The use of a large pharmacoepidemiological database to study exposure to oral corticosteroids and risk of fractures: validation of study population and results
Bibliographic record
Abstract
Purpose - The objective of this study was an evaluation of the sensitivity of findings of the relationship between oral corticosteroid use and the risk of fracture. We found in earlier work that the risk of fracture was significantly higher during oral corticosteroid treatment, with increases of 61% in hip and 160% in vertebral fractures.Methods - Information was obtained from the General Practice Research Database which contains medical records of general practitioners in the UK. The study included 244,235 oral corticosteroid users and 244,235 controls.Results - The validation of fracture cases showed that the hip fractures, as recorded in the GPRD, were confirmed by the GP on the questionnaire in 90.7% of the cases and by discharge summary in 86.5%. The relative rate of non-vertebral fracture during oral corticosteroid use did not vary substantially between patients with different diseases, age, or gender. The sensitivity analysis, modifying the type of analysis or inclusion of patients, did not materially change the findings.Conclusions - We found a high level of validity of the GPRD with respect to hip and vertebral fractures. The sensitivity analysis indicated internal validity and consistency of the findings on fracture risks of oral corticosteroid therapy. Copyright (c) 2000 John Wiley & Sons, Ltd.
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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 | 0.070 | 0.205 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".