Effects of Repository Corticotropin Injection on Medication Use in Patients With Rheumatologic Conditions: A Claims Data Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Currently, specific studies identifying how repository corticotropin injection (RCI) is used in rheumatologic conditions are lacking. This is a first step to familiarize the trends of demographics using RCI as well as other medication use. Objective: RCI may produce anti-inflammatory as well as immune-modulatory effects. The purpose of this study is to examine the demographics of those who use RCI and the change in medication use, specifically prednisone, after RCI initiation. Method: This study used the Symphony Health Solutions (SHA) Claims database from 2008 to 2015. International Classification of Disease, Ninth Revision, codes were used to identify rheumatologic conditions including rheumatoid arthritis, systemic lupus erythematosus, dermatomyositis, and polymyositis. Information including RCI dose and concomitant medication uses was also obtained. Results: A total of 2749 patients with rheumatologic conditions receiving RCI were investigated for demographic information, and a total of 1048 patients with rheumatologic conditions on RCI were examined for medication use. The use of nonsteroidal anti-inflammatory drugs, disease-modifying anti-rheumatic drugs, and biologics overall decreased significantly in all 3 rheumatologic conditions except biologics in dermatomyositis/polymyositis. In addition, mean prednisone dose before and after RCI use significantly decreased one quarter (12 weeks) after RCI initiation. Conclusion: Claims-based study on RCI use indicates that RCI use might reduce use of prednisone, disease-modifying anti-rheumatic drugs, and other biologics. Further prospective study is needed.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it