Demographic and co-morbidity characteristics of patients tested for SARS-CoV-2 from March 2020 to January 2022 in a national clinical research network: results from PCORnet(R) (preprint)

Background Prior studies have documented differences in the age, racial, and ethnic characteristics among patients with SARS-CoV-2 infection. However, little is known about how these characteristics changed over time during the pandemic and whether racial, ethnic, and age disparities evident early in the pandemic were persistent over time. This study reports on trends in SARS-CoV-2 infections among U.S. adults from March 1, 2020 to January, 31 2022, using data from electronic health records. Methods and Findings We captured repeated cross-sectional information from 43 large healthcare systems in 52 U.S. States and territories, participating in PCORnet(R), the National Patient-Centered Clinical Research Network. Using distributed queries executed at each participating institution, we acquired information for all patients [≥] 20 years of age who were tested for SARS-CoV-2 (both positive and negative results), including care setting, age, sex, race, and ethnicity by month as well as comorbidities (assessed with diagnostic codes). During this time period, 1,325,563 patients had positive (13% inpatient) and 6,705,868 patients had negative (25% inpatient) viral tests for SARS-CoV-2. Disparities in testing positive were present across racial and ethnic groups, especially in the inpatient setting. Compared to White patients, Black or African American and other race patients had relative risks for testing positive of 1.5 or greater in the inpatient setting for 12 of the 23-month study period. Compared to nonHispanic patients, Hispanic patients had relative risks for testing positive in the inpatient setting of 1.5 or greater for 16 of 23. Ethnic and racial differences were present in emergency department and ambulatory settings but were less common across time than in inpatient settings. Trends in infections by age group demonstrated higher test positivity for older patients in the inpatient setting only for most months, except for June and July of 2020, April to August 2021, and January 2022. Comorbidities were common, with much higher rates among those hospitalized; hypertension (38% of patients SARS-CoV-2 positive vs. 29% for those negative) and type 2 diabetes mellitus (22% vs. 13%) were the most common. Conclusion and Relevance Racial and ethnic disparities changed over time among persons infected with SARS-CoV-2. These trends highlight potential underlying mechanisms, such as poor access to care and differential vaccination rates, that may have contributed to greater disparities, especially early in the pandemic. Monitoring data on characteristics of patients testing positive in real time could allow public health officials and policymakers to tailor interventions to ensure that patients and communities most in need are receiving adequate testing, mitigation strategies, and treatment.

Excess burden of respiratory and abdominal conditions following COVID-19 infections during the ancestral and Delta variant periods in the United States: An EHR-based cohort study from the RECOVER Program (preprint)

Importance The frequency and characteristics of post-acute sequelae of SARS-CoV-2 infection (PASC) may vary by SARS-CoV-2 variant. Objective To characterize PASC-related conditions among individuals likely infected by the ancestral strain in 2020 and individuals likely infected by the Delta variant in 2021. Design Retrospective cohort study of electronic medical record data for approximately 27 million patients from March 1, 2020-November 30, 2021. Setting Healthcare facilities in New York and Florida. Participants Patients who were at least 20 years old and had diagnosis codes that included at least one SARS-CoV-2 viral test during the study period. Exposure Laboratory-confirmed COVID-19 infection, classified by the most common variant prevalent in those regions at the time. Main Outcome(s) and Measure(s) Relative risk (estimated by adjusted hazard ratio [aHR]) and absolute risk difference (estimated by adjusted excess burden) of new conditions, defined as new documentation of symptoms or diagnoses, in persons between 31-180 days after a positive COVID-19 test compared to persons with only negative tests during the 31-180 days after the last negative test. Results We analyzed data from 560,752 patients. The median age was 57 years; 60.3% were female, 20.0% non-Hispanic Black, and 19.6% Hispanic. During the study period, 57,616 patients had a positive SARS-CoV-2 test; 503,136 did not. For infections during the ancestral strain period, pulmonary fibrosis, edema (excess fluid), and inflammation had the largest aHR, comparing those with a positive test to those with a negative test, (aHR 2.32 [95% CI 2.09 2.57]), and dyspnea (shortness of breath) carried the largest excess burden (47.6 more cases per 1,000 persons). For infections during the Delta period, pulmonary embolism had the largest aHR comparing those with a positive test to a negative test (aHR 2.18 [95% CI 1.57, 3.01]), and abdominal pain carried the largest excess burden (85.3 more cases per 1,000 persons). Conclusions and Relevance We documented a substantial relative risk of pulmonary embolism and large absolute risk difference of abdomen-related symptoms after SARS-CoV-2 infection during the Delta variant period. As new SARS-CoV-2 variants emerge, researchers and clinicians should monitor patients for changing symptoms and conditions that develop after infection.

