Late Breaking Abstract - Role of remotely measured REM sleep in the determination of clinical recovery from COPD exacerbations using wearable technology
Bibliographic record
Abstract
Introduction and Background: Chronic obstructive pulmonary disease (COPD) is characterized by breathlessness and acute exacerbations, a leading cause of adult hospitalization marked by worsening respiratory symptoms and multi-system pathophysiological changes. Aims and Objectives: To determine the clinical utility of remotely collected REM time, a distinct feature of sleep, as a marker of recovery from COPD exacerbations. Methods: Data from a completed longitudinal prospective study of 21 patients with moderate-to-very-severe COPD with a current exacerbation ( ClinicalTrials.gov NCT05776654 ) were used. REM sleep was measured with a biometric ring, for 21 consecutive days in the home environment. Recovery date was confirmed using the validated Exacerbation of Chronic Pulmonary Disease Tool (EXACT) Patient-Reported Outcome (PRO) tool. Analyses were performed using multivariable linear regression and t-tests. Results: By Day 21, REM sleep was 37% higher in the Recovered (n=10) when compared with the Persistent Worsening (n=11) (17.4[10.2, 24.7], P<0.001, Fig.1A). The greatest magnitude of improvement in REM sleep occurred in females, with an average increase of 32±8mins (Fig.1B). erj;66/suppl_69/PA2523/F1 F1 F1 Conclusions: REM sleep appears to be closely associated with the clinical status during exacerbations. Remote REM sleep monitoring may represent a simple approach to daily surveillance during an exacerbation.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.011 | 0.002 |
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".