Comparative effectiveness of angiotensin-converting-enzyme inhibitors and angiotensin II receptor blockers in patients with type 2 diabetes and retinopathy
Bibliographic record
Abstract
BACKGROUND: Angiotensin-converting-enzyme (ACE) inhibitors and angiotensin II receptor blockers (ARBs) are effective treatments for diabetic retinopathy, but randomized trials and meta-analyses comparing their effects on macrovascular complications have yielded conflicting results. We compared the effectiveness of these drugs in patients with pre-existing diabetic retinopathy in a large population-based cohort. METHODS: We conducted a propensity score-matched cohort study using Taiwan's National Health Insurance Research Database. We included adult patients prescribed an ACE inhibitor or ARB within 90 days after diagnosis of diabetic retinopathy between 2000 and 2010. Primary outcomes were all-cause death and major adverse cardiovascular events (myocardial infarction, ischemic stroke or cardiovascular death). Secondary outcomes were hospital admissions with acute kidney injury or hyperkalemia. RESULTS: We identified 11 246 patients receiving ACE inhibitors and 15 173 receiving ARBs, of whom 9769 patients in each group were matched successfully by propensity scores. In the intention-to-treat analyses, ARBs were similar to ACE inhibitors in risk of all-cause death (hazard ratio [HR] 0.94, 95% confidence interval [CI] 0.87-1.01) and major adverse cardiovascular events (HR 0.95, 95% CI 0.87-1.04), including myocardial infarction (HR 1.03, 95% CI 0.88-1.20), ischemic stroke (HR 0.94, 95% CI 0.85-1.04) and cardiovascular death (HR 1.01, 95% CI 0.88-1.16). They also did not differ from ACE inhibitors in risk of hospital admission with acute kidney injury (HR 1.01, 95% CI 0.91-1.13) and hospital admission with hyperkalemia (HR 1.01, 95% CI 0.86-1.18). Results were similar in as-treated analyses. INTERPRETATION: Our study showed that ACE inhibitors were similar to ARBs in risk of all-cause death, major adverse cardiovascular events and adverse effects among patients with pre-existing diabetic retinopathy.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".