Severe acute infection and chronic pulmonary disease are risk factors for developing post-COVID-19 conditions

Post-COVID-19 conditions, also known as "long COVID", has significantly impacted the lives of many individuals, but the risk factors for this condition are poorly understood. In this study, we performed a retrospective EHR analysis of 89,843 individuals at a multi-state health system in the United States with PCR-confirmed COVID-19, including 1,086 patients diagnosed with long COVID and 1,086 matched controls not diagnosed with long COVID. For these two cohorts, we evaluated a wide range of clinical covariates, including laboratory tests, medication orders, phenotypes recorded in the clinical notes, and outcomes. We found that chronic pulmonary disease (CPD) was significantly more common as a pre-existing condition for the long COVID cohort than the control cohort (odds ratio: 1.9, 95% CI: [1.5, 2.6]). Additionally, long-COVID patients were more likely to have a history of migraine (odds ratio: 2.2, 95% CI: [1.6, 3.1]) and fibromyalgia (odds ratio: 2.3, 95% CI: [1.3, 3.8]). During the acute infection phase, the following lab measurements were abnormal in the long COVID cohort: high triglycerides (meanlongCOVID: 278.5 mg/dL vs. meancontrol: 141.4 mg/dL), low HDL cholesterol levels (meanlongCOVID: 38.4 mg/dL vs. meancontrol: 52.5 mg/dL), and high neutrophil-lymphocyte ratio (meanlongCOVID: 10.7 vs. meancontrol: 7.2). The hospitalization rate during the acute infection phase was also higher in the long COVID cohort compared to the control cohort (ratelongCOVID: 5% vs. ratecontrol: 1%). Overall, this study suggests that the severity of acute infection and a history of CPD, migraine, CFS, or fibromyalgia may be risk factors for long COVID symptoms. Our findings motivate clinical studies to evaluate whether suppressing acute disease severity proactively, especially in patients at high risk, can reduce incidence of long COVID.

SARS-CoV-2 and influenza co-infection throughout the COVID-19 pandemic: An assessment of co-infection rates and cohort characterization

BackgroundCase reports of patients infected with COVID-19 and influenza virus ("flurona") have raised questions around the prevalence and clinical significance of these reports. MethodsEpidemiological data from the HHS Protect Public Data Hub was analyzed to show trends in SARS-CoV-2 and influenza co-infection-related hospitalizations in the United States in relation to SARS-CoV-2 and influenza strain data from NCBI Virus and FluView. In addition, we retrospectively analyzed all cases of PCR-confirmed SARS-CoV-2 across the Mayo Clinic Enterprise from January 2020 to January 2022 and identified cases of influenza co-infections within two weeks of PCR-positive diagnosis date. Using a cohort from the Mayo Clinic with joint PCR testing data, we estimated the expected number of co-infection cases given the background prevalences of COVID-19 and influenza during the Wuhan (Original), Alpha, Delta, and Omicron waves of the pandemic. FindingsConsidering data from all states of the United States using HHS Protect Public Data Hub, hospitalizations due to influenza co-infection with SARS-CoV-2 were seen to be highest in January 2022 compared to all previous months during the COVID-19 pandemic. Among 171,639 SARS-CoV-2-positive cases analyzed at Mayo Clinic between January 2020 and January 2022, only 73 cases of influenza co-infection were observed. Identified coinfected patients were relatively young (mean age: 28.4 years), predominantly male, and had few comorbidities. During the Delta era (June 16, 2021 to December 13, 2021), there were 9 lab-confirmed co-infection cases observed compared to 13.9 expected cases (95% CI: [12.7, 15.2]), and during the Omicron era (December 14, 2021 to January 17, 2022), there were 54 lab-confirmed co-infection cases compared to 80.9 expected cases (95% CI: [76.6, 85.1]). ConclusionsReported co-infections of SARS-CoV-2 and influenza are rare. These co-infections have occurred throughout the COVID-19 pandemic and their prevalence can be explained by background rates of COVID-19 and influenza infection. Preliminary assessment of longitudinal EHR data suggests that most co-infections so far have been observed among relatively young and healthy patients. Further analysis is needed to assess the outcomes of "flurona" among subpopulations with risk factors for severe COVID-19 such as older age, obesity, and immunocompromised status. Significance StatementReports of COVID-19 and influenza co-infections ("flurona") have raised concern in recent months as both COVID-19 and influenza cases have increased to significant levels in the US. Here, we analyze trends in co-infection cases over the course of the pandemic to show that these co-infection cases are expected given the background prevalences of COVID-19 and influenza independently. In addition, from an initial analysis of these co-infection cases which have been observed at the Mayo Clinic, we find that these co-infection cases are extremely rare and have mostly been observed in relatively young, healthy patients.

