Multidisciplinary Rehabilitation of a Patient With Neuromyelitis Optica
Bibliographic record
Abstract
Background and Objectives: Neuro Myelitis Optica (NMO) is a rare progressive and disabling autoimmune disease. The disabling consequences of the disease affect many aspects of the patients and their family life. multidisciplinary rehabilitation can be very effective in promoting quality of life and slowing disease progression by working with different disciplines. The aim of this study is to report the effects of multidisciplinary rehabilitation on the performance and quality of life of a patient with NMO and her family. Case Report: This study reports a six-month multidisciplinary rehabilitation program conducted for a woman with NMO and her caregiver. The rehabilitation team included the patient’s caregiver, a neurologist, an occupational therapist, and a speech therapist. The approaches of stabilization and recovery, maintenance, modification, and prevention were used through 70 sessions of occupational therapy. Also, the occupational performance was assessed with the Canadian Occupational Performance Measure. Furthermore, the Persian version of SF36 was used to assess the quality of life. The speech therapy intervention was performed in 24 sessions and included breath strengthening exercises, sound therapy, and laryngeal muscle manipulation. After six months, the results showed a great improvement in the quality of life of the patient and her caregiver. Conclusion: The use of team approaches in the face of progressive neurodegenerative diseases such as NMO has a significant impact on improving the quality of life of these patients and their families.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".