A Randomized Clinical Trial Testing Hydroxychloroquine for Reduction of SARS-CoV-2 Viral Shedding and Hospitalization in Early Outpatient COVID-19 Infection.

Early in the COVID-19 pandemic, no effective treatment existed to prevent clinical worsening of COVID-19 among recently diagnosed outpatients. At the University of Utah, Salt Lake City, Utah, we conducted a phase 2 prospective parallel group randomized placebo-controlled trial (NCT04342169) to determine whether hydroxychloroquine given early in disease reduces the duration of SARS-CoV-2 shedding. We enrolled nonhospitalized adults (≥18 years of age) with a recent positive diagnostic test for SARS-CoV-2 (within 72 h of enrollment) and adult household contacts. Participants received either 400 mg hydroxychloroquine by mouth twice daily on day 1 followed by 200 mg by mouth twice daily on days 2 to 5 or oral placebo with the same schedule. We performed SARS-CoV-2 nucleic acid amplification testing (NAAT) on oropharyngeal swabs on days 1 to 14 and 28 and monitored clinical symptomatology, rates of hospitalization, and viral acquisition by adult household contacts. We identified no overall differences in the duration of oropharyngeal carriage of SARS-CoV-2 (hazard ratio of viral shedding time comparing hydroxychloroquine to placebo, 1.21; 95% confidence interval [CI], 0.91, 1.62). Overall, 28-day hospitalization incidence was similar between treatments (4.6% hydroxychloroquine versus 2.7% placebo). No differences were seen in symptom duration, severity, or viral acquisition in household contacts between treatment groups. The study did not reach the prespecified enrollment target, which was likely influenced by a steep decline in COVID-19 incidence corresponding to the initial vaccine rollout in the spring of 2021. Oropharyngeal swabs were self-collected, which may introduce variability in these results. Placebo treatments were not identical to hydroxychloroquine treatments (capsules versus tablets) which may have led to inadvertent participant unblinding. In this group of community adults early in the COVID-19 pandemic, hydroxychloroquine did not significantly alter the natural history of early COVID-19 disease. (This study has been registered at ClinicalTrials.gov under registration no. NCT04342169). IMPORTANCE Early in the COVID-19 pandemic, no effective treatment existed to prevent clinical worsening of COVID-19 among recently diagnosed outpatients. Hydroxychloroquine received attention as a possible early treatment; however, quality prospective studies were lacking. We conducted a clinical trial to test the ability of hydroxychloroquine to prevent clinical worsening of COVID-19.

Rapid-cycle designs to adapt interventions for COVID-19 in safety-net healthcare systems.

Racial/ethnic minority, low socioeconomic status, and rural populations are disproportionately affected by COVID-19. Developing and evaluating interventions to address COVID-19 testing and vaccination among these populations are crucial to improving health inequities. The purpose of this paper is to describe the application of a rapid-cycle design and adaptation process from an ongoing trial to address COVID-19 among safety-net healthcare system patients. The rapid-cycle design and adaptation process included: (a) assessing context and determining relevant models/frameworks; (b) determining core and modifiable components of interventions; and (c) conducting iterative adaptations using Plan-Do-Study-Act (PDSA) cycles. PDSA cycles included: Plan. Gather information from potential adopters/implementers (e.g., Community Health Center [CHC] staff/patients) and design initial interventions; Do. Implement interventions in single CHC or patient cohort; Study. Examine process, outcome, and context data (e.g., infection rates); and, Act. If necessary, refine interventions based on process and outcome data, then disseminate interventions to other CHCs and patient cohorts. Seven CHC systems with 26 clinics participated in the trial. Rapid-cycle, PDSA-based adaptations were made to adapt to evolving COVID-19-related needs. Near real-time data used for adaptation included data on infection hot spots, CHC capacity, stakeholder priorities, local/national policies, and testing/vaccine availability. Adaptations included those to study design, intervention content, and intervention cohorts. Decision-making included multiple stakeholders (e.g., State Department of Health, Primary Care Association, CHCs, patients, researchers). Rapid-cycle designs may improve the relevance and timeliness of interventions for CHCs and other settings that provide care to populations experiencing health inequities, and for rapidly evolving healthcare challenges such as COVID-19.

