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Record W2033216103 · doi:10.1097/bor.0000000000000065

Implementation research in osteoporosis

2014· review· en· W2033216103 on OpenAlexafffund
Sumit R. Majumdar

Bibliographic record

VenueCurrent Opinion in Rheumatology · 2014
Typereview
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Alberta
FundersAlberta Innovates - Health Solutions
KeywordsMedicineOsteoporosisMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To provide an update of recent and influential studies of implementation research in osteoporosis. RECENT FINDINGS: In recent years, several implementation interventions have been designed and tested to improve osteoporosis screening (primary prevention), increase bone mineral density testing and treatment after a fracture (secondary prevention), and enhance shared decision-making along with long-term medication adherence and persistence. Different forms of care coordination, from multifaceted interventions through labor-intensive and capital-intensive 'fracture liaison services', seem most consistently to improve quality of osteoporosis care. When randomized trials (rather than observational studies) are used to test these various interventions, they are often found to be ineffective, and even when they are effective, the effect sizes are modest and less than had been anticipated by researchers or required by decision-makers. However, even modest effects have been shown in economic analyses to be very cost-effective or cost-saving. SUMMARY: Although osteoporosis implementation research has tended to lag behind other conditions such as coronary disease or diabetes, in recent years, the number, quality, novelty, and rigor of osteoporosis intervention trials have substantially increased - though much more work remains to be done.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.905
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.324
GPT teacher head0.583
Teacher spread0.260 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2014
Admission routes2
Has abstractyes

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