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Public health impact of adverse bone effects of oral corticosteroids

2001· article· en· W2106926670 on OpenAlexaff
Tjeerd van Staa, Lucien Abenhaim, Cyrus Cooper, B. Zhang, Hubert G. M. Leufkens

Bibliographic record

VenueBritish Journal of Clinical Pharmacology · 2001
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineCorticosteroidPrednisoloneAdverse effectMedical recordPediatricsSurgeryDentistryInternal medicine

Abstract

fetched live from OpenAlex

AIMS: The objective of this study was to estimate the number of fractures attributed to oral corticosteroid use. METHODS: Information was obtained from the General Practice Research Database which contains medical records of general practitioners in the UK. The total number of corticosteroid-related fractures during a course of treatment was estimated using the formula for attributable risk among the exposed. RESULTS: A total of 244 235 patients was prescribed an oral corticosteroid. The rate of hip fractures increased exponentially with age in both males and females. The excess number of hip fracture cases among females aged 85 years or older using 7.5 mg prednisolone per day or more was 1.4 cases per 100 patients per year. About 47% of all hip and 72% of all vertebral fractures that occurred can be attributed to oral corticosteroid use. Among 10 000 female users of higher doses, 99.7 nonvertebral, 31.6 hip and 45.8 vertebral fractures can be attributed to use of oral corticosteroids. CONCLUSIONS: The targeting of high-risk patients will be important for implementing preventative strategies in a cost-effective manner.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.150
GPT teacher head0.513
Teacher spread0.362 · 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 designObservational
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

Citations69
Published2001
Admission routes1
Has abstractyes

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