cardiovascular comorbidity

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-11-15, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-11-15 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Clinician-Focused Overview and Developments in Polysomnography. https://app.cochat.ai/papers/10.1007/s40675-020-00197-5
The paper
Markun, L. C., & Sampat, A. (2020). Clinician-Focused Overview and Developments in Polysomnography. Current Sleep Medicine Reports. https://doi.org/10.1007/s40675-020-00197-5

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.