0471 INSPIRATORY FLOW LIMITATION IN A LARGE AMBULATORY COHORT OF SUSPECTED SLEEP APNOEA PATIENTS
Bibliographic record
Abstract
There is no agreed upon best diagnostic or prognostic metric for sleep apnoea. Novel percentage of inspiratory flow limited breaths, clinical pre-test probability of sleep apnoea from adjusted neck circumference, and usual estimated respiratory disturbance index (eRDI) were compared against Epworth Sleep Scale (ESS), a biomarker of sleep apnoea effect. Complete demographics and polygraphy from 52 395 sequential patients referred for ambulatory sleep apnoea screening (www.sagatech.ca) using the Remmers Sleep Recorder (Sagatech Electronics Ltd., Calgary, Alberta, Canada) were assessed with descriptive analysis, analysis of variance, and Bayes Information Criteria (BIC) selected hierarchical cluster modelling (R 3.3.2, mclust 5.2). Inspiratory flow limitation was quantified breath by breath using an automated algorithm (US patent 8834387). 1.) Reviewing scatter plots showed inspiratory flow limitation remained elevated when eRDI did not with low Epworth scores. 2.) Inspiratory flow limitation, eRDI, and their interaction each had significant correlations with ESS (F: 55.49, 1073.71, 8.82; df = 1; all p << 0.01). 3.) BIC, classification, and density plots of cluster modelling showed three to four distinct groups within the 0 to 20% inspiratory flow limited range. 1.) Quantified breath by breath inspiratory flow limitation remained high in mild sleepiness unlike traditional eRDI. 2.) Inspiratory flow limitation and eRDI separately and together significantly correlated with sleepiness. 3.) Three to four tightly grouped clusters of inspiratory flow limitation severity were discerned, but are of unlikely clinical utility. Further analysis of gender effects is planned. RCPSC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".