Urate lowering therapy to improve renal outcomes in patients with chronic kidney disease: systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Hyperuricemia may contribute to renal injury. We do not know whether use of treatments that lower urate reduce the progression of chronic kidney disease (CKD) and cardiovascular disease. We performed a systematic review and meta-analysis of randomized controlled trials to assess the benefits and risks of treatments that lower urate in patients with stages 3-5 CKD. METHODS: We searched MEDLINE, EMBASE, CENTRAL, Web of Science and trial registers for randomized controlled trials (RCTs) without language restriction. Two authors independently screened articles, assessed risk of bias and extracted data. Data obtained included serum uric acid, serum creatinine or other estimates of glomerular filtration rate, incidence of end-stage renal disease (ESRD), systolic and diastolic blood pressure, proteinuria, cardiovascular disease and adverse events. RESULTS: From the 5497 citations screened, 19 RCTs enrolling 992 participants met our inclusion criteria. Given significant heterogeneity in duration of follow-up and study comparators, only trials greater than 3 months comparing allopurinol and inactive control were meta-analyzed using random effects models. Pooled estimate for eGFR was in favour of allopurinol with a mean difference (MD) of 3.2 ml/min/1.73 m(2), 95% CI 0.16-6.2 ml/min/1.73 m(2), p = 0.039 and this was consistent with results for serum creatinine. Statistically significant reductions in serum uric acid, systolic and diastolic blood pressure were found, favouring allopurinol. There were insufficient data on adverse events, incidence of ESRD and cardiovascular disease for analysis. CONCLUSIONS: Adequately powered RCTs are needed to establish whether treatments that lower urate have beneficial renal and cardiovascular effects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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