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Record W3159342713 · doi:10.1093/sleep/zsab072.059

060 Challenging the current assessment criteria for scoring central sleep apnea at altitude

2021· article· en· W3159342713 on OpenAlexaffabout
Jordan D. Bird, Jason Chan, Alexander Rimke, Anne Kalker, Garrick Chan, Tom D. Brutsaert, Mingma G. Sherpa, Trevor A. Day

Bibliographic record

VenueSLEEP · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsMount Royal University
Fundersnot available
KeywordsContext (archaeology)PolysomnographyMedicineApneaCentral sleep apneaSleep medicineObstructive sleep apneaSleep apneaAltitude (triangle)Effects of high altitude on humansAnesthesiaSleep disorderInsomnia

Abstract

fetched live from OpenAlex

Abstract Introduction Sleep disordered breathing comes in two forms: obstructive and central sleep apnea (SA). Obstructive sleep apnea (OSA) is caused by upper airway collapse during sleep, and is associated with increases in morbidity and mortality. Conversely, central sleep apnea (CSA) results from increases in respiratory chemosensitivity to blood gas challenges in the context of high-altitude ascent. CSA increases in severity and apneas shorten in duration with higher ascent and/or time spent at altitude. Although both types of SA are characterized by intermittent periods of apnea and hyperventilation, the underlying mechanisms and phenotypes between OSA and CSA are different. A universal scoring system for the two types of context-dependent SA may lead to errors in quantification. The American Association of Sleep Medicine (AASM) developed assessment criteria for SA, which are universally-utilized for all types of SA to quantify an apnea-hypopnea index (AHI; events/hour), where apneas are scored as cessation of breathing ≥10-sec. We aimed to assess the effect of reducing the apnea-detection threshold (ADT) to <10-sec to quantitatively assess the extent that a shorter ADT affects the scoring of AHI in the context of high-altitude ascent, where CSA is universal. Methods We assessed CSA using portable polysomnography (ApneaLink, ResMed) during ascent to 5160m in the Nepal Himalaya over 10 days in 15 healthy participants. Files were archived digitally for later analysis using automated scoring software (ApneaLink Reporting Software, ResMed). We quantified and compared AHI using AASM criteria (i.e., 10-sec ADT) and a shorter 5-sec ADT. Results AHI was 3.9±4.1 events/hour at 1045m prior to ascent, with AHI increasing to 37.5±32.8 events/hour (P<0.0001) at 5160m after 10 days of incremental ascent using AASM criteria (i.e., 10-sec ADT). When the ADT was reduced to 5-sec at 5160m, AHI was increased to 61.6±38.1 (+61%; P=0.0002). Conclusion This preliminary report suggests that the AASM criterion for scoring apneas, which is broadly applied to OSA at low altitude, may underestimate the assessment and quantification of CSA with ascent to and prolonged stays at high altitude. Development of distinct assessment criteria for OSA and CSA may be warranted. Support (if any) Natural Science sand Engineering Research Council of Canada

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.313
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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