Recommendations for the prevention of osteoporosis and fragility fractures. International comparison and synthesis.
Bibliographic record
Abstract
OBJECTIVES: This review included the following objectives: a) to synthesize recommendations made by public agencies in Western countries concerning screening for osteoporosis; b) to compare these recommendations and sort out the similarities and discrepancies; and c) to propose a strategy for the fight against osteoporosis and fragility fractures. METHODS: Eleven reports published by publicly financed agencies were included in the analysis: three international, four North American and four European agencies. Transcriptions of recommendations and arguments were classified using criteria for evaluation of screening technologies. RESULTS: Of eight reports that made a recommendation on mass screening, four made a recommendation against the use of densitometry, two remained vague with a conditionally positive recommendation, and two made no recommendation, arguing insufficient scientific evidence. Concerning screening of asymptomatic women in the perimenopause period, recommendations were uniformly opposed to the use of bone densitometry in five of nine reports, and the other four made no recommendation, arguing insufficient scientific evidence. Some of the discrepancies can be explained by the different definitions given to osteoporosis and by the confusion of terms between screening and diagnostic testing. A strategy is proposed to ensure that all women who are at risk of osteoporosis and fragility fracture have access to preventive measures. This strategy is based on the complementarity and coordination of roles between health promotion interventions and clinical interventions. CONCLUSIONS: Prevention of osteoporosis and fragility fractures is an attainable goal. Existing resources are currently badly targeted. Compromises must be negotiated between the different stakeholders and biomedical disciplines to achieve efficiency and accessibility in the reduction of fragility fractures. A first compromise to reconcile social and scientific realities would be to use a best-evidence synthesis instead of an evidence-based medicine approach in future analyses and recommendations by public authorities. A second compromise would be to recognize the complementary roles of public health and clinical professionals toward the common objective of preventing fragility fractures.
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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 | 0.065 | 0.170 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 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".