Resolution of Sporadic Hemiplegic Migraine by Correcting a Cervical Spine Kyphosis Utilizing the Chiropractic BioPhysics® (CBP®) Technique: A Case Report With Long-Term Follow-Up
Bibliographic record
Abstract
A 19-year-old male suffered from sporadic hemiplegic migraine (SHM) for several years and experienced significant pain and disability with sensory and motor disturbances during the migraine headaches. Weakness, abnormal vision, abnormal sensation, one-sided disabling motor weakness, and other signs of SHM were diagnosed. The patient had received previous physical therapy, chiropractic and over-the-counter medications, as well as migraine-specific prescriptions without lasting improvements. Chiropractic BioPhysics® (CBP®) spinal structural rehabilitation protocols were used to increase cervical lordosis and improve cervical muscular strength, mobility, and posture. These protocols include spine-specific prescriptions for Mirror Image® postural exercises, traction, and spinal manipulative therapy. After 24 treatments over eight weeks, all subjective and objective outcomes improved dramatically with a near resolution of all initial symptoms of SHM. There were a significant increase in cervical lordosis and a reduction in forward head posture. The neck disability index improved from 26% to 6%, and all pain scores for all regions improved following treatment. A 10-month follow-up exam showed the outcomes were maintained. SHM is rare and debilitating, is part of the global burden of disease, and is a major cause of disability in the world. Reports of successful conservative and non-conservative long-term treatments for SHM are rare, and there are no clinical trials showing successful treatments for SHM. This successful case demonstrates preliminary evidence that CBP spinal structural rehabilitation may serve as a treatment option for SHM. Future studies are needed to replicate the findings from this case.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".