Measurement properties of patient-reported outcome measures (PROMs) in adults with obstructive sleep apnea (OSA): A systematic review
Bibliographic record
Abstract
This systematic review summarizes the evidence regarding the quality of patient-reported outcome measures (PROMs) validated in patients with obstructive sleep apnea (OSA). We performed a systematic literature search of all PROMs validated in patients with OSA, and found 22 measures meeting our inclusion criteria. The quality of the studies was assessed using the consensus-based standards for the selection of health status measurement instruments (COSMIN) checklist. The results showed that most of the measurement properties of the PROMs were not, or not adequately, assessed. For many identified PROMs there was no involvement of patients with OSA during their development or before the PROM was tested in patients with OSA. Positive exceptions and the best current candidates for assessing health status in patients with OSA are the sleep apnea quality of life index (SAQLI), Maugeri obstructive sleep apnea syndrome (MOSAS) questionnaire, Quebec sleep questionnaire (QSQ) and the obstructive sleep apnea patient-oriented severity index (OSAPOSI). Even though there is not enough evidence to fully judge the quality of these PROMs as outcome measure, when interpreted with caution, they have the potential to add value to clinical research and clinical practice in evaluating aspects of health status that are important to patients.
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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 | 0.018 | 0.096 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".