Prevalence of Pain within Limb Girdle Muscular Dystrophy R9 and Implications for Other Degenerative Diseases
Bibliographic record
Abstract
Our primary aim was to establish the prevalence of pain within limb girdle muscular dystrophy R9 (LGMDR9). As part of the Global FKRP Registry, patients are asked to complete the Short Form McGill Pain Questionnaire (SF-MPQ) annually. We used the results of this questionnaire to determine individuals' maximum pain score and total pain score and examined overall pain intensity and associations between pain intensity and LGMDR9 genotypes, age, and ambulatory status. We also considered the pain descriptors used and pain progression over time. Of the 502 patients, 87% reported current pain and 25% reported severe current pain. We found no associations in pain severity between the different genotypes of LGMDR9. However, we did find statistically significant associations between pain severity and ambulatory status and between our paediatric and adult populations. We found pain descriptors to be more common words that one may associate with non-neural pain, and we found that a significant number of individuals (69%) reported a fluctuating pain pattern over time. We concluded that pain should be considered a significant issue among individuals with LGMDR9 requiring management. Implications regarding assessment of pain for other degenerative diseases are discussed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".