Bibliographic record
Abstract
Background Decline in estimated glomerular filtration rate (eGFR) is an important surrogate marker for the assessment of renal function. Addition of a second agent to angiotensin-converting-enzyme inhibitor (ACEI) or angiotensin II receptor blocker (ARB) treatment may improve current therapeutic strategies aimed at suppressing renal disease progression. Objective To determine the effect of cilostazol in combination with ACEI or ARB treatment on the decline in eGFR. Setting A tertiary hospital in Korea. Method In an observational cohort study, we analyzed 5505 patients who were prescribed ACEI or ARB and cilostazol or other antiplatelet agents. Main outcome measure The primary outcome assessed was worsening of renal function defined as a 30% decline in eGFR per year. The secondary outcomes included commencement of dialysis, renal transplantation, death, myocardial infarction, and ischemic stroke. Results Following propensity score matching, eGFR decreased over time in the majority of patients, but the decline was less in patients in the cilostazol treated (CT) group of stage 1-2 category compared to the cilostazol untreated (CU) group (OR 0.80; 95% CI 0.66-0.98). In the subgroup analysis, the strongest effect in slowing eGFR decline was observed in CT patients at a high risk of diabetes (OR 0.782; 95% CI 0.615-0.993) and the elderly (OR 0.693; 95% CI 0.504-0.953) in the stage 1-2 category. No significant increase in cardiovascular risk was observed between the CT and CU groups. Conclusion Treatment with cilostazol plus ACEI or ARB was observed to prevent worsening of renal progression in patients in the stages 1-2.
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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) | 0.000 | 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 | 0.001 |
| 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 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".