Scoring criteria for portable monitor recordings: a comparison of four hypopnoea definitions in a population-based cohort
Bibliographic record
Abstract
RATIONALE: Limited-channel portable monitors (PMs) are increasingly used as an alternative to polysomnography (PSG) for the diagnosis of obstructive sleep apnoea (OSA). However, recommendations for the scoring of PM recordings are still lacking. Pulse-wave amplitude (PWA) drops, considered as surrogates for EEG arousals, may increase the detection sensitivity for respiratory events in PM recordings. OBJECTIVES: To investigate the performance of four different hypopnoea scoring criteria, using 3% or 4% oxygen desaturation levels, including or not PWA drops as surrogates for EEG arousals, and to determine the impact of measured versus reported sleep time on OSA diagnosis. METHODS: Subjects drawn from a population-based cohort underwent a complete home PSG. The PSG recordings were scored using the 2012 American Academy of Sleep Medicine criteria to determine the apnoea-hypopnoea index (AHI). Recordings were then rescored using only parameters available on type 3 PM devices according to different hypopnoea criteria and patients-reported sleep duration to determine the 'portable monitor AHIs' (PM-AHIs). MAIN RESULTS: 312 subjects were included. Overall, PM-AHIs showed a good concordance with the PSG-based AHI although it tended to slightly underestimate it. The PM-AHI using 3% desaturation without PWA drops showed the best diagnostic accuracy for AHI thresholds of ≥ 5/h and ≥ 15/h (correctly classifying 94.55% and 93.27% of subjects, respectively, vs 80.13% and 87.50% with PWA drops). There was a significant but modest correlation between PWA drops and EEG arousals (r=0.20, p=0.0004). CONCLUSION: Interpretation of PM recordings using hypopnoea criteria which include 3% desaturation without PWA drops as EEG arousal surrogate showed the best diagnosis accuracy compared with full PSG.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".