Patient Reported Outcome Measures in Adult Spinal Muscular Atrophy: A Scoping Review and Graphical Visualization of the Evidence
Bibliographic record
Abstract
BACKGROUND: Spinal Muscular Atrophy (SMA) is a hereditary neuromuscular disease with an estimated prevalence of 1/10 000 births. SMA is increasingly recognized as a multi-system disease with a need to study additional under-recognized health domains such as quality of life, fatigue, bulbar function, respiratory function, and independence. OBJECTIVE: Identify and assess reported evidence from the literature investigating Patient Reported Outcome Measures (PROMs) in adults with SMA. Develop a novel method drawing from network theory to graphically depict the literature, PROMs, and supporting psychometric evidence. METHODS: A scoping review was completed following PRISM-ScR, COSMIN and JBI scoping review guidelines. Literature investigating PROMs in adult SMA or neuromuscular disease was identified from peer-reviewed and grey databases. A network graph was derived from extracted data. RESULTS: 5292 articles were retrieved, 81 articles met inclusion criteria; corresponding to 31 unique PROMs. Only two PROMs were developed specifically for SMA. Few PROMs covered multiple domains of health. Most PROMs were incompletely validated, focusing on concurrent validity, and few assessed responsiveness or internal consistency. CONCLUSIONS: PROMs are emerging tools for monitoring and assessing adults with SMA. Despite their potential benefits, additional validation studies should be completed prior to their use for clinical decision-making. Network graphics may represent a technique to aid in the visualization of evidence supporting a scoping review.
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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 | 0.035 | 0.122 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.030 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".