AO Spine Clinical Practice Recommendations: Evaluation, Implications and Management of Osteoporosis in Adult Spinal Deformity
Bibliographic record
Abstract
Study designLiterature review with clinical recommendation.ObjectivesTo provide the readers with a concise curation of the relevant spine literature regarding the identification and management of osteoporosis in patients with adult spinal deformity (ASD) and set out recommendations for how the practicing clinician should interpret and make use of this evidence.MethodsKey articles from the published literature surrounding osteoporosis in patients being treated for ASD were reviewed and clinical recommendations were formulated by consensus. The recommendations are dichotomously graded into strong and conditional after integrating an assessment of methodological quality and expert opinion. This opinion considers experience and practical issues such as risks, burdens, costs, patient values, and circumstances.Results6 articles were selected by practicing spinal deformity surgeons and each evaluated for the strength of methodology and scientific evidence.ConclusionsThe current evidence suggests that preoperative evaluation of osteoporosis before ASD surgery should be routine. Additionally, there is clinical benefit in using anabolic agents for at least 3 months to improve bone stock and prevent mechanical complications. While high quality, strong evidence is still yet to be reported, all healthcare providers managing patients with ASD should be aware of the importance of bone health for optimizing post-operative outcomes and minimising complications.
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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 | 0.039 | 0.201 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".