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Record W4387500147 · doi:10.1503/cmaj.221647

Clinical practice guideline for management of osteoporosis and fracture prevention in Canada: 2023 update

2023· article· en· W4387500147 on OpenAlexafffundvenueabout
Suzanne N. Morin, Sidney Feldman, Larry Funnell, Lora Giangregorio, Sandra Kim, Heather McDonald-Blumer, Nancy Santesso, Rowena Ridout, Wendy E. Ward, Maureen C. Ashe, Zahra Bardai, Joan Bartley, Neil Binkley, Steven Burrell, Debra A. Butt, Suzanne M. Cadarette, Angela M. Cheung, Phil Chilibeck, Sheila Dunn, Jamie Falk, Heather Frame, William Gittings, Kaleen N. Hayes, Carol Holmes, George Ioannidis, Susan Jaglal, Robert G. Josse, Aliya Khan, Virginia McIntyre, Lynn Nash, Ahmed Negm, Αλεξάνδρα Παπαϊωάννου, Matteo Ponzano, Isabel B. Rodrigues, Lehana Thabane, Christine A Thomas, Lianne Tile, John D. Wark

Bibliographic record

VenueCanadian Medical Association Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMcGill University
FundersUniversity of WaterlooMcMaster UniversityOsteoporosis Canada
KeywordsGuidelineMedicinePsychological interventionOsteoporosisGrading (engineering)Quality managementFamily medicineRisk assessmentPhysical therapyNursingPathology

Abstract

fetched live from OpenAlex

BACKGROUND: In Canada, more than 2 million people live with osteoporosis, a disease that increases the risk for fractures, which result in excess mortality and morbidity, decreased quality of life and loss of autonomy. This guideline update is intended to assist Canadian health care professionals in the delivery of care to optimize skeletal health and prevent fractures in postmenopausal females and in males aged 50 years and older. METHODS: This guideline is an update of the 2010 Osteoporosis Canada clinical practice guideline on the diagnosis and management of osteoporosis in Canada. We followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework and quality assurance as per Appraisal of Guidelines for Research and Evaluation (AGREE II) quality and reporting standards. Primary care physicians and patient partners were represented at all levels of the guideline committees and groups, and participated throughout the entire process to ensure relevance to target users. The process for managing competing interests was developed before and continued throughout the guideline development, informed by the Guideline International Network principles. We considered benefits and harms, patient values and preferences, resources, equity, acceptability and feasibility when developing recommendations; the strength of each recommendation was assigned according to the GRADE framework. RECOMMENDATIONS: The 25 recommendations and 10 good practice statements are grouped under the sections of exercise, nutrition, fracture risk assessment and treatment initiation, pharmacologic interventions, duration and sequence of therapy, and monitoring. The management of osteoporosis should be guided by the patient's risk of fracture, based on clinical assessment and using a validated fracture risk assessment tool. Exercise, nutrition and pharmacotherapy are key elements of the management strategy for fracture prevention and should be individualized. INTERPRETATION: The aim of this guideline is to empower health care professionals and patients to have meaningful discussions on the importance of skeletal health and fracture risk throughout older adulthood. Identification and appropriate management of skeletal fragility can reduce fractures, and preserve mobility, autonomy and quality of life.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.504
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.386
Teacher spread0.361 · 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 teacher head, not a consensus.

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

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

Citations186
Published2023
Admission routes4
Has abstractyes

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