The treatment and rationale for the correction of a cervical kyphosis spinal deformity in a cervical asymptomatic young female: a Chiropractic BioPhysics<sup>®</sup> case report with follow-up
Bibliographic record
Abstract
[Purpose] To present a case demonstrating dramatic restoration of the cervical lordosis and reduction of forward head posture by use of Chiropractic BioPhysics® (CBP®) technique. [Participant and Methods] A 24-year-old cervical asymptomatic female presented with poor craniocervical posture. Radiography revealed forward head posture and an exaggerated cervical kyphosis. [Results] The patient received CBP care including mirror image® cervical extension exercises, cervical extension traction and spinal manipulative therapy. After 36 treatments over 17-weeks, repeat radiography demonstrated a dramatic improvement of an alteration of the cervical kyphosis to a lordosis and a reduction of forward head posture. Subsequent treatment increased the lordosis further. Long-term follow-up at 3.5 years showed some loss of original correction, however, a maintenance of the global lordosis. [Conclusion] This case demonstrates that non-surgical reversal of a cervical kyphosis to a lordosis is possible in a short time using CBP cervical extension protocols. It is logical if the kyphosis had not been corrected, over time, osteoarthritis and various craniovertebral symptoms would have evolved as the literature indicates. The diagnosis of gross spinal deformity, we argue, requires its correction prior to the onset of symptoms and permanent degenerative changes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.005 | 0.002 |
| 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".