Harnessing the Power of Blockchains and Machine Learning to End the COVID-19 Pandemic.

The last catastrophic pandemic the world has seen was the 1918 H1N1 influenza pandemic, considering that it happened 102 years ago, one can perhaps leverage the technologic advancements over the past century to combat the current pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (COVID-19), which has already infected more than 16 million people globally and shut down the majority of the daily activities of life. The danger and challenge of infectious diseases such as COVID-19 lies in their highly contagious nature, spreading like wildfire with the potential to infect the majority of the world's population unless drastic measures are undertaken. In some countries, the social distancing and quarantine measures are either insufficient or ineffective as the number of cases is still on the rise. A major issue causing this rise is that most COVID-19 carriers appear asymptomatic. Identifying infected individuals as well as healthy/immune ones is the most crucial step in halting the disease spread. This is where the role of mass screening comes in.

Expanding repertoire of SARS-CoV-2 deletion mutations contributes to evolution of highly transmissible variants.

The emergence of highly transmissible SARS-CoV-2 variants and vaccine breakthrough infections globally mandated the characterization of the immuno-evasive features of SARS-CoV-2. Here, we systematically analyzed 2.13 million SARS-CoV-2 genomes from 188 countries/territories (up to June 2021) and performed whole-genome viral sequencing from 102 COVID-19 patients, including 43 vaccine breakthrough infections. We identified 92 Spike protein mutations that increased in prevalence during at least one surge in SARS-CoV-2 test positivity in any country over a 3-month window. Deletions in the Spike protein N-terminal domain were highly enriched for these 'surge-associated mutations' (Odds Ratio = 14.19, 95% CI 6.15-32.75, p value = 3.41 × 10-10). Based on a longitudinal analysis of mutational prevalence globally, we found an expanding repertoire of Spike protein deletions proximal to an antigenic supersite in the N-terminal domain that may be one of the key contributors to the evolution of highly transmissible variants. Finally, we generated clinically annotated SARS-CoV-2 whole genome sequences from 102 patients and identified 107 unique mutations, including 78 substitutions and 29 deletions. In five patients, we identified distinct deletions between residues 85-90, which reside within a linear B cell epitope. Deletions in this region arose contemporaneously on a diverse background of variants across the globe since December 2020. Overall, our findings based on genomic-epidemiology and clinical surveillance suggest that the genomic deletion of dispensable antigenic regions in SARS-CoV-2 may contribute to the evasion of immune responses and the evolution of highly transmissible variants.

Inference from longitudinal laboratory tests characterizes temporal evolution of COVID-19-associated coagulopathy (CAC).

Temporal inference from laboratory testing results and triangulation with clinical outcomes extracted from unstructured electronic health record (EHR) provider notes is integral to advancing precision medicine. Here, we studied 246 SARS-CoV-2 PCR-positive (COVIDpos) patients and propensity-matched 2460 SARS-CoV-2 PCR-negative (COVIDneg) patients subjected to around 700,000 lab tests cumulatively across 194 assays. Compared to COVIDneg patients at the time of diagnostic testing, COVIDpos patients tended to have higher plasma fibrinogen levels and lower platelet counts. However, as the infection evolves, COVIDpos patients distinctively show declining fibrinogen, increasing platelet counts, and lower white blood cell counts. Augmented curation of EHRs suggests that only a minority of COVIDpos patients develop thromboembolism, and rarely, disseminated intravascular coagulopathy (DIC), with patients generally not displaying platelet reductions typical of consumptive coagulopathies. These temporal trends provide fine-grained resolution into COVID-19 associated coagulopathy (CAC) and set the stage for personalizing thromboprophylaxis.

