Impact of Chronic Kidney Disease on Use of Evidence-Based Therapy in Stable Coronary Artery Disease: A Prospective Analysis of 22,272 Patients
Bibliographic record
Abstract
PURPOSE: To assess the frequency of chronic kidney disease (CKD), define the associated demographics, and evaluate its association with use of evidence-based drug therapy in a contemporary global study of patients with stable coronary artery disease. METHODS: 22,272 patients from the ProspeCtive observational LongitudinAl RegIstry oF patients with stable coronary arterY disease (CLARIFY) were included. Baseline estimated glomerular filtration rate (eGFR) was calculated (CKD-Epidemiology Collaboration formula) and patients categorised according to CKD stage: >89, 60-89, 45-59 and <45 mL/min/1.73 m2. RESULTS: Mean (SD) age was 63.9±10.4 years, 77.3% were male, 61.8% had a history of myocardial infarction, 71.9% hypertension, 30.4% diabetes and 75.4% dyslipidaemia. Chronic kidney disease (eGFR<60 mL/min/1.73 m2) was seen in 22.1% of the cohort (6.9% with eGFR<45 mL/min/1.73 m2); lower eGFR was associated with increasing age, female sex, cardiovascular risk factors, overt vascular disease, other comorbidities and higher systolic but lower diastolic blood pressure. High use of secondary prevention was seen across all CKD stages (overall 93.4% lipid-lowering drugs, 95.3% antiplatelets, 75.9% beta-blockers). The proportion of patients taking statins was lower in patients with CKD. Antiplatelet use was significantly lower in patients with CKD whereas oral anticoagulant use was higher. Angiotensin-converting enzyme inhibitor use was lower (52.0% overall) and inversely related to declining eGFR, whereas angiotensin-receptor blockers were more frequently prescribed in patients with reduced eGFR. CONCLUSIONS: Chronic kidney disease is common in patients with stable coronary artery disease and is associated with comorbidities. Whilst use of individual evidence-based medications for secondary prevention was high across all CKD categories, there remains an opportunity to improve the proportion who take all three classes of preventive therapies. Angiotensin-converting enzyme inhibitors were used less frequently in lower eGRF categories. Surprisingly the reverse was seen for angiotensin-receptor blockers. Further evaluation is required to fully understand these associations. The CLARIFY (ProspeCtive observational LongitudinAl RegIstry oF patients with stable coronary arterY disease) Registry is registered in the ISRCTN registry of clinical trials with the number ISRCTN43070564. http://www.controlled-trials.com/ISRCTN43070564.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".