A Single-Group Pretest Posttest Design Using Full Kinetic Chain Manipulative Therapy With Rehabilitation in the Treatment of 18 Patients With Hip Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: Hip osteoarthritis (HOA) affects 30 million Americans or more, and is a leading cause of disability, suffering, and pain. Standard treatments are minimally effective and carry significant risk and expense. This study assessed treatment effects of a chiropractic protocol for HOA. METHODS: Eighteen individuals, who did not qualify due to low baseline Western Ontario and McMaster Osteoarthritis Index scores (WOMAC) for other ongoing HOA randomized control trials, were selected. A prospectively planned protocol, consisting of axial manipulation to the affected hip with modified Thomas and active assisted stretch, was combined with full kinetic chain treatment or manipulative therapy to the spine, knee, ankle, or foot and assessed with use of valid and reliable outcome measures. RESULTS: The primary outcome measure, the Overall Therapy Effectiveness Tool, was assessed with chi(2) and demonstrated that 83.33% of participants were improved after the ninth visit, P = .005, and 78% improved at the 3-month follow-up, P = .018. Using the paired t test, WOMAC was improved 64% at the ninth visit, P = .000, and 47% at follow-up, P = .016. CONCLUSION: In HOA patients with lower WOMAC scores, a highly organized HOA treatment appears to have resulted in statistically and clinically meaningful intragroup changes in the Overall Effectiveness Therapy Tool, WOMAC, Harris Hip Scale, and range of motion, all with P
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".