Improved postural control in a patient having adult spinal deformity and previous thoraco-lumbar scoliosis surgery: a Chiropractic Biophysics® case report
Bibliographic record
Abstract
Background: ) posture rehabilitation as well as balance rehabilitation in an elderly patient with long-standing spinal deformity including thoracic hyperkyphosis and a T10-L4 Harrington rod instrumentation for thoracolumbar scoliosis. Case Description: A 69-year-old female presented with the main complaint of balance and gait impairment as well as back pain and headaches. Balance assessment on a force plate showed impaired balance, in the vestibular challenging condition (eyed closed; standing on foam). Radiography showed a forward stooped posture and surgical hardware. Treatment was directed at posture by CBP methods and balance rehabilitation by a whole-body vibration exercise program. Treatment progressed over a 10-month period. The patient experienced relief of back pains and headaches. There was a clinically significant improvement in posturography including a 102 cm reduction in center of pressure (COP) path length. There was an inch reduction in forward sagittal stoop. Conclusions: A non-surgical rehabilitation program demonstrated a clinically significant improvement in balance performance in an elderly female diagnosed with osteopenia, spinal deformity, and previous spine deformity surgery. This approach to improving postural stability is important and further investigations should be undertaken.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 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".