Cardiorenal effects of dual blockade with Angiotensin-converting enzyme inhibitors and Angiotensin receptor blockers in people with CKD: analysis of routinely collected data with emulation of a reference trial (ONTARGET)
Bibliographic record
Abstract
Abstract We aimed to explore whether the ONTARGET trial results, which led to an end of recommendations of dual angiotensin-converting enzyme inhibitor (ACEi) and angiotensin receptor blocker (ARB) use, extended to patients with chronic kidney disease (CKD) who were underrepresented in the trial. We selected people prescribed an ACEi and/or an ARB in the UK Clinical Practice Research Datalink Aurum during 1/1/2001-31/7/2019. We specified an operational definition of dual users and applied ONTARGET eligibility criteria. We used propensity-score—weighted Cox-proportional hazards models to compare dual therapy to ACEi for the primary composite trial outcome (cardiovascular death, myocardial infarction, stroke, or hospitalisation for heart failure), as well as a primary composite renal outcome (≥50% reduction in GFR or end-stage kidney disease), and other secondary outcomes, including hyperkalaemia. Conditional on successfully benchmarking results against the ONTARGET trial, we explored treatment effect heterogeneity by CKD at baseline. In the propensity-score—weighted trial-eligible analysis cohort (n=412 406), for dual therapy vs ACEi we observed hazard ratio (HR) 0.98 (95% CI: 0.93, 1.03), for the primary composite outcome, consistent with the trial results (ONTARGET HR 0.99, 95% CI: 0.92, 1.07). Dual therapy use was associated with an increased risk of the primary renal composite outcome, HR 1.25 (95% CI: 1.15, 1.36) vs ONTARGET HR 1.24 (1.01, 1.51) and hyperkalaemia, HR 1.15 (95% CI: 1.09, 1.22) in the trial eligible cohort, consistent with ONTARGET. The presence of CKD at baseline had minimal impact on results. Translational statement We extended ONTARGET trial findings of the comparative effectiveness of dual ARB and ACEi therapy use compared to ACEi alone for a composite cardiovascular outcome to UK patients at high-risk of cardiovascular disease, including those with CKD. As in ONTARGET, we found an increased risk of a composite renal outcome (≥50% reduction in GFR or end-stage kidney disease) and an increased risk of hyperkalaemia among dual users compared to ACEi alone. Consistent results were observed among patients with CKD at baseline. This is evidence against the hypothesis that dual blockade provides cardiorenal benefits among high-risk cardiovascular patients with CKD.
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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 | 0.079 | 0.123 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".