Medical Boards: Impact of Growing Virtual Care and Need for Integrated Approach to Enhance Quality and Safety

The increased amount of virtual care during the COVID-19 pandemic has exacerbated the challenge of providing appropriate medical board oversight to ensure proper quality of care delivery and safety of patients. This is partly due to the conventional model of each state medical board (SMB) holding responsibility for medical standards and oversight only within the jurisdiction of that state board and partly due to regulatory waivers and reduced enforcement of privacy policies. Even with a revoked license in one state, significant number of physicians have continued to practice by obtaining a medical license in a different state. Individualized requests were sent to 63 medical boards with questions related to practice of telemedicine and digital health by debarred or penalized medical doctors. The responses revealed major deficiencies and the urgent need to adopt a nationwide framework and to create an anchor point to serve as the coordinator of all relevant information related to incidents of improper medical practice. The ability to cause damage to large number of patients is significantly more now. Federal and state agencies urgently need to provide more attention and funding to issues related to quality of care and patient care in the changing ecosystem that includes medical specialists at a distance and the use of evolving digital health services and products. The creation, maintenance, and use of an integrated information system at national and multinational levels is increasingly important.

A COVID-19 Telehealth Impact Study—Exploring One Year of Telehealth Experimentation

Importance: This three-part study characterizes the widespread implementation of telehealth during the first year of the COVID-19 pandemic, giving us insight into the role of telehealth as we enter a stage of “new normal” healthcare delivery in the U.S. Objective: The COVID-19 Telehealth Impact Study was designed to describe the natural experiment of telehealth adoption during the pandemic. Using a large claims data stream and surveys of providers and patients, we studied telehealth in all 50 states to inform healthcare leaders. Design, Setting, Participants: In March 2020, the MITRE Corporation and Mayo Clinic founded the COVID-19 Healthcare Coalition (C19HCC), to respond to the pandemic. We report trends using a dataset of over 2 billion healthcare claims covering over 50% of private insurance activity in the U.S. (January 2019-December 2020), along with key elements from our provider survey (July-August 2020) and patient survey (November 2020 - February 2021). Main Outcomes and Measures: There was rapid and widespread adoption of telehealth in Spring 2020 with over 12 million telehealth claims in April 2020, accounting for 49.4% of total health care claims. Providers and patients expressed high levels of satisfaction with telehealth. 75% of providers indicated that telehealth enabled them to provide quality care. 84% of patients agreed that quality of their telehealth visit was good. Results: Peak levels of telehealth use varied widely among states ranging from 74.9% in Massachusetts to 25.4% in Mississippi. Every clinical discipline saw a steep rise with the largest claims volume in behavioral health. Provision of care by out-of-state provider was common at 6.5% (October-December 2020). Providers reported multiple modalities of telehealth care delivery. 74% of patients indicated they will use telehealth services in the future. Conclusions and Relevance: Innovation shown by providers and patients during this period of rapid telehealth expansion constitutes a great natural experiment in care delivery with evidence supporting widespread clinical adoption and satisfaction on the part of both patients and clinicians. The authors encourage continued broad access to telehealth over the next 12 months to allow telehealth best practices to emerge, creating a more effective and resilient system of care delivery.

Predictions for Telehealth in 2021: We Can’t Wait for It!

For long-term and episodic telehealth, we start to see the “final mile experience” with home delivery of pharmaceuticals, durable medical equipment, and even direct-to-consumer lab testing. [...]I am optimistic that synergistic integration of telehealth services with big data, AI-powered algorithms and information from wearables or mobile devices will have the greatest positive impact on healthcare and its outcomes over the next 2–5 years (more than any digital technology alone). [...]rideshare companies bent the cost curve to the point where riders can stop paying high monthly parking fees (aka insurance premiums) and continue to get low-cost, safe, reliable transportation (aka virtual visits) when needed. [...]telehealth will follow the rideshare roadmap…or maybe we will just merge industries.2 Ingrid Vasiliu-Feltes Over the past few years, we have witnessed a significant increase in telehealth adoption and expansion. “Tele-XR-Health” (a telehealth clinic with VR powered medical treatments) has the potential to redefine and reshape medical education, medical training, virtual healthcare delivery, and virtual clinical trials.

Surveillance of Safety of 3 Doses of COVID-19 mRNA Vaccination Using Electronic Health Records.