Risk Factors and Predictive Modeling for Post-Acute Sequelae of SARS-CoV-2 Infection: Findings from EHR Cohorts of the RECOVER Initiative (preprint)

Background Patients who were SARS-CoV-2 infected could suffer from newly incidental conditions in their post-acute infection period. These conditions, denoted as the post-acute sequelae of SARS-CoV-2 infection (PASC), are highly heterogeneous and involve a diverse set of organ systems. Limited studies have investigated the predictability of these conditions and their associated risk factors. Method In this retrospective cohort study, we investigated two large-scale PCORnet clinical research networks, INSIGHT and OneFlorida+, including 11 million patients in the New York City area and 16.8 million patients from Florida, to develop machine learning prediction models for those who are at risk for newly incident PASC and to identify factors associated with newly incident PASC conditions. Adult patients aged  20 with SARS-CoV-2 infection and without recorded infection between March 1st, 2020, and November 30th, 2021, were used for identifying associated factors with incident PASC after removing background associations. The predictive models were developed on infected adults. Results We find several incident PASC, e.g., malnutrition, COPD, dementia, and acute kidney failure, were associated with severe acute SARS-CoV-2 infection, defined by hospitalization and ICU stay. Older age and extremes of weight were also associated with these incident conditions. These conditions were better predicted (C-index >0.8). Moderately predictable conditions included diabetes and thromboembolic disease (C-index 0.7-0.8). These were associated with a wider variety of baseline conditions. Less predictable conditions included fatigue, anxiety, sleep disorders, and depression (C-index around 0.6). Conclusions This observational study suggests that a set of likely risk factors for different PASC conditions were identifiable from EHRs, predictability of different PASC conditions was heterogeneous, and using machine learning-based predictive models might help in identifying patients who were at risk of developing incident PASC. 

Effect of Ivermectin 600 mcg/kg for 6 days vs Placebo on Time to Sustained Recovery in Outpatients with Mild to Moderate COVID-19: A Randomized Clinical Trial (preprint)

Background: Whether ivermectin, with a maximum targeted dose of 600 mcg/kg, shortens symptom duration or prevents hospitalization among outpatients with mild to moderate coronavirus disease 2019 (COVID-19) remains unknown. Our objective was to evaluate the effectiveness of ivermectin, dosed at 600 mcg/kg, daily for 6 days compared with placebo for the treatment of early mild to moderate COVID-19. Methods: ACTIV-6, an ongoing, decentralized, randomized, double-blind, placebo-controlled, platform trial, was designed to evaluate repurposed therapies in outpatients with mild to moderate COVID-19. A total of 1206 participants age >=30 years with confirmed COVID-19, experiencing >=2 symptoms of acute infection for <=7 days, were enrolled from February 16, 2022, through July 22, 2022, with follow-up data through November 10, 2022, at 93 sites in the US. Participants were randomized to ivermectin, with a maximum targeted dose of 600 mcg/kg (n=602), daily vs. placebo daily (n=604) for 6 days. The primary outcome was time to sustained recovery, defined as at least 3 consecutive days without symptoms. The 7 secondary outcomes included a composite of hospitalization, death, or urgent/emergent care utilization by day 28. Results: Among 1206 randomized participants who received study medication or placebo, median (interquartile range) age was 48 (38-58) years; 713 (59%) were women; and 1008 (84%) reported 2 or more SARS-CoV-2 vaccine doses. Median time to recovery was 11 (11-12) days in the ivermectin group and 11 (11-12) days in the placebo group. The hazard ratio (HR) (95% credible interval [CrI], posterior probability of benefit) for improvement in time to recovery was 1.02 (0.92-1.13; P[HR>1]=0.68). In those receiving ivermectin, 34 (5.7%) were hospitalized, died, or had urgent or emergency care visits compared with 36 (6.0%) receiving placebo (HR 1.0, 0.6-1.5; P[HR<1]=0.53). In the ivermectin group, 1 participant died and 4 were hospitalized (0.8%); 2 participants (0.3%) were hospitalized in the placebo group and there were no deaths. Adverse events were uncommon in both groups. Conclusions: Among outpatients with mild to moderate COVID-19, treatment with ivermectin, with a maximum targeted dose of 600 mcg/kg daily for 6 days, compared with placebo did not improve time to recovery. These findings do not support the use of ivermectin in patients with mild to moderate COVID-19. Trial registration: ClinicalTrials.gov Identifier: NCT04885530 .

