What traditional, complementary, and integrative medicine recommendations exist across osteoporosis clinical practice guidelines? A systematic review and quality assessment
Bibliographic record
Abstract
BACKGROUND: Traditional, complementary and integrative medicine (TCIM) is sought by more than 50% of patients with osteoporosis. Despite this, many healthcare providers lack the knowledge to adequately counsel patients on safe and effective TCIM use. The purpose of this study was to determine the quantity and quality of TCIM recommendations in clinical practice guidelines (CPGs) for the treatment and/or management of osteoporosis. METHODS: MEDLINE, EMBASE and CINAHL databases, in addition to the Guidelines International Network, and the National Center for Complementary and Integrative Health website were searched from 2009-2020. CPGs making TCIM recommendations for the treatment/management of osteoporosis were assessed with the AGREE II instrument. RESULTS: Of 536 unique search results, 27 osteoporosis CPGs made mention of TCIM therapies. From highest to lowest, scaled domain percentages of all eligible CPGs averaged to 92.59% for scope and purpose, 88.79% for clarity in presentation, 55.04% for stakeholder involvement, 47.84% for editorial independence, 46.53% for rigor of development, and 36.96% for applicability. Of the 27 CPGs assessed, 4 CPGs were recommended as is by both appraisers, while 23 CPGs were recommended with modifications. CONCLUSIONS: Recommendations pertaining to calcium and vitamin D supplementation and exercise were favorably recommended across nearly all CPGs. In the case of other TCIM interventions, recommendations varied greatly, which may present challenges for CPGs target users due to a lack of consistency. Given the varying quality of osteoporosis CPGs found, those requiring improvement may benefit from their guideline development panel utilizing the AGREE II instrument to inform future updates.
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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 | 0.155 | 0.435 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.025 | 0.027 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".