The dapagliflozin and prevention of adverse outcomes in chronic kidney disease (DAPA-CKD) trial: baseline characteristics
Bibliographic record
Abstract
BACKGROUND: The Dapagliflozin and Prevention of Adverse outcomes in Chronic Kidney Disease (DAPA-CKD; NCT03036150) trial was designed to assess the effect of the sodium-glucose co-transporter 2 (SGLT2) inhibitor dapagliflozin on kidney and cardiovascular events in participants with CKD with and without type 2 diabetes (T2D). This analysis reports the baseline characteristics of those recruited, comparing them with those enrolled in other trials. METHODS: In DAPA-CKD, 4304 participants with a urinary albumin:creatinine ratio (UACR) ≥200 mg/g and estimated glomerular filtration rate (eGFR) between 25 and 75 mL/min/1.73 m2 were randomized to dapagliflozin 10 mg once daily or placebo. Mean eGFR was 43.1 mL/min/1.73 m2 and median UACR was 949 mg/g (108 mg/mmol). RESULTS: Overall, 2906 participants (68%) had a diagnosis of T2D and of these, 396 had CKD ascribed to a cause other than diabetes. The most common causes of CKD after diabetes (n = 2510) were ischaemic/hypertensive nephropathy (n = 687) and chronic glomerulonephritis (n = 695), of which immunoglobulin A nephropathy (n = 270) was the most common. A total of 4174 participants (97%) were receiving an angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, 1882 (43.7%) diuretics, 229 (5.3%) mineralocorticoid receptor antagonists and 122 (2.8%) glucagon-like peptide 1 receptor agonists. In contrast to the Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE), the DAPA-CKD trial enrolled participants with CKD due to diabetes and to causes other than diabetes. The mean eGFR of participants in the DAPA-CKD trial was 13.1 mL/min/1.73 m2 lower than in CREDENCE, similar to that in the Finerenone in Reducing Kidney Failure and Disease Progression in DKD (FIDELIO-DKD) trial and the Study Of diabetic Nephropathy with AtRasentan (SONAR). CONCLUSIONS: Participants with a wide range of underlying kidney diseases receiving renin-angiotensin system blocking therapy have been enrolled in the DAPA-CKD trial. The trial will examine the efficacy and safety of dapagliflozin in participants with CKD Stages 2-4 and increased albuminuria, with and without T2D.
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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 | 0.001 |
| 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) | 0.004 | 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".