Fluvoxamine for Outpatient Treatment of COVID-19: A Decentralized, Placebo-controlled, Randomized, Platform Clinical Trial (preprint)

Background: The effectiveness of fluvoxamine to shorten symptom duration or prevent hospitalization among outpatients in the US with mild to moderate symptomatic coronavirus disease 2019 (COVID-19) is unclear. Design: ACTIV-6 is an ongoing, decentralized, double-blind, randomized, placebo-controlled platform trial testing repurposed medications in outpatients with mild to moderate COVID-19. A total of 1288 non-hospitalized adults aged >=30 years with confirmed COVID-19 experiencing >=2 symptoms of acute infection for <=7 days prior to randomization were randomized to receive fluvoxamine 50 mg or placebo twice daily for 10 days. The primary outcome was time to sustained recovery, defined as the third of 3 consecutive days without symptoms. Secondary outcomes included composites of hospitalization or death with or without urgent or emergency care visit by day 28. Results: Of 1331 participants randomized (mean [SD] age, 48.5 [12.8] years; 57% women; 67% reported receiving at least 2 doses of a SARS-CoV-2 vaccine), 1288 completed the trial (n=614 placebo, n=674 fluvoxamine). Median time to recovery was 13 days (IQR 12-13) in the placebo group and 12 days (IQR 11-14) in the fluvoxamine group (hazard ratio [HR] 0.96, 95% credible interval [CrI] 0.86-1.07; posterior probability for benefit [HR>1]=0.22). Twenty-six participants (3.9%) in the fluvoxamine group were hospitalized or had urgent or emergency care visits compared with 23 (3.8%) in the placebo group (HR 1.1, 95% CrI 0.6-1.8; posterior probability for benefit [HR<1]=0.340). One participant in the fluvoxamine group and 2 in the placebo group were hospitalized; no deaths occurred. Adverse events were uncommon in both groups. Conclusions: Treatment with fluvoxamine 50 mg twice daily for 10 days did not improve time to recovery, compared with placebo, among outpatients with mild to moderate COVID-19. These findings do not support the use of fluvoxamine at this dose and duration in patients with mild to moderate COVID-19.

Identifying Contextual and Spatial Risk Factors for Post-Acute Sequelae of SARS-CoV-2 Infection: An EHR-based Cohort Study from the RECOVER Program (preprint)

Post-acute sequelae of SARS-CoV-2 infection (PASC) affects a wide range of organ systems among a large proportion of patients with SARS-CoV-2 infection. Although studies have identified a broad set of patient-level risk factors for PASC, little is known about the contextual and spatial risk factors for PASC. Using electronic health data of patients with COVID-19 from two large clinical research networks in New York City and Florida, we identified contextual and spatial risk factors from nearly 200 environmental characteristics for 23 PASC symptoms and conditions of eight organ systems. We conducted a two-phase environment-wide association study. In Phase 1, we ran a mixed effects logistic regression with 5-digit ZIP Code tabulation area (ZCTA5) random intercepts for each PASC outcome and each contextual and spatial factor, adjusting for a comprehensive set of patient-level confounders. In Phase 2, we ran a mixed effects logistic regression for each PASC outcome including all significant (false positive discovery adjusted p-value < 0.05) contextual and spatial characteristics identified from Phase I and adjusting for confounders. We identified air toxicants (e.g., methyl methacrylate), criteria air pollutants (e.g., sulfur dioxide), particulate matter (PM2.5) compositions (e.g., ammonium), neighborhood deprivation, and built environment (e.g., food access) that were associated with increased risk of PASC conditions related to nervous, respiratory, blood, circulatory, endocrine, and other organ systems. Specific contextual and spatial risk factors for each PASC condition and symptom were different across New York City area and Florida. Future research is warranted to extend the analyses to other regions and examine more granular contextual and spatial characteristics to inform public health efforts to help patients recover from SARS-CoV-2 infection.

Machine Learning for Identifying Data-Driven Subphenotypes of Incident Post-Acute SARS-CoV-2 Infection Conditions with Large Scale Electronic Health Records: Findings from the RECOVER Initiative (preprint)

The post-acute sequelae of SARS-CoV-2 infection (PASC) refers to a broad spectrum of symptoms and signs that are persistent, exacerbated, or newly incident in the post-acute SARS-CoV-2 infection period of COVID-19 patients. Most studies have examined these conditions individually without providing concluding evidence on co-occurring conditions. To answer this question, this study leveraged electronic health records (EHRs) from two large clinical research networks from the national Patient-Centered Clinical Research Network (PCORnet) and investigated patients’ newly incident diagnoses that appeared within 30 to 180 days after a documented SARS-CoV-2 infection. Through machine learning, we identified four reproducible subphenotypes of PASC dominated by blood and circulatory system, respiratory, musculoskeletal and nervous system, and digestive system problems, respectively. We also demonstrated that these subphenotypes were associated with distinct patterns of patient demographics, underlying conditions present prior to SARS-CoV-2 infection, acute infection phase severity, and use of new medications in the post-acute period. Our study provides novel insights into the heterogeneity of PASC and can inform stratified decision-making in the treatment of COVID-19 patients with PASC conditions.

