The Long-Term Impact of Renin-Angiotensin System (RAS) Inhibition on Cardiorenal Outcomes (LIRICO): A Randomized, Controlled Trial
Bibliographic record
Abstract
BACKGROUND: The comparative effectiveness of treatment with angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), or their combination in people with albuminuria and cardiovascular risk factors is unclear. METHODS: In a multicenter, randomized, open label, blinded end point trial, we evaluated the effectiveness on cardiovascular events of ACE or ARB monotherapy or combination therapy, targeting BP<130/80 in patients with moderate or severe albuminuria and diabetes or other cardiovascular risk factors. End points included a primary composite of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, and hospitalization for cardiovascular causes and a revised end point of all-cause mortality. Additional end points included ESRD, doubling of serum creatinine, albuminuria, eGFR, BP, and adverse events. RESULTS: Because of slow enrollment, the trial was modified and stopped 41% short of targeted enrollment of 2100 participants, corresponding to 35% power to detect a 25% reduced risk in the primary outcome. Our analysis included 1243 adults, with median follow-up of 2.7 years. Efficacy outcomes were similar between groups (ACE inhibitor versus ARB, ACE inhibitor versus combination, ARB versus combination) as were rates of serious adverse events. The rate of permanent discontinuation for ARB monotherapy (6.3%) was significantly lower than for ACE inhibitor monotherapy (15.7%) or combined therapy (18.3%). CONCLUSIONS: Patients may tolerate ARB monotherapy better than ACE inhibitor monotherapy. However, data from this trial and similar trials, although as yet inconclusive, show no trend suggesting differences in mortality and renal outcomes with ACE inhibitors or ARBs as dual or monotherapy in patients with albuminuria and diabetes or other cardiovascular risk factors.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".