Epilepsy and seizure disorders: A review of literature relative to chiropractic care of children
Bibliographic record
Abstract
Objective: To review the currently available literature regarding chiropractic care relative to patients with epilepsy, particular emphasis being placed on those who have epilepsy as children. Data Sources: The Index to Chiropractic Literature was searched for the years 1980 through 1998 through use of the keywords epilepsy and seizure. The MANTIS database was searched for the years 1970 through 2000 through use of the Medical Subject Heading (MeSH) keywords chiropractic, epilepsy, seizure , and child/children . In addition,a MEDLINE search ofthe literature was performed for the years 1966 through 2000 through use of the same subject headings. Results: The present study reviews 17 reports of pediatric epileptic patients receiving chiropractic care. Fourteen of the 17 patients were receiving anticonvulsive medications, which had proven unsuccessful in the management of the condition. Upper cervical care to correct vertebral subluxation was administered to 15 patients, and all reported positive outcomes as a result of chiropractic care. Conclusions: Chiropractic care may represent a nonpharmaceutical health care approach for pediatric epileptic patients. Current anecdotal evidence suggests that correction of upper cervical vertebral subluxation complex might be most beneficial. It is suggested that chiropractic care be further investigated regarding its role in the overall health care management of pediatric epileptic 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".