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

Sample-Efficient Spatio-Spectral Whitespace Detection Using Least Matching Pursuit

Multi-antenna wireless communication improves spectral efficiency by reusing frequencies at different locations in space using beamforming and spatial multiplexing. In the past, research has extensively focused on dynamically reusing unused frequency bands to optimize spectrum usage, but methods that identify unused resources in space appear to be unexplored. In this paper, we propose a sample-efficient whitespace detection pipeline for multi-antenna radio-frequency (RF) transceivers that detects unused resources in both frequency and space. Our spatio-spectral whitespace detection pipeline relies on multi-antenna nonuniform wavelet sampling, which identifies unused frequencies in space at sub-Nyquist sampling rates. We demonstrate the efficacy of our approach via system simulations and show that reliable spatio-spectral whitespace detection is possible with 16× lower sampling rates than methods relying on Nyquist sampling.ISSN:2169-353

Identifying Unused RF Channels Using Least Matching Pursuit

Cognitive radio aims at identifying unused radio-frequency (RF) bands with the goal of re-using them opportunistically for other services. While compressive sensing (CS) has been used to identify strong signals (or interferers) in the RF spectrum from sub-Nyquist measurements, identifying unused frequencies from CS measurements appears to be uncharted territory. In this paper, we propose a novel method for identifying unused RF bands using an algorithm we call least matching pursuit (LMP). We present a sufficient condition for which LMP is guaranteed to identify unused frequency bands and develop an improved algorithm that is inspired by our theoretical result. We perform simulations for a CS-based RF whitespace detection task in order to demonstrate that LMP is able to outperform black-box approaches that build on deep neural networks

Resiliency in the Age of COVID-19: A Policy Toolkit

Twenty-nine LBJ School authors have come together to craft interdisciplinary and resilience-based policy solutions in one toolkit called Resiliency in the Age of COVID-19. In 18 articles that span public management, climate change, economic development, national security and more, LBJ School policy authors provide a forward-thinking lens on what went wrong and what leadership, public policies and initiatives it will take to fix the system flaws exposed by the pandemic. Published during the LBJ School’s 50th anniversary year, the toolkit also provides a snapshot of the school’s depth and breadth of policy and research engagement at this moment in time.Public Affair

Effect of Antiplatelet Therapy on Survival and Organ Support–Free Days in Critically Ill Patients With COVID-19

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