Search

Importance: SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis., Methods: RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms., Discussion: RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options., Registration: NCT05172024., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Helen Chu reported consulting for Merck, GSK, Pfizer, Ellume, Janssen, Vindico CME, and the Bill and Melinda Gates Foundation, and receiving research support from Gates Ventures, Ellume, and Sanofi Pasteur. She also serves as a co-investigator on studies funded by Pfizer, Novavax, and GSK. Maged Costantine reported receiving grant support for work not related to RECOVER work/publications from Baxter International and Siemens Healthcare and personal consulting fees not related to this paper from Progenity, Quidel Ortho, and Siemens Healthcare. Kristine Erlandson reported research funding from Gilead Sciences and consulting payments from Gilead Sciences, Merck, and ViiV Pharmaceuticals, all paid to the University of Colorado. Emily Gallagher reported consulting for Novartis, Flare Therapeutics and Seagen. Edward Gardner reported research support (clinical trials) from Gilead Sciences, ViiV Healthcare, and Cepheid. Jason Goldman reported research support from Gilead, Eli Lilly and Regeneron; grants from Gilead, Merck (BARDA); personal fees for consulting from Gilead, Eli Lilly; and non-financial support from Adaptive Biotechnologies and Labcorp/Monogram Biosciences outside the submitted work. Timothy Heinrich reported grant support from Merck Inc. and consulting fees from Roche. Rachel Hess reported serving as Data Safety Monitoring Board member for Astellas Pharmaceuticals unrelated to the current work. Leora Horwitz reported being a member of the National Academy of Medicine Committee on the Long-Term Health Effects Stemming from COVID-19 and Implications for the Social Security Administration. Priscilla Hsue reported receiving honoraria from Gilead and Merck unrelated to study topic, receiving study drug from Regeneron unrelated to study topic, and receiving a research grant from Novartis. Judith James reported OMRF has licensed her IP to Progentec Biosciences, has received grant support from Progentec Biosciences, and serves on Advisory Committees to Glaxo Smith Klein, Merck and Novartis. Arthur Kim reports providing educational materials to Clinical Care Options and UpToDate and serving on a Data Safety Monitoring board for Kintor Pharmaceuticals, Ltd. Bruce Levy reported serving as a consultant for AstraZeneca, Entrinsic Biosciences, Gossamer Bio and Nocion Therapeutics and receiving research support from Amgen, Genentech, GlaxoSmithKline, Pieris Pharmaceuticals, SRA and Sanofi unrelated to the current work. Vincent Marconi reported receiving grants from NIH during the conduct of the study and grants from NIH, Veteran Affairs, and Centers for Disease Control and Prevention; grants, personal fees, nonfinancial support, and other from Lilly and Gilead; grants and personal fees from ViiV; and nonfinancial support from Bayer outside the submitted work. Grace McComsey reported serving as consultant for Merck, Gilead, ViiV, Janssen and have received research support from Pfizer, Vanda, Genentech, Roche, Redhill and Cognivue. Torri Metz reported being a site PI and a participant in the medical advisory board for the planning of a Pfizer clinical trial of SARS-CoV-2 vaccination in pregnancy. She also reported being a site PI for a Pfizer study evaluating the pharmacokinetics of Paxlovid in pregnant people with COVID-19. Janet Mullington reported support for investigator-initiated research by "Open Medicine Foundation and the Patient-Led Research Collaborative" Princess Ogbogu reported research support from Astrazeneca, GSK, Blueprint medical; advisory board for Astrazeneca, GSK, Sanofi, Kalvista; and consulting for Astrazeneca, GSK Sairam Parthasarathy reported research funding to Institution from Sergey Brin foundation of COVID and Long-COVID research. Michael Peluso reported consulting fees from Gilead Sciences and AstraZeneca, and service on data safety monitoring board for American Gene Technologies. Sean Quigley reported service on speaker Board for Servier, Alnylam, Agios; service on advisory board for Recordati, Alexion. Franz Rischard reported research support from NIH/NHLBI, United Therapeutics, Acceleron/Merck, Janssen, Insmed, Aerovate, and Bayer; and consulting/advisory compensation from Acceleron and Bayer. Nadine Rouphael reported being a consultant for ICON and EMMES as a safety consultant for clinical trials; service on the advisory boards for Moderna; funds to institution from Sanofi, Lilly, Merck, Quidel and Pfizer. PJ Utz reported stock ownership of Gilead and PI of biomarker studies for Pfizer STOP-PASC paxlovid trial Juan Wisnivesky received receiving consulting honorarium from Sanofi, Banook, Prospero, PPD and Atea and research grants from Sanofi, Regeneron, Axella, and Arnold Consultants., (Copyright: © 2023 Horwitz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The COVID-19 pandemic has demonstrated the need for efficient and