Reduction of thoraco-lumbar kyphosis results in the alleviation of low back pain in an adolescent basketball player: a Chiropractic Biophysics<sup>®</sup> (CBP<sup>®</sup>) case report
Bibliographic record
Abstract
[Purpose] To present the case of a significant reduction in thoraco-lumbar deformity and alleviation of chronic low back pain in an otherwise healthy and active adolescent male basketball player. [Participant and Methods] A 17 year old was assessed with chronic low back pain persisting for 4 years. Radiographic assessment revealed a prominent thoraco-lumbar kyphosis. Chiropractic Biophysics® structural rehabilitation including mirror image® exercise and traction methods as well as spinal manipulative therapy was performed 2–3 times per week. [Results] There was a 12° improvement in the thoraco-lumbar deformity corresponding with the alleviation of chronic low back pains and near complete reduction in disability after 36 treatments over a 4-month period. [Conclusion] This case adds to the growing literature showing the efficacy of the non-surgical spinal rehabilitative methods of Chiropractic Biophysics in improving spine alignment and relieving spinal pain syndromes. This case also demonstrates the importance of the routine screening for spine alignment via radiography in leading to proper biomechanical diagnosis and treatment.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".