Cumulative Burden of Glucocorticoid-related Adverse Events in Patients with Systemic Lupus Erythematosus: Findings from a 12-year Longitudinal Study
Bibliographic record
Abstract
OBJECTIVE: The aim of this population-based study is to examine the adverse events (AE) associated with longitudinal systemic glucocorticoid (GC) use among an ethnic Chinese systemic lupus erythematosus (SLE) cohort. METHODS: Our study subjects were patients with newly diagnosed SLE aged 18 and older who received at least 1 prescription of systemic GC between 2001 and 2012 from Taiwan's National Health Insurance Research Database (NHIRD). The earliest prescription date of systemic GC for each subject was defined as the index date. For each subject, we calculated the average prednisolone-equivalent dose and the medication possession ratio (MPR) of GC use every 90 days for each patient after the index date. Patients with a diagnosis of AE (defined by the International Classification of Diseases-9-Clinical Modification diagnosis code) during the followup were also identified from the NHIRD. Generalized estimating equations adjusted for propensity score were applied to examine the association between longitudinal GC use and risks of prespecified AE (musculoskeletal, gastrointestinal, ophthalmologic, infectious, cardiovascular, neuropsychiatric, metabolic, and dermatologic diseases). RESULTS: We identified 11,288 patients with SLE (mean followup: 6.28 yrs). Higher doses and higher MPR of GC were associated with increased risk of osteonecrosis [adjusted OR (aOR) 2.87-9.09]. Similar results were found regarding the risk of osteoporosis (aOR 1.71-3.67), bacterial infection (aOR 2.12-3.89), Cushingoid syndrome (aOR 6.51-62.03), and sleep disorder (aOR 1.42-3.59). CONCLUSION: To our knowledge, this is the first study to show that the dose and intensity of longitudinal use of GC were both associated with risk of AE among a nationwide Asian SLE cohort.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".