Reducing Chronic Spine Pain in an Adult Male by Decreasing Lumbar Scoliosis and Increasing Cervical Lordosis Using Chiropractic BioPhysics® Protocols: A 26-Month Follow-Up Case Report
Bibliographic record
Abstract
We present a case report of a patient suffering from chronic low back pain (CLBP) and chronic non-specific neck pain (CNSNP), both of which were caused and complicated by a physically demanding occupation, a history of mixed martial arts, and lumbar scoliosis. Improvements in patient-reported outcomes (PROs) and radiographic findings were observed following conservative spine rehabilitation. The patient, a 34-year-old male, had experienced chronic spine pain, particularly CLBP and CNSNP, for several years. He reported severe pain and increasing disability after a recent neck injury sustained while practicing jiu-jitsu. Radicular pain, along with numbness and tingling, was noted in the right upper extremity, extending to the first three digits, and there were also altered sensations and temperature changes in both feet. He described sharp, pinching mid-back pain and worsening disability due to the persistent pain, which led him to seek manual manipulative chiropractic spine therapy, though he reported little benefit from it. The patient had relied on over-the-counter pain medications for many years without achieving long-term pain and disability relief, and these medications were no longer used following treatment. Chiropractic BioPhysics® (CBP®) spinal structural rehabilitation protocols were used to improve coronal and sagittal balance, as well as paraspinal muscular strength, addressing posture, mobility, and related aspects. These protocols include postural exercises, postural Mirror Image® traction, and postural spinal manipulative therapy. All PROs improved, with a near resolution of all initial symptoms of chronic spine pain. Outcomes measured included disability indices and health-related quality of life (HRQoL) indicators. Radiographic parameter improvements were significant, demonstrating improved coronal and sagittal balance as a result of the treatment. Following 30 in-office treatments, administered three times per week for 10 weeks, initial outcomes were reassessed. The patient then received 13 in-office treatments periodically over one year, and all initial outcomes were repeated. The improvements remained stable over time. A 26-month follow-up found that the improvements were sustained over a very long period without additional treatment after the 13-month examination. Chronic spine pain, specifically CLBP and CNSNP, is a significant source of suffering and contributes substantially to the global burden of disease. Improvement in HRQoLs, PROs, and objective spine parameters are desirable clinical outcomes. Our case report documents objective improvement in lumbar scoliosis and spine pain, which is rare in conservative studies. This successful treatment of chronic pain with long-term follow-up contributes to the growing evidence supporting conservative, non-surgical treatments for CNSNP and CLBP. Successful management of chronic spine pain was observed in a patient undergoing CBP® treatment. The treatment was designed to address abnormal sagittal and coronal postural balance and radiographic abnormalities indicating spinal misalignment and reassess progress in PROs, as well as objective and subjective HRQoL measures, both following treatment and 13 months later. However, larger studies are needed to draw firm conclusions regarding the efficacy of this treatment for chronic pain.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".