Importance: Recent reports on waning of COVID-19 vaccine-induced immunity have led to the approval and rollout of additional doses and booster vaccinations. Individuals at increased risk of SARS-CoV-2 infection are receiving additional vaccine doses in addition to the regimen that was tested in clinical trials. Risks and adverse event profiles associated with additional vaccine doses are currently not well understood. Objective: To evaluate the safety of third-dose vaccination with US Food and Drug Administration (FDA)-approved COVID-19 mRNA vaccines. Design, Setting, and Participants: This cohort study was conducted using electronic health record (EHR) data from December 2020 to October 2021 from the multistate Mayo Clinic Enterprise. Participants included all 47 999 individuals receiving 3-dose COVID-19 mRNA vaccines within the study setting who met study inclusion criteria. Participants were divided into 2 cohorts by vaccine brand administered and served as their own control groups, with no comparison made between cohorts. Data were analyzed from September through November 2021. Exposures: Three doses of an FDA-authorized COVID-19 mRNA vaccine, BNT162b2 or mRNA-1273. Main Outcomes and Measures: Vaccine-associated adverse events were assessed via EHR report. Adverse event risk was quantified using the percentage of study participants who reported the adverse event within 14 days after each vaccine dose and during a 14-day control period, immediately preceding the first vaccine dose. Results: Among 47 999 individuals who received 3-dose COVID-19 mRNA vaccines, 38 094 individuals (21 835 [57.3%] women; median [IQR] age, 67.4 [52.5-76.5] years) received BNT162b2 (79.4%) and 9905 individuals (5099 [51.5%] women; median [IQR] age, 67.7 [59.5-73.9] years) received mRNA-1273 (20.6%). Reporting of severe adverse events remained low after the third vaccine dose, with rates of pericarditis (0.01%; 95% CI, 0%-0.02%), anaphylaxis (0%; 95% CI, 0%-0.01%), myocarditis (0%; 95% CI, 0%-0.01%), and cerebral venous sinus thrombosis (no individuals) consistent with results from earlier studies. Significantly more individuals reported low-severity adverse events after the third dose compared with after the second dose, including fatigue (2360 individuals [4.92%] vs 1665 individuals [3.47%]; P < .001), lymphadenopathy (1387 individuals [2.89%] vs 995 individuals [2.07%]; P < .001), nausea (1259 individuals [2.62%] vs 979 individuals [2.04%]; P < .001), headache (1185 individuals [2.47%] vs 992 individuals [2.07%]; P < .001), arthralgia (1019 individuals [2.12%] vs 816 individuals [1.70%]; P < .001), myalgia (956 individuals [1.99%] vs 784 individuals [1.63%]; P < .001), diarrhea (817 individuals [1.70%] vs 595 individuals [1.24%]; P < .001), fever (533 individuals [1.11%] vs 391 individuals [0.81%]; P < .001), vomiting (528 individuals [1.10%] vs 385 individuals [0.80%]; P < .001), and chills (224 individuals [0.47%] vs 175 individuals [0.36%]; P = .01). Conclusions and Relevance: This study found that although third-dose vaccination against SARS-CoV-2 infection was associated with increased reporting of low-severity adverse events, risk of severe adverse events remained comparable with risk associated with the standard 2-dose regime. These findings suggest the safety of third vaccination doses in individuals who were eligible for booster vaccination at the time of this study.

Enabling Research and Clinical Use of Patient-Generated Health Data (the mindLAMP Platform): Digital Phenotyping Study.

