Febuxostat for Cerebral and CaRdiorenovascular Events PrEvEntion StuDy
Bibliographic record
Abstract
AIMS: To compare the occurrence of cerebral, cardiovascular, and renal events in patients with hyperuricaemia treated with febuxostat and those treated with conventional therapy with lifestyle modification. METHODS AND RESULTS: This multicentre, prospective, randomized open-label, blinded endpoint study was done in 141 hospitals in Japan. A total of 1070 patients were included in the intention-to-treat population. Elderly patients with hyperuricaemia (serum uric acid >7.0 to ≤9.0 mg/dL) at risk for cerebral, cardiovascular, or renal disease, defined by the presence of hypertension, Type 2 diabetes, renal disease, or history of cerebral or cardiovascular disease, were randomized to febuxostat and non-febuxostat groups and were observed for 36 months. Cerebral, cardiovascular, and renal events and all deaths were defined as the primary composite event. The serum uric acid level at endpoint (withdrawal or completion of the study) in the febuxostat (n = 537) and non-febuxostat groups (n = 533) was 4.50 ± 1.52 and 6.76 ± 1.45 mg/dL, respectively (P < 0.001). The primary composite event rate was significantly lower in the febuxostat group than in non-febuxostat treatment [hazard ratio (HR) 0.750, 95% confidence interval (CI) 0.592-0.950; P = 0.017] and the most frequent event was renal impairment (febuxostat group: 16.2%, non-febuxostat group: 20.5%; HR 0.745, 95% CI 0.562-0.987; P = 0.041). CONCLUSION: Febuxostat lowers uric acid and delays the progression of renal dysfunction. REGISTRATION: ClinicalTrials.gov (NCT01984749).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".