Analysis of Prednisolone-Induced Osteoporosis Using the Japanese Adverse Drug Event Report Database
Bibliographic record
Abstract
PURPOSE: Osteoporosis is an adverse event of prednisolone. This study aimed to assess prednisolone-induced osteoporosis (PIO) profiles and patient backgrounds by analyzing data from the Japanese Adverse Drug Event Report (JADER) database. METHODS: The current study focused only on orally administered prednisolone. PIO was defined using preferred terms from the Medical Dictionary for Regulatory Activities. Reporting odds ratio (ROR) at 95% confidence interval (CI) and the time-to-onset profile of PIO were used to evaluate adverse events. RESULTS: The RORs (95% CI) of the female and male subgroups were 4.73 (4.17-5.38) and 2.49 (2.06-3.00), respectively. The analysis of time-to-onset profiles demonstrated that the median values (interquartile range: 25.0-75.0%) of PIO were 136 (74.0-294.0). The prednisolone treatment duration was significantly longer in the PIO patient group than in the non-PIO patient group. The findings suggest that patients with rheumatoid arthritis, systemic lupus erythematosus, and nephrotic syndrome receiving prednisolone have different age-related PIO profiles. CONCLUSIONS: Our results suggest that longer prednisolone treatment duration and larger cumulative dose might be risk factors of PIO. The potential risk for PIO should not be overlooked, and careful observation is recommended.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".