BACKGROUND: There is a growing need for the integration of patient-generated health data (PGHD) into research and clinical care to enable personalized, preventive, and interactive care, but technical and organizational challenges, such as the lack of standards and easy-to-use tools, preclude the effective use of PGHD generated from consumer devices, such as smartphones and wearables. OBJECTIVE: This study outlines how we used mobile apps and semantic web standards such as HTTP 2.0, Representational State Transfer, JSON (JavaScript Object Notation), JSON Schema, Transport Layer Security (version 1.3), Advanced Encryption Standard-256, OpenAPI, HTML5, and Vega, in conjunction with patient and provider feedback to completely update a previous version of mindLAMP. METHODS: The Learn, Assess, Manage, and Prevent (LAMP) platform addresses the abovementioned challenges in enhancing clinical insight by supporting research, data analysis, and implementation efforts around PGHD as an open-source solution with freely accessible and shared code. RESULTS: With a simplified programming interface and novel data representation that captures additional metadata, the LAMP platform enables interoperability with existing Fast Healthcare Interoperability Resources-based health care systems as well as consumer wearables and services such as Apple HealthKit and Google Fit. The companion Cortex data analysis and machine learning toolkit offer robust support for artificial intelligence, behavioral feature extraction, interactive visualizations, and high-performance data processing through parallelization and vectorization techniques. CONCLUSIONS: The LAMP platform incorporates feedback from patients and clinicians alongside a standards-based approach to address these needs and functions across a wide range of use cases through its customizable and flexible components. These range from simple survey-based research to international consortiums capturing multimodal data to simple delivery of mindfulness exercises through personalized, just-in-time adaptive interventions.

Comparative effectiveness of mRNA-1273 and BNT162b2 against symptomatic SARS-CoV-2 infection.

BACKGROUND: mRNA coronavirus disease 2019 (COVID-19) vaccines are safe and effective, but increasing reports of breakthrough infections highlight the need to vigilantly monitor and compare the effectiveness of these vaccines. METHODS: We retrospectively compared protection against symptomatic infection conferred by mRNA-1273 and BNT162b2 at Mayo Clinic sites from December 2020 to September 2021. We used a test-negative case-control design to estimate vaccine effectiveness (VE) and to compare the odds of symptomatic infection after full vaccination with mRNA-1273 versus BNT162b2, while adjusting for age, sex, race, ethnicity, geography, comorbidities, and calendar time of vaccination and testing. FINDINGS: Both vaccines were highly effective over the study duration (VEmRNA-1273: 84.1%, 95% confidence interval [CI]: 81.6%-86.2%; VEBNT162b2: 75.6%, 95% CI: 72.2%-78.7%), but their effectiveness was reduced during July-September (VEmRNA-1273: 75.6%, 95% CI: 70.1%-80%; VEBNT162b2: 63.5%, 95% CI: 55.8%-69.9%) as compared to December-May (VEmRNA-1273: 93.7%, 95% CI: 90.4%-95.9%; VEBNT162b2: 85.7%, 95% CI: 81.4%-88.9%). Adjusted for demographic characteristics, clinical comorbidities, time of vaccination, and time of testing, the odds of experiencing a symptomatic breakthrough infection were lower after full vaccination with mRNA-1273 than with BNT162b2 (odds ratio: 0.60; 95% CI: 0.55-0.67). CONCLUSIONS: Both mRNA-1273 and BNT162b2 strongly protect against symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. It is imperative to continue monitoring and comparing available vaccines over time and with respect to emerging variants to inform public and global health decisions. FUNDING: This study was funded by nference.

Analysis of the Effectiveness of the Ad26.COV2.S Adenoviral Vector Vaccine for Preventing COVID-19.

Importance: Continuous assessment of the effectiveness and safety of the US Food and Drug Administration-authorized SARS-CoV-2 vaccines is critical to amplify transparency, build public trust, and ultimately improve overall health outcomes. Objective: To evaluate the effectiveness of the Johnson & Johnson Ad26.COV2.S vaccine for preventing SARS-CoV-2 infection. Design, Setting, and Participants: This comparative effectiveness research study used large-scale longitudinal curation of electronic health records from the multistate Mayo Clinic Health System (Minnesota, Arizona, Florida, Wisconsin, and Iowa) to identify vaccinated and unvaccinated adults between February 27 and July 22, 2021. The unvaccinated cohort was matched on a propensity score derived from age, sex, zip code, race, ethnicity, and previous number of SARS-CoV-2 polymerase chain reaction tests. The final study cohort consisted of 8889 patients in the vaccinated group and 88 898 unvaccinated matched patients. Exposure: Single dose of the Ad26.COV2.S vaccine. Main Outcomes and Measures: The incidence rate ratio of SARS-CoV-2 infection in the vaccinated vs unvaccinated control cohorts, measured by SARS-CoV-2 polymerase chain reaction testing. Results: The study was composed of 8889 vaccinated patients (4491 men [50.5%]; mean [SD] age, 52.4 [16.9] years) and 88 898 unvaccinated patients (44 748 men [50.3%]; mean [SD] age, 51.7 [16.7] years). The incidence rate ratio of SARS-CoV-2 infection in the vaccinated vs unvaccinated control cohorts was 0.26 (95% CI, 0.20-0.34) (60 of 8889 vaccinated patients vs 2236 of 88 898 unvaccinated individuals), which corresponds to an effectiveness of 73.6% (95% CI, 65.9%-79.9%) and a 3.73-fold reduction in SARS-CoV-2 infections. Conclusions and Relevance: This study's findings are consistent with the clinical trial-reported efficacy of Ad26.COV2.S and the first retrospective analysis, suggesting that the vaccine is effective at reducing SARS-CoV-2 infection, even with the spread of variants such as Alpha or Delta that were not present in the original studies, and reaffirm the urgent need to continue mass vaccination efforts globally.

Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram.

OBJECTIVE: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using artificial intelligence applied to the electrocardiogram (ECG). METHODS: A global, volunteer consortium from 4 continents identified patients with ECGs obtained around the time of polymerase chain reaction-confirmed COVID-19 diagnosis and age- and sex-matched controls from the same sites. Clinical characteristics, polymerase chain reaction results, and raw electrocardiographic data were collected. A convolutional neural network was trained using 26,153 ECGs (33.2% COVID positive), validated with 3826 ECGs (33.3% positive), and tested on 7870 ECGs not included in other sets (32.7% positive). Performance under different prevalence values was tested by adding control ECGs from a single high-volume site. RESULTS: The area under the curve for detection of acute COVID-19 infection in the test group was 0.767 (95% CI, 0.756 to 0.778; sensitivity, 98%; specificity, 10%; positive predictive value, 37%; negative predictive value, 91%). To more accurately reflect a real-world population, 50,905 normal controls were added to adjust the COVID prevalence to approximately 5% (2657/58,555), resulting in an area under the curve of 0.780 (95% CI, 0.771 to 0.790) with a specificity of 12.1% and a negative predictive value of 99.2%. CONCLUSION: Infection with SARS-CoV-2 results in electrocardiographic changes that permit the artificial intelligence-enhanced ECG to be used as a rapid screening test with a high negative predictive value (99.2%). This may permit the development of electrocardiography-based tools to rapidly screen individuals for pandemic control.

Mapping each pre-existing condition's association to short-term and long-term COVID-19 complications.

Understanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage ~1.1 million clinical notes from 1803 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0-30 days, 31-60 days, and 61-90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (89/1803 patients, 4.9%) followed by cardiac arrhythmia (45/1803 patients, 2.5%). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia, and anemia. The onset of new complications after 30 days is rare and most commonly involves pleural effusion (31-60 days: 11 patients, 61-90 days: 9 patients). Lastly, comparing the rates of complications with a propensity-matched COVID-negative hospitalized population confirmed the importance of hypertension as a risk factor for early-onset complications. Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.

Cerebral Venous Sinus Thrombosis is not Significantly Linked to COVID-19 Vaccines or Non-COVID Vaccines in a Large Multi-State Health System.

OBJECTIVE: To assess the association of COVID-19 vaccines and non-COVID-19 vaccines with cerebral venous sinus thrombosis (CVST). MATERIALS AND METHOD: We retrospectively analyzed a cohort of 771,805 vaccination events across 266,094 patients in the Mayo Clinic Health System between 01/01/2017 and 03/15/2021. The primary outcome was a positive diagnosis of CVST, identified either by the presence of a corresponding ICD code or by an NLP algorithm which detected positive diagnosis of CVST within free-text clinical notes. For each vaccine we calculated the relative risk by dividing the incidence of CVST in the 30 days following vaccination to that in the 30 days preceding vaccination. RESULTS: We identified vaccination events for all FDA-approved COVID-19 vaccines including Pfizer-BioNTech (n = 94,818 doses), Moderna (n = 36,350 doses) and Johnson & Johnson - J&J (n = 1,745 doses). We also identified vaccinations events for 10 common FDA-approved non-COVID-19 vaccines (n = 771,805 doses). There was no statistically significant difference in the incidence rate of CVST in 30-days before and after vaccination for any vaccine in this population. We further found the baseline CVST incidence in the study population between 2017 and 2021 to be 45 to 98 per million patient years. CONCLUSIONS: This real-world evidence-based study finds that CVST is rare and is not significantly associated with COVID-19 vaccination in our patient cohort. Limitations include the rarity of CVST in our dataset, a relatively small number of J&J COVID-19 vaccination events, and the use of a population drawn from recipients of a SARS-CoV-2 PCR test in a single health system.