comprehensive, simultaneous assessment of multiple combined novel therapies for viral infection across the range of illness severity. Randomized Controlled Trials (RCT) are the gold standard by which efficacy of therapeutic agents is demonstrated. However, they rarely are designed to assess treatment combinations across all relevant subgroups. A big data approach to analyzing real-world impacts of therapies may confirm or supplement RCT evidence to further assess effectiveness of therapeutic options for rapidly evolving diseases such as COVID-19., Methods: Gradient Boosted Decision Tree, Deep and Convolutional Neural Network classifiers were implemented and trained on the National COVID Cohort Collaborative (N3C) data repository to predict the patients' outcome of death or discharge. Models leveraged the patients' characteristics, the severity of COVID-19 at diagnosis, and the calculated proportion of days on different treatment combinations after diagnosis as features to predict the outcome. Then, the most accurate model is utilized by eXplainable Artificial Intelligence (XAI) algorithms to provide insights about the learned treatment combination impacts on the model's final outcome prediction., Results: Gradient Boosted Decision Tree classifiers present the highest prediction accuracy in identifying patient outcomes with area under the receiver operator characteristic curve of 0.90 and accuracy of 0.81 for the outcomes of death or sufficient improvement to be discharged. The resulting model predicts the treatment combinations of anticoagulants and steroids are associated with the highest probability of improvement, followed by combined anticoagulants and targeted antivirals. In contrast, monotherapies of single drugs, including use of anticoagulants without steroid or antivirals are associated with poorer outcomes., Conclusions: This machine learning model by accurately predicting the mortality provides insights about the treatment combinations associated with clinical improvement in COVID-19 patients. Analysis of the model's components suggests benefit to treatment with combination of steroids, antivirals, and anticoagulant medication. The approach also provides a framework for simultaneously evaluating multiple real-world therapeutic combinations in future research studies., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Moradi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: While COVID-19 vaccines reduce adverse outcomes, post-vaccination SARS-CoV-2 infection remains problematic. We sought to identify community factors impacting risk for breakthrough infections (BTI) among fully vaccinated persons by rurality., Methods: We conducted a retrospective cohort study of US adults sampled between January 1 and December 20, 2021, from the National COVID Cohort Collaborative (N3C). Using Kaplan-Meier and Cox-Proportional Hazards models adjusted for demographic differences and comorbid conditions, we assessed impact of rurality, county vaccine hesitancy, and county vaccination rates on risk of BTI over 180 days following two mRNA COVID-19 vaccinations between January 1 and September 21, 2021. Additionally, Cox Proportional Hazards models assessed the risk of infection among adults without documented vaccinations. We secondarily assessed the odds of hospitalization and adverse COVID-19 events based on vaccination status using multivariable logistic regression during the study period., Results: Our study population included 566,128 vaccinated and 1,724,546 adults without documented vaccination. Among vaccinated persons, rurality was associated with an increased risk of BTI (adjusted hazard ratio [aHR] 1.53, 95% confidence interval [CI] 1.42-1.64, for urban-adjacent rural and 1.65, 1.42-1.91, for nonurban-adjacent rural) compared to urban dwellers. Compared to low vaccine-hesitant counties, higher risks of BTI were associated with medium (1.07, 1.02-1.12) and high (1.33, 1.23-1.43) vaccine-hesitant counties. Compared to counties with high vaccination rates, a higher risk of BTI was associated with dwelling in counties with low vaccination rates (1.34, 1.27-1.43) but not medium vaccination rates (1.00, 0.95-1.07). Community factors were also associated with higher odds of SARS-CoV-2 infection among persons without a documented vaccination. Vaccinated persons with SARS-CoV-2 infection during the study period had significantly lower odds of hospitalization and adverse events across all geographic areas and community exposures., Conclusions: Our findings suggest that community factors are associated with an increased risk of BTI, particularly in rural areas and counties with high vaccine hesitancy. Communities, such as those in rural and disproportionately vaccine hesitant areas, and certain groups at high risk for adverse breakthrough events, including immunosuppressed/compromised persons, should continue to receive public health focus, targeted interventions, and consistent guidance to help manage community spread as vaccination protection wanes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Anzalone et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)