Improvements in one severe progressive multiple sclerosis patient quality of life after an intensity fluid dynamic treatment.
Bibliographic record
Abstract
Clinical case: A 49-year-old man (MM72) affected by Secondary Progressive Multiple Sclerosis (SP-MS) since 1998. On last 3 years, neurologists valued 9.0 the patient MM72's EDSS. Methods: MM72 was treated by acoustic waves, modulated in frequency and power by the MAM device, according to an ambulatory intensive protocol. Patient's treatments schedule was organized in thirty cycles of DrenoMAM and AcuMAM, and manual cervical spinal adjustments. Before and after treatments, MSIS-29, Barthel, FIM, EDSS, ESS, and FSS questionnaires were administered to the patient. Results: MM72 patient had improvements in all index score (MSIS-29, Barthel, FIM, EDSS, ESS and FSS) after 30 treatments by MAM plus cervical spine chiropractic adjustments. He showed a significative improvement of his disability and the restore of many functions. After MAM treatments, MM72's cognitive sphere improved of 370%. Fur-thermore, after 5 years of paraplegy, he regained his lower limbs and feet fingers movements with an increase of 230%. Conclusion: We suggest ambulatory intensive treatments by fluid dynamic MAM protocol in SP-MS patients. Statistical analyses are in progress on a larger sample of SP-MS 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".