A specialized exercise programme for a patient suffering from eosinophilic meningitis
Bibliographic record
Abstract
Aims The aim of this study was to determine whether a specialized exercise program, including vibration training, resistance exercise and stretching, improved health, fitness and quality of life in a patient suffering from chronic pain due to skin hypersensitivity, insomnia, irritability and depression, all associated with eosinophilic meningitis, with pain exacerbated during exercise. Methods The 20-–30-minute program incorporated stretching, lower-body exercises performed on a vibration platform and upper-body resistance exercises, which were performed three times a week within an air-conditioned environment. The patient wore a tight-fitting long-sleeve shirt to minimize skin pain. Pre- and post-assessments included body mass index, girth, cholesterol, resting heart rate and blood pressure, mobility, strength, endurance and flexibility. Findings The patient completed all 36 exercise sessions, resulting in an average 14% (2–25%) improvement in health, 42% (19–103%) improvement in functional fitness, and improved quality of life measures as stated by the patient. Despite experiencing chest skin pain during vibration training, the combination of the air-conditioned environment, as well as the short duration of the sessions, the use of a long-sleeved shirt and the proximity of the patient's house to the clinic, helped him control his pain. Conclusions The set programme with pain-control measures was a successful exercise combination for the patient who was previously unable to undertake regular exercise due to pain associated with skin hypersensitivity from meningitis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".