Higher versus lower doses of ACE inhibitors, angiotensin-2 receptor blockers and beta-blockers in heart failure with reduced ejection fraction: Systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Current heart failure (HF) guidelines recommend titrating angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs) and beta-blockers (BBs) to target doses used in pivotal placebo-controlled randomized controlled trials (RCTs). Despite a number of RCTs comparing different doses (i.e. higher versus lower doses) of ACEIs, ARBs and BBs, the effects of higher versus lower doses on efficacy and safety remains unclear. For this reason, we performed a systematic review and meta-analysis to evaluate the efficacy and safety of higher versus lower doses of ACEIs, ARBs and BBs in patients with HFrEF. METHODS: We searched MEDLINE, Embase and the Cochrane Central Register of Controlled Trials (CENTRAL) via Ovid from inception to April 25th, 2018 and opentrials.net and clinicaltrials.gov for relevant trials that compared different doses of medications in heart failure. We analyzed trials by drug class (ACEIs, ARBs, and BBs) for efficacy outcomes (all-cause mortality, cardiovascular mortality, all-cause hospitalizations, HF hospitalizations, HF worsening). For safety outcomes, we pooled trials within and across drug classes. RESULTS: Our meta-analysis consisted of 14 RCTs. Using GRADE criteria, the quality of evidence for ACEIs and ARBs was assessed as generally moderate for efficacy and high for adverse effects, whereas overall quality for BBs was very low to low. Over ~2-4 years higher versus lower doses of ACEIs, ARBs or BBs did not significantly reduce all-cause mortality [ACEIs relative risk (RR) 0.94 (95% confidence interval 0.87-1.02)], ARBs RR 0.96 (0.87-1.04), BBs RR 0.25 (0.06-1.01)] or all cause hospitalizations [ACEIs relative risk (RR) 0.94 (95% confidence interval 0.86-1.02)], ARBs RR 0.98 (0.93-1.04), BBs RR 0.93 (0.39-2.24)]. However, all point estimates favoured higher doses. Higher doses of ARBs significantly reduced hospitalization for HF [RR 0.89 (0.80-0.99)- 2.8% ARR], and higher doses of ACEIs and ARBs significantly reduced HF worsening [RR 0.85 (0.79-0.92)- 5.1% ARR and 0.91 (0.84-0.99)- 3.2% ARR, respectively] compared to lower doses. None of the differences between higher versus lower doses of BBs were significant; however, precision was low. Higher doses of these medications compared to lower doses increased the risk of discontinuation due to adverse events, hypotension, dizziness, and for ACEIs and ARBs, increased hyperkalemia and elevations in serum creatinine. Absolute increase in harms for adverse effects ranged from ~ 3 to 14%. CONCLUSIONS: Higher doses of ACEIs and ARBs reduce the risk of HF worsening compared to lower doses, and higher doses of ARBs also reduce the risk of HF hospitalization but the evidence is sparse and imprecise. Higher doses increase the chance of adverse effects compared to lower doses. Evidence for BBs is inconclusive. These results support initially always starting at low doses of ACEIs/ARBs and only titrating the dose up if the patient tolerates dose increases.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.045 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".