Real-time analysis of a mass vaccination effort confirms the safety of FDA-authorized mRNA COVID-19 vaccines.

BACKGROUND: As the coronavirus disease 2019 (COVID-19) vaccination campaign unfolds, it is important to continuously assess the real-world safety of Food and Drug Administration (FDA)-authorized vaccines. Curation of large-scale electronic health records (EHRs) enables near-real-time safety evaluations that were not previously possible. METHODS: In this retrospective study, we deployed deep neural networks over a large EHR system to automatically curate the adverse effects mentioned by physicians in over 1.2 million clinical notes between December 1, 2020 and April 20, 2021. We compared notes from 68,266 individuals who received at least one dose of BNT162b2 (n = 51,795) or mRNA-1273 (n = 16,471) to notes from 68,266 unvaccinated individuals who were matched by demographic, geographic, and clinical features. FINDINGS: Individuals vaccinated with BNT162b2 or mRNA-1273 had a higher rate of return to the clinic, but not the emergency department, after both doses compared to unvaccinated controls. The most frequently documented adverse effects within 7 days of each vaccine dose included myalgia, headache, and fatigue, but the rates of EHR documentation for each side effect were remarkably low compared to those derived from active solicitation during clinical trials. Severe events, including anaphylaxis, facial paralysis, and cerebral venous sinus thrombosis, were rare and occurred at similar frequencies in vaccinated and unvaccinated individuals. CONCLUSIONS: This analysis of vaccine-related adverse effects from over 1.2 million EHR notes of more than 130,000 individuals reaffirms the safety and tolerability of the FDA-authorized mRNA COVID-19 vaccines in practice. FUNDING: This study was funded by nference.

FDA-authorized mRNA COVID-19 vaccines are effective per real-world evidence synthesized across a multi-state health system.

BACKGROUND: Two US Food and Drug Administration (FDA)-authorized coronavirus disease 2019 (COVID-19) mRNA vaccines, BNT162b2 (Pfizer/BioNTech) and mRNA-1273 (Moderna), have demonstrated high efficacy in large phase 3 randomized clinical trials. It is important to assess their effectiveness in a real-world setting. METHODS: This is a retrospective analysis of 136,532 individuals in the Mayo Clinic health system (Arizona, Florida, Iowa, Minnesota, and Wisconsin) with PCR testing data between December 1, 2020 and April 20, 2021. We compared clinical outcomes for a vaccinated cohort of 68,266 individuals who received at least one dose of either vaccine (nBNT162b2 = 51,795; nmRNA-1273 = 16,471) and an unvaccinated control cohort of 68,266 individuals propensity matched based on relevant demographic, clinical, and geographic features. We estimated real-world vaccine effectiveness by comparing incidence rates of positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) PCR testing and COVID-19-associated hospitalization and intensive care unit (ICU) admission starting 7 days after the second vaccine dose. FINDINGS: The real-world vaccine effectiveness of preventing SARS-CoV-2 infection was 86.1% (95% confidence interval [CI]: 82.4%-89.1%) for BNT162b2 and 93.3% (95% CI: 85.7%-97.4%) for mRNA-1273. BNT162b2 and mRNA-1273 were 88.8% (95% CI: 75.5%-95.7%) and 86.0% (95% CI: 71.6%-93.9%) effective in preventing COVID-19-associated hospitalization. Both vaccines were 100% effective (95% CIBNT162b2: 51.4%-100%; 95% CImRNA-1273: 43.3%-100%) in preventing COVID-19-associated ICU admission. CONCLUSIONS: BNT162b2 and mRNA-1273 are effective in a real-world setting and are associated with reduced rates of SARS-CoV-2 infection and decreased burden of COVID-19 on the healthcare system. FUNDING: This study was funded by nference.

