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Record W4375954592 · doi:10.1503/cmaj.221219

Recommendations on screening for primary prevention of fragility fractures

2023· article· en· W4375954592 on OpenAlexaffvenueabout
Guylène Thériault, Heather Limburg, Scott Klarenbach, Donna L. Reynolds, John J. Riva, Brett D. Thombs, Laure Tessier, Roland Grad, Brenda J. Wilson

Bibliographic record

VenueCanadian Medical Association Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMcMaster UniversityHamilton Health SciencesUniversity of TorontoMemorial University of NewfoundlandPublic Health Agency of CanadaUniversity of AlbertaMcGill University
Fundersnot available
KeywordsPrimary preventionFragilityComputer sciencePrimary (astronomy)Fragility fractureMedicineData sciencePathologyOsteoporosis

Abstract

fetched live from OpenAlex

BACKGROUND: Fragility fractures are a major health concern for older adults and can result in disability, admission to hospital and long-term care, and reduced quality of life. This Canadian Task Force on Preventive Health Care (task force) guideline provides evidence-based recommendations on screening to prevent fragility fractures in community-dwelling individuals aged 40 years and older who are not currently on preventive pharmacotherapy. METHODS: We commissioned systematic reviews on benefits and harms of screening, predictive accuracy of risk assessment tools, patient acceptability and benefits of treatment. We analyzed treatment harms via a rapid overview of reviews. We further examined patient values and preferences via focus groups and engaged stakeholders at key points throughout the project. We used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach to determine the certainty of evidence for each outcome and strength of recommendations, and adhered to Appraisal of Guidelines for Research and Evaluation (AGREE), Guidelines International Network and Guidance for Reporting Involvement of Patients and the Public (GRIPP-2) reporting guidance. RECOMMENDATIONS: We recommend "risk assessment-first" screening for prevention of fragility fractures in females aged 65 years and older, with initial application of the Canadian clinical Fracture Risk Assessment Tool (FRAX) without bone mineral density (BMD). The FRAX result should be used to facilitate shared decision-making about the possible benefits and harms of preventive pharmacotherapy. After this discussion, if preventive pharmacotherapy is being considered, clinicians should request BMD measurement using dual-energy x-ray absorptiometry (DXA) of the femoral neck, and re-estimate fracture risk by adding the BMD T-score into FRAX (conditional recommendation, low-certainty evidence). We recommend against screening females aged 40-64 years and males aged 40 years and older (strong recommendation, very low-certainty evidence). These recommendations apply to community-dwelling individuals who are not currently on pharmacotherapy to prevent fragility fractures. INTERPRETATION: Risk assessment-first screening for females aged 65 years and older facilitates shared decision-making and allows patients to consider preventive pharmacotherapy within their individual risk context (before BMD). Recommendations against screening males and younger females emphasize the importance of good clinical practice, where clinicians are alert to changes in health that may indicate the patient has experienced or is at higher risk of fragility fracture.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.061
metaresearch head score (Gemma)0.272
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.272
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.012
Bibliometrics0.0110.008
Science and technology studies0.0020.002
Scholarly communication0.0050.006
Open science0.0090.005
Research integrity0.0150.012
Insufficient payload (model declined to judge)0.0200.010

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.

Opus teacher head0.043
GPT teacher head0.383
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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".

Quick stats

Citations24
Published2023
Admission routes3
Has abstractyes

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