Prevalence of Renal Impairment in a US Commercially Insured Rheumatoid Arthritis Population: A Retrospective Analysis
Bibliographic record
Abstract
INTRODUCTION: Global prevalence estimates for chronic kidney disease (CKD) in rheumatoid arthritis (RA) vary. This study assessed real-world prevalence estimates of renal impairment, based on estimated glomerular filtration rate (eGFR), among commercially insured patients with RA in the United States (US). METHODS: ) between January 2013 and December 2018. Adult patients with ≥ 2 claims for RA and ≥ 2 serum creatinine (SCr) measurements ≥ 90 days apart on or after the index date were included. eGFR was calculated per the Modification of Diet in Renal Disease equation. Prevalence of eGFR-based renal impairment was estimated for the overall RA population and for two subgroups: patients on advanced therapies (biologic disease-modifying antirheumatic drugs/tofacitinib) and patients stratified based on health plan types. RESULTS: Among 128,062 patients with ≥ 2 RA claims, 42,173 had qualifying SCr measurements, 16,197 were on advanced RA therapies, and 4911 had Medicare Advantage or Supplemental plus Part D coverage. For the overall population and the subgroup on advanced therapies, mild renal impairment was observed in 52% and 51%, moderate renal impairment in 9% and 7%, and severe renal impairment in 0.5% and 0.3% of patients, respectively. Moderate and severe renal impairment was more prevalent in the Medicare Advantage/Supplemental plus Part D population compared to the commercial coverage population. CONCLUSIONS: Approximately 7-10% of commercially insured adult patients in the US with RA had moderate or severe renal impairment. Assessment of renal function is an important consideration for safe treatment.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 teacher head, 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".