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Record W4410579212 · doi:10.1016/j.chpulm.2025.100182

Understanding Inpatient Sleep Studies for Sleep-Disordered Breathing

2025· article· en· W4410579212 on OpenAlexafffundabout
Tetyana Kendzerska, Sachin R. Pendharkar, Robert Talarico, George Chandy, Sunita Mulpuru, Kednapa Thavorn, Mark I. Boulos, MICHAEL SB MAK, Marcus Povitz

Bibliographic record

VenueCHEST Pulmonary · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science CentreUniversity of CalgaryOttawa HospitalUniversity of Ottawa
FundersAmerican College of Chest PhysiciansInstitute for Clinical Evaluative SciencesAmerican Academy of Sleep MedicineOntario Ministry of Health and Long-Term CareCenter for HIV/AIDS Educational Studies and Training, Hunter CollegeInstitut canadien d'information sur la santéMinistry of Health, Ontario
KeywordsSleep (system call)Sleep disordered breathingBreathingDatabasePopulationMedicineComputer scienceObstructive sleep apneaAnesthesiaEnvironmental health

Abstract

fetched live from OpenAlex

Background: The utility of inpatient vs outpatient polysomnography (PSG) for individuals with sleep-disordered breathing is unclear. Research Question: How do patient characteristics and sleep medicine care patterns differ between individuals undergoing inpatient vs outpatient PSG? Study Design and Methods: We conducted a retrospective population-based health administrative database study on all adult Ontarians (Canada) hospitalized and/or who underwent PSG between 2012 and 2018. We compared individuals who underwent PSG: (1) during hospitalization (inpatient PSG), (2) within the first month after discharge (delayed PSG), and (3) were not hospitalized in the last year (outpatient PSG). Outcomes included the following: baseline characteristics at the time of PSG, outpatient follow-up rates, and positive airway pressure claims in the year after PSG. Results: We identified 748 individuals in the inpatient group, 9,310 in the delayed group, and 730,967 in the outpatient PSG group. Compared with delayed or outpatient PSG groups, in unadjusted analyses, individuals in the inpatient PSG group were more likely to be older, previously assessed for sleep-disordered breathing, reside in a low-income neighborhood, and have greater comorbidity burden (standardized differences > 0.10). In adjusted analysis, individuals in the inpatient PSG group were less likely to be seen in the sleep clinic within the first year after PSG than the delayed or outpatient PSG group (hazard ratio [HR], 0.79; 95% CI, 0.71-0.87), with no difference between the delayed and outpatient PSG groups (HR, 1.00; 95% CI, 0.98-1.03). Compared with the delayed or outpatient PSG group, those in the inpatient PSG group were 21% (HR vs delayed group, 0.79; 95% CI, 0.67-0.94) to 53% (HR vs outpatient group, 0.47; 95% CI 0.27-0.82) less likely to initiate CPAP or auto-titrating positive airway pressure, and 2 to 10 times more likely to initiate bilevel positive airway pressure (HR vs outpatient group, 10.03; 95% CI, 7.30-13.77). Interpretation: Our results indicate that individuals undergoing inpatient PSG represent a unique smaller subgroup with greater comorbidity and social disadvantage, whereas the delayed PSG group may represent an optimal model of care, informing directions for future prospective studies.

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)0.023
metaresearch head score (Gemma)0.108
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.108
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.094
GPT teacher head0.340
Teacher spread0.245 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes3
Has abstractyes

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