The Intelligent Automated Pressure-Adjustable Orthosis for Patients With Adolescent Idiopathic Scoliosis
Bibliographic record
Abstract
STUDY DESIGN: Randomized controlled trial. OBJECTIVE: To compare the effectiveness of the automated pressure-adjustable orthosis (PO) and conventional orthosis (CO) for treatment of adolescent idiopathic scoliosis (AIS). SUMMARY OF BACKGROUND DATA: Orthosis wearing quality may influence its effectiveness for AIS. An automated PO aimed to provide a more optimized and consistent biomechanical environment. Clinical evaluation was conducted to study the effectiveness of this innovative orthosis. METHODS: Patients with AIS who met the criteria (Age 10-14, Cobb 20°-40°, and Risser sign 0-2) were recruited from two clinics and randomly assigned to the PO and CO groups. Compliance sensors were embedded in both groups, while the PO group was set to adjust the interfacial pressure as prescribed automatically. Clinical assessments (radiology and quality of life, QoL) were conducted at the baseline, immediate after orthosis fitting and 1-year follow-up. Orthosis wearing compliance was tracked using thermo and pressure sensors. RESULTS: Twenty-four patients were enrolled with one drop-out (PO, n = 11; CO, n = 12). Significant immediate in-orthosis correction was observed in the PO (11.0° ± 6.5°, 42.0%, P < 0.001) and CO (10.3° ± 5.3°, 37.6%, P < 0.001) groups. After 1 year, no patient with PO progressed while two with CO had progression more than 5°. The mean daily wearing duration was 1.1 hours longer in the PO group as compared with the CO group (15.4 ± 4.5 vs. 14.3 ± 3.8 h). Moreover, the wearing quality within the targeted pressure was 33.9% higher in the PO group (56.5 ± 16.5% vs. 23.1 ± 12.1%, P < 0.001). No significant difference in the QoL results was observed between two groups nor within both groups during the study period. CONCLUSION: This study showed that the automated PO could enhance wearing quality when compared with the CO, thus offering a better biomechanical corrective effect in the study period without adverse effect on the patients' wearing quantity and QoL. LEVEL OF EVIDENCE: 1.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".