Racial/ethnic minority, low socioeconomic status, and rural populations experience a disproportionate burden of COVID-19. Finding ways to address COVID-19 among these populations is crucial to improving health inequities. The purpose of this paper is to describe the rapid-cycle design process for a research project to address COVID-19 testing and vaccination among safety-net healthcare system patients. The project used real-time information on changes in COVID-19 policy (e.g., vaccination authorization), local case rates, and the capacity of safety-net healthcare systems to iteratively change interventions to ensure interventions were relevant and timely for patients. Key changes that were made to interventions included a change to the study design to include vaccination as a focus of the interventions after the vaccine was authorized; change in intervention content according to the capacity of local Community Health Centers to provide testing to patients; and changes to intervention cohorts such that priority groups of patients were selected for intervention based on characteristics including age, residency in an infection "hot spot," or race/ethnicity. Iteratively improving interventions based on real-time data collection may increase intervention relevance and timeliness, and rapid-cycle adaptions can be successfully implemented in resource constrained settings like safety-net healthcare systems.

Hydroxychloroquine for treatment of non-hospitalized adults with COVID-19: A meta-analysis of individual participant data of randomized trials.

Hydroxychloroquine (HCQ) was initially promoted as an oral therapy for early treatment of coronavirus disease 2019 (COVID-19). Conventional meta-analyses cannot fully address the heterogeneity of different designs and outcomes of randomized controlled trials (RCTs) assessing the efficacy of HCQ in outpatients with mild COVID-19. We conducted a pooled analysis of individual participant data from RCTs that evaluated the effect of HCQ on hospitalization and viral load reduction in outpatients with confirmed COVID-19. We evaluated the overall treatment group effect by log-likelihood ratio test (-2LL) from a generalized linear mixed model to accommodate correlated longitudinal binary data. The analysis included data from 11 RCTs. The outcome of virological effect, assessed in 1560 participants (N = 795 HCQ, N = 765 control), did not differ significantly between the two treatment groups (-2LL = 7.66; p = 0.18) when adjusting for cohort, duration of symptoms, and comorbidities. The decline in polymerase chain reaction positive tests from day 1 to 7 was 42.0 and 41.6 percentage points in the HCQ and control groups, respectively. Among the 2037 participants evaluable for hospitalization (N = 1058 HCQ, N = 979 control), we found no significant differences in hospitalization rate between participants receiving HCQ and controls (odds ratio 0.995; 95% confidence interval 0.614-1.610; -2LL = 0.0; p = 0.98) when adjusting for cohort, duration of symptoms, and comorbidities. This individual participant data meta-analysis of 11 HCQ trials that evaluated severe acute respiratory syndrome-coronavirus 2 viral clearance and COVID-19 hospitalization did not show a clinical benefit of HCQ. Our meta-analysis provides evidence to support the interruption in the use of HCQ in mild COVID-19 outpatients to reduce progression to severe disease.

Proportion of Patients on Warfarin Therapy Who Are Eligible for Conversion to a Direct Oral Anticoagulant in the Setting of COVID-19.

BACKGROUND: Warfarin, a commonly prescribed anticoagulant, requires frequent lab monitoring. Lab monitoring puts patients at risk of COVID-19 exposure and diverts medical resources away from health care systems. Direct oral anticoagulants (DOACs) do not require routine therapeutic monitoring and are indicated first line for nonvalvular atrial fibrillation (NVAF) stroke prevention and venous thromboembolism (VTE) prevention/treatment. OBJECTIVE: The purpose of the study was to determine the proportion of patients who qualify for DOACs and assess for predictors of qualification. METHODS: This cross-sectional study investigated patients on warfarin managed by Michigan Medicine Anticoagulation Service. Direct oral anticoagulant eligibility criteria were established using apixaban, dabigatran, and rivaroxaban package inserts. Patient eligibility was determined through chart review. The primary outcome was the proportion of patients who qualify for DOACs based on clinical factors. Predictors of DOAC qualification were assessed. RESULTS: This study included 3205 patients and found 51.8% (n = 1661) of patients qualified for DOACs. Qualifying patients were older (71.9 vs 59.4 years, P < 0.0001) with a higher CHA2DS2 VASc (3.7 vs 3.4, P < 0.0007). The primary disqualifying factor was extreme weight, high and low. Accounting for a patient's sex and referral source, age > 65 (odds ratio [OR] = 1.9, P < 0.0001) and NVAF indication (OR = 5.6, P < 0.0001) were significant predictors for DOAC qualification. CONCLUSION AND RELEVANCE: Approximately 52% of patients on warfarin were eligible for DOACs. This presents an opportunity to reduce patient exposure to health care settings and health care utilization in the setting of COVID-19. Increased costs of DOACs need to be assessed.

Inaccuracies in electronic health records smoking data and a potential approach to address resulting underestimation in determining lung cancer screening eligibility.

