Critical Evaluation of the 2016 SOSORT Clinical Guidelines on the Detection and Clinical Management of Adolescent Idiopathic Scoliosis Using the AGREE II Tool: A Chiropractic Perspective
Bibliographic record
Abstract
Objective The objective of this study is to assess the methodological quality of the 2016 Society on Scoliosis Orthopaedic and Rehabilitation Treatment (SOSORT) guidelines for the detection and management of adolescent idiopathic scoliosis . Methods A diverse group of experts, including practicing chiropractors , chiropractors with a Diplomate by the American Chiropractic Board of Radiology , chiropractors with PhD degrees, and chiropractors involved in teaching within chiropractic programs was invited to participate in the study. Experts independently evaluated the guidelines using the Appraisal of Guidelines for Research and Evaluation II tool. Individual scaled scores were calculated for each item and the 6 domains, with methodological quality considered good if the score was equal to or greater than 70%. Results The 19 experts, including 6 clinicians, 4 chiropractic radiologists, 6 researchers, and 3 lecturers, represented Canada ( n = 3), United states ( n = 4), France ( n = 2), Australia ( n = 1), United Kingdom ( n = 1), Switzerland ( n = 1), Sweden ( n = 3), Denmark ( n = 2), China ( n = 1), and Côte d'Ivoire ( n = 1). Domain scaled scores ranged from 38% to 90%. The 4 items of the applicability domain scored between 26% and 45%. The experts made suggestions for improving the applicability of the guidelines’ recommendations. Conclusion The methodological quality of the 2016 SOSORT clinical practice guidelines was deemed good. However, strategies should be devised to improve their applicability. This could be achieved by involving a more diverse representation of healthcare professions in the development of future guidelines.
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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 | 0.587 | 0.843 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.021 | 0.012 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".