Increased Frequency and Costs of Ambulatory Medical Care Utilization Prior to the Diagnosis of Rheumatoid Arthritis: A National Population‐Based Study
Bibliographic record
Abstract
OBJECTIVE: To investigate the frequency and costs associated with ambulatory medical care utilization over an 8-year period in patients prior to the diagnosis of rheumatoid arthritis (RA). METHODS: We used Taiwan's National Health Insurance Research Database to identify 691 newly diagnosed RA cases between 2005 and 2010. We selected 1,382 controls without RA, frequency matched by sex, age, and the catastrophic illness certificate application year of the cases. The frequency and costs of ambulatory medical care utilization between the RA patients and controls were compared using the 2-sample Kolmogorov-Smirnov test. RESULTS: The median frequency of ambulatory medical care utilization was significantly higher in RA patients compared with controls (29 versus 13; P < 0.001) in the year before diagnosis. The differences remained significant throughout all 8 annual periods before diagnosis. Similarly, the inflation-adjusted costs of ambulatory medical care utilization in RA patients increased annually over the study period, from a median of $212 eight years preceding diagnosis to $798 one year preceding diagnosis. Frequency of ambulatory medical care utilization due to diseases of the musculoskeletal system and connective tissue (P < 0.001), acute respiratory infections (P < 0.001), diseases of the upper respiratory tract (P = 0.01), and diseases of the upper gastrointestinal tract (P = 0.04) were higher among RA patients in the 2-year period preceding diagnosis. CONCLUSION: We found increased frequency and costs of ambulatory care utilization among RA patients in Taiwan preceding diagnosis of RA.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".