OBJECTIVE: The US Preventive Services Task Force (USPSTF) requires the estimation of lifetime pack-years to determine lung cancer screening eligibility. Leading electronic health record (EHR) vendors calculate pack-years using only the most recently recorded smoking data. The objective was to characterize EHR smoking data issues and to propose an approach to addressing these issues using longitudinal smoking data. MATERIALS AND METHODS: In this cross-sectional study, we evaluated 16 874 current or former smokers who met USPSTF age criteria for screening (50-80 years old), had no prior lung cancer diagnosis, and were seen in 2020 at an academic health system using the Epic® EHR. We described and quantified issues in the smoking data. We then estimated how many additional potentially eligible patients could be identified using longitudinal data. The approach was verified through manual review of records from 100 subjects. RESULTS: Over 80% of evaluated records had inaccuracies, including missing packs-per-day or years-smoked (42.7%), outdated data (25.1%), missing years-quit (17.4%), and a recent change in packs-per-day resulting in inaccurate lifetime pack-years estimation (16.9%). Addressing these issues by using longitudinal data enabled the identification of 49.4% more patients potentially eligible for lung cancer screening (P < .001). DISCUSSION: Missing, outdated, and inaccurate smoking data in the EHR are important barriers to effective lung cancer screening. Data collection and analysis strategies that reflect changes in smoking habits over time could improve the identification of patients eligible for screening. CONCLUSION: The use of longitudinal EHR smoking data could improve lung cancer screening.

Managing the risks and benefits of clinical research in response to a pandemic.

Introduction: The coronavirus disease 2019 (COVID-19) created major disruptions at academic centers and healthcare systems globally. Clinical and Translational Science Awards (CTSA) fund hubs supported by the National Center for Advancing Translational Sciences provideinfrastructure and leadership for clinical and translational research at manysuch institutions. Methods: We surveyed CTSA hubs and received responses from 94% of them regarding the impact of the pandemic and the processes employed for the protection of research personnel and participants with respect to the conduct of research, specifically for studies unrelated to COVID-19. Results: In this report, we describe the results of the survey findings in the context of the current understanding of disease transmission and mitigation techniques. Conclusions: We reflect on common practices and provide recommendations regarding lessons learned that will be relevant to future pandemics, particularly with regards to staging the cessation and resumption of research activities with an aim to keep the workforce, research participants, and our communities safe in future pandemics.

Angiotensin II receptor blocker or angiotensin-converting enzyme inhibitor use and COVID-19-related outcomes among US Veterans.

BACKGROUND: Angiotensin II receptor blockers (ARBs) and angiotensin-converting enzyme inhibitors (ACEIs) may positively or negatively impact outcomes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We investigated the association of ARB or ACEI use with coronavirus disease 2019 (COVID-19)-related outcomes in US Veterans with treated hypertension using an active comparator design, appropriate covariate adjustment, and negative control analyses. METHODS AND FINDINGS: In this retrospective cohort study of Veterans with treated hypertension in the Veterans Health Administration (01/19/2020-08/28/2020), we compared users of (A) ARB/ACEI vs. non-ARB/ACEI (excluding Veterans with compelling indications to reduce confounding by indication) and (B) ARB vs. ACEI among (1) SARS-CoV-2+ outpatients and (2) COVID-19 hospitalized inpatients. The primary outcome was all-cause hospitalization or mortality (outpatients) and all-cause mortality (inpatients). We estimated hazard ratios (HR) using propensity score-weighted Cox regression. Baseline characteristics were well-balanced between exposure groups after weighting. Among outpatients, there were 5.0 and 6.0 primary outcomes per 100 person-months for ARB/ACEI (n = 2,482) vs. non-ARB/ACEI (n = 2,487) users (HR 0.85, 95% confidence interval [CI] 0.73-0.99, median follow-up 87 days). Among outpatients who were ARB (n = 4,877) vs. ACEI (n = 8,704) users, there were 13.2 and 14.8 primary outcomes per 100 person-months (HR 0.91, 95%CI 0.86-0.97, median follow-up 85 days). Among inpatients who were ARB/ACEI (n = 210) vs. non-ARB/ACEI (n = 275) users, there were 3.4 and 2.0 all-cause deaths per 100 person months (HR 1.25, 95%CI 0.30-5.13, median follow-up 30 days). Among inpatients, ARB (n = 1,164) and ACEI (n = 2,014) users had 21.0 vs. 17.7 all-cause deaths, per 100 person-months (HR 1.13, 95%CI 0.93-1.38, median follow-up 30 days). CONCLUSIONS: This observational analysis supports continued ARB or ACEI use for patients already using these medications before SARS-CoV-2 infection. The novel beneficial association observed among outpatients between users of ARBs vs. ACEIs on hospitalization or mortality should be confirmed with randomized trials.