Osteopathic Manual Treatment for Amyotrophic Lateral Sclerosis: A Feasibility Pilot Study
Bibliographic record
Abstract
BACKGROUND: Current interventions in amyotrophic lateral sclerosis (ALS) are focused on supporting quality of life (QoL) and easing pain with a multidisciplinary approach. OBJECTIVE: Primary aim of this pilot work assessed feasibility, safety, tolerability and satisfaction of osteopathic manual treatment (OMT) in 14 ALS outpatients. METHODS: Patients were randomized according to an initial single-blind design (12 weeks, T0-T1), in order to receive OMT (weekly for 4 weeks, and fortnightly for the following 8 weeks) versus usual-care (n=7 each group), followed by an OMT open period (T1-T2, once a week for 8 weeks, n=10). Secondary aims included blind osteopathic assessment of somatic dysfunctions (SD) for goal attainment scale (GAS) calculation, Brief Pain Inventory-short form and McGill QoL-16 items. RESULTS: OMT was demonstrated feasible and safe and patients displayed high satisfaction (T1-VAS=8.34 ± 0.46; T2-VAS=8.52 ± 0.60). Considering secondary aims no significant differences emerged. Finally, at study entry (T0), a cervico-dorsal SD was found in 78% of ALS patients versus 28% of healthy matched controls (p<0.01). CONCLUSION: OMT was found feasible, safe and satisfactory in ALS. The lack of secondary aim differences can be due to the limited sample size. OMT could be an interesting option to explore in ALS.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".