Anemia during SARS-CoV-2 infection is associated with rehospitalization after viral clearance.

Patients with COVID-19 can experience symptoms and complications after viral clearance. It is important to identify clinical features of patients who are likely to experience these prolonged effects. We conducted a retrospective study to compare longitudinal laboratory test measurements (hemoglobin, hematocrit, estimated glomerular filtration rate, serum creatinine, and blood urea nitrogen) in patients rehospitalized after PCR-confirmed SARS-CoV-2 clearance (n = 104) versus patients not rehospitalized after viral clearance (n = 278). Rehospitalized patients had lower median hemoglobin levels in the year prior to COVID-19 diagnosis (Cohen's D = -0.50; p = 1.2 × 10-3) and during their active SARS-CoV-2 infection (Cohen's D = -0.71; p = 4.6 × 10-8). Rehospitalized patients were also more likely to be diagnosed with moderate or severe anemia during their active infection (Odds Ratio = 4.07; p = 4.99 × 10-9). These findings suggest that anemia-related laboratory tests should be considered in risk stratification algorithms for patients with COVID-19.

Plasma IL-6 levels following corticosteroid therapy as an indicator of ICU length of stay in critically ill COVID-19 patients.

Intensive care unit (ICU) admissions and mortality in severe COVID-19 patients are driven by "cytokine storms" and acute respiratory distress syndrome (ARDS). Interim clinical trial results suggest that the corticosteroid dexamethasone displays better 28-day survival in severe COVID-19 patients requiring ventilation or oxygen. In this study, 10 out of 16 patients (62.5%) that had an average plasma IL-6 value over 10 pg/mL post administration of corticosteroids also had worse outcomes (i.e., ICU stay >15 days or death), compared to 8 out of 41 patients (19.5%) who did not receive corticosteroids (p-value = 0.0024). Given this potential association between post-corticosteroid IL-6 levels and COVID-19 severity, we hypothesized that the glucocorticoid receptor (GR or NR3C1) may be coupled to IL-6 expression in specific cell types that govern cytokine release syndrome (CRS). Examining single-cell RNA-seq data from BALF of severe COVID-19 patients and nearly 2 million cells from a pan-tissue scan shows that alveolar macrophages, smooth muscle cells, and endothelial cells co-express NR3C1 and IL-6, motivating future studies on the links between the regulation of NR3C1 function and IL-6 levels.

Exploratory analysis of immunization records highlights decreased SARS-CoV-2 rates in individuals with recent non-COVID-19 vaccinations.

Clinical studies are ongoing to assess whether existing vaccines may afford protection against SARS-CoV-2 infection through trained immunity. In this exploratory study, we analyze immunization records from 137,037 individuals who received SARS-CoV-2 PCR tests. We find that polio, Haemophilus influenzae type-B (HIB), measles-mumps-rubella (MMR), Varicella, pneumococcal conjugate (PCV13), Geriatric Flu, and hepatitis A/hepatitis B (HepA-HepB) vaccines administered in the past 1, 2, and 5 years are associated with decreased SARS-CoV-2 infection rates, even after adjusting for geographic SARS-CoV-2 incidence and testing rates, demographics, comorbidities, and number of other vaccinations. Furthermore, age, race/ethnicity, and blood group stratified analyses reveal significantly lower SARS-CoV-2 rate among black individuals who have taken the PCV13 vaccine, with relative risk of 0.45 at the 5 year time horizon (n: 653, 95% CI (0.32, 0.64), p-value: 6.9e-05). Overall, this study identifies existing approved vaccines which can be promising candidates for pre-clinical research and Randomized Clinical Trials towards combating COVID-19.