Patient-Reported Outcome Measures in Neuromuscular Diseases: A Scoping Review
Bibliographic record
Abstract
Patient-reported outcome measures (PROMs) are valuable in comprehensively understanding patients' health experiences and informing healthcare decisions in research and clinical care without clinicians' input. Until now, no central resource containing information on all PROMS in neuromuscular diseases (NMD) is available, hindering the comparison and choice of PROMs used to monitor NMDs and appropriately reflect the patient's voice. This scoping review aimed to present a comprehensive assessment of the existing literature on using PROMs in children and adults with NMD. A scoping methodology was followed using Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines to assess the literature on PROMs in NMDs. Eligibility criteria encompassed articles describing psychometric development or evaluation of generic or disease-specific PROM-based instruments for adults and children with specific NMDs. The data charting process involved extracting measurement properties of included PROMs, comprising validity, reliability, responsiveness, and interpretability information. The review identified 190 PROMs evaluated across 247 studies in individuals with NMDs. The majority of PROMs were disease specific. The physical functioning domain was most assessed. Validity was the most frequently investigated measurement property, with a limited number of PROMs sufficiently evaluated for a range of psychometric characteristics. There is a strong need for further research on the responsiveness and interpretability of PROMs and the development of PROMs on social functioning in NMD.
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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 | 0.054 | 0.188 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.020 | 0.022 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".