Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

An Iterative Technique for Improved Two-level Logic Minimization

In this paper, we describe an iterative heuristic technique to improve the quality of results obtained during two-level logic minimization using ESPRESSO. Although ESPRESSO minimizes the number of cubes in the solution e#ectively, there are several problem instances where its results are worse than the Quine-McCluskey based exact minimization technique. Our technique is designed to improve the results of ESPRESSO while utilizing ESPRESSO's Unate Recursive Paradigm based optimization heuristics, on account of their simplicity and power. Our technique is based on performing a series of iterations of ESPRESSO, in each of which we extract a number of cubes and append them into a HYPER-COVER. For the given (and subsequent) iterations of ESPRESSO, these cubes are considered as don't care cubes. By e#ectively selecting the number of iterations performed by our heuristic, we can trade o# the improvement in solution quality against the run-time of our algorithm. We have implemented several variants of our iterative algorithm, and have compared their e#ectiveness. We show that with a small number of iterations, our technique is able to improve on the number of cubes in the solution, with an acceptable run-time overhead. The best variant is able to improve the ESPRESSO cube count by up to 18%, with an acceptable increase in run-time. In 58 examples where the ESPRESSO results can be potentially improved, one of the variants of our algorithm demonstrated better results than ESPRESSO for 27 cases