Understanding Post-Acute Sequelae of SARS-CoV-2 Infection through Data-Driven Analysis with Longitudinal Electronic Health Records: Findings from the RECOVER Initiative (preprint)

Recent studies have investigated post-acute sequelae of SARS-CoV-2 infection (PASC) using real-world patient data such as electronic health records (EHR). Prior studies have typically been conducted on patient cohorts with small sample sizes 1 or specific patient populations 2,3 limiting generalizability. This study aims to characterize PASC using the EHR data warehouses from two large national patient-centered clinical research networks (PCORnet), INSIGHT and OneFlorida+, which include 11 million patients in New York City (NYC) and 16.8 million patients in Florida respectively. With a high-throughput causal inference pipeline using high-dimensional inverse propensity score adjustment, we identified a broad list of diagnoses and medications with significantly higher incidence 30-180 days after the laboratory-confirmed SARS-CoV-2 infection compared to non-infected patients. We found more PASC diagnoses and a higher risk of PASC in NYC than in Florida, which highlights the heterogeneity of PASC in different populations.

Hydroxychloroquine for pre-exposure prophylaxis of COVID-19 in health care workers: a randomized, multicenter, placebo-controlled trial (HERO-HCQ) (preprint)

ABSTRACT Objective To determine whether hydroxychloroquine (HCQ) is safe and effective at preventing COVID-19 infections among health care workers (HCW). Design Multicenter, 1:1 randomized, placebo-controlled, double-blind, parallel-group, superiority trial. Setting 34 clinical centers in the United States. Participants 1360 HCW at risk for COVID-19 infection enrolled between April and November 2020. Interventions A loading dose of HCQ 600 mg twice on Day 1 followed by 400 mg daily for 29 days or matching placebo taken orally. Main Outcome Measure Composite of confirmed or suspected COVID-19 clinical infection by Day 30 defined as new onset fever, cough, or dyspnea and either a positive SARS-CoV-2 PCR test (confirmed) or a lack of confirmatory testing due to local restrictions (suspected). Results Enrollment for the study was closed before full accrual due to difficulties recruiting additional participants. The primary composite endpoint occurred in 41 (6.0%) participants receiving HCQ and 53 (7.8%) participants receiving placebo. No statistically significant difference in the proportion of participants experiencing clinical infection (estimated difference of -1.8%, 95% confidence interval -4.6% to 0.9%, p=0.20). We identified no significant safety issues. Conclusion Oral HCQ taken as prescribed appeared to be safe in a group of HCW. No significant clinical benefits were observed. The study was underpowered to rule out a small but potentially important reduction in COVID-19 infections. Trial Registration NCT04334148

Characteristics of 24,516 Patients Diagnosed with COVID-19 Illness in a National Clinical Research Network: Results from PCORnet (preprint)

Background: National data from diverse institutions across the United States are critical for guiding policymakers as well as clinical and public health leaders. This study characterized a large national cohort of patients diagnosed with COVID-19 in the U.S., compared to patients diagnosed with viral pneumonia and influenza. Methods and Findings: We captured cross-sectional information from 36 large healthcare systems in 29 U.S. states, participating in PCORnet, the National Patient-Centered Clinical Research Network. Patients included were those diagnosed with COVID-19, viral pneumonia and influenza in any care setting, starting from January 1, 2020. Using distributed queries executed at each participating institution, we acquired information for patients on care setting (any, ambulatory, inpatient or emergency department, mechanical ventilator), age, sex, race, state, comorbidities (assessed with diagnostic codes), and medications used for treatment of COVID-19 (hydroxychloroquine with or without azithromycin; corticosteroids, anti-interleukin-6 agents). During this time period, 24,516 patients were diagnosed with COVID-19, with 42% in an emergency department or inpatient hospital setting; 79,639 were diagnosed with viral pneumonia (53% inpatient/ED) and 163,984 with influenza (41% inpatient/ED). Among COVID-19 patients, 68% were 20 to <65 years of age, with more of the hospitalized/ED patients in older age ranges (23% 65+ years vs. 12% for COVID-19 patients in the ambulatory setting). Patients with viral pneumonia were of a similar age, and patients with influenza were much younger. Comorbidities were common, especially for patients with COVID-19 and viral pneumonia, with hypertension (32% for COVID-19 and 46% for viral pneumonia), arrhythmias (20% and 35%), and pulmonary disease (19% and 40%) the most common. Hydroxychloroquine was used in treatment for 33% and tocilizumab for 11% of COVID-19 patients on mechanical ventilators (25% received azithromycin as well). Conclusion and Relevance: PCORnet leverages existing data to capture information on one of the largest U.S. cohorts to date of patients diagnosed with COVID-19 compared to patients diagnosed with viral pneumonia and influenza.