Three doses of COVID-19 mRNA vaccination are safe based on adverse events reported in electronic health records

Recent reports on waning of COVID-19 vaccine induced immunity have led to the approval and roll-out of additional dose and booster vaccinations. At risk individuals are receiving additional vaccine dose(s), in addition to the regimen that was tested in clinical trials. The risks and the adverse event profiles associated with these additional vaccine doses are currently not well understood. Here, we performed a retrospective study analyzing vaccine-associated adverse events using electronic health records (EHRs) of individuals that have received three doses of mRNA-based COVID-19 vaccines (n = 47,999). By comparing symptoms reported in 2-week time periods after each vaccine dose and in a 2-week period before the 1st vaccine dose, we assessed the risk associated with 3rd dose vaccination, for both BNT162b2 and mRNA-1273. Reporting of severe adverse events remained low after the 3rd vaccine dose, with rates of pericarditis (0.01%, 0%-0.02% 95% CI), anaphylaxis (0.00%, 0%-0.01% 95% CI), myocarditis (0.00%, 0%-0.01% 95% CI), and cerebral venous sinus thrombosis (no cases), consistent with earlier studies. Significantly more individuals (p-value < 0.05) report low-severity adverse events after their 3rd dose compared with after their 2nd dose, including fatigue (4.92% after 3rd dose vs 3.47% after 2nd dose), lymphadenopathy (2.89% vs 2.07%), nausea (2.62% vs 2.04%), headache (2.47% vs 2.07%), arthralgia (2.12% vs 1.70%), myalgia (1.99% vs 1.63%), diarrhea (1.70% vs 1.24%), fever (1.11% vs 0.81%), vomiting (1.10% vs 0.80%), and chills (0.47% vs 0.36%). Our results show that although 3rd dose vaccination against SARS-CoV-2 infection led to increased reporting of low-severity adverse events, risk of severe adverse events remained comparable to the standard 2-dose regime. This study provides support for the safety of 3rd vaccination doses of individuals that are at high-risk of severe COVID-19 and breakthrough infection.

COVID-19 vaccines dampen genomic diversity of SARS-CoV-2: Unvaccinated patients exhibit more antigenic mutational variance

Variants of SARS-CoV-2 are evolving under a combination of immune selective pressure in infected hosts and natural genetic drift, raising a global alarm regarding the durability of COVID-19 vaccines. Here, we conducted longitudinal analysis over 1.8 million SARS-CoV-2 genomes from 183 countries or territories to capture vaccination-associated viral evolutionary patterns. To augment this macroscale analysis, we performed viral genome sequencing in 23 vaccine breakthrough COVID-19 patients and 30 unvaccinated COVID-19 patients for whom we also conducted machine-augmented curation of the electronic health records (EHRs). Strikingly, we find the diversity of the SARS-CoV-2 lineages is declining at the country-level with increased rate of mass vaccination (n = 25 countries, mean correlation coefficient = -0.72, S.D. = 0.20). Given that the COVID-19 vaccines leverage B-cell and T-cell epitopes, analysis of mutation rates shows neutralizing B-cell epitopes to be particularly more mutated than comparable amino acid clusters (4.3-fold, p < 0.001). Prospective validation of these macroscale evolutionary patterns using clinically annotated SARS-CoV-2 whole genome sequences confirms that vaccine breakthrough patients indeed harbor viruses with significantly lower diversity in known B cell epitopes compared to unvaccinated COVID-19 patients (2.3-fold, 95% C.I. 1.4-3.7). Incidentally, in these study cohorts, vaccinated breakthrough patients also displayed fewer COVID-associated complications and pre-existing conditions relative to unvaccinated COVID-19 patients. This study presents the first known evidence that COVID-19 vaccines are fundamentally restricting the evolutionary and antigenic escape pathways accessible to SARS-CoV-2. The societal benefit of mass vaccination may consequently go far beyond the widely reported mitigation of SARS-CoV-2 infection risk and amelioration of community transmission, to include stemming of rampant viral evolution.

Association of Intravenous Bamlanivimab Use with Reduced Hospitalization, Intensive Care Unit Admission, and Mortality in Patients with Mild to Moderate COVID-19

BackgroundClinical data to support the use of bamlanivimab for the treatment of outpatients with mild to moderate coronavirus disease-19 (COVID-19) is needed. Methods2,335 patients who received single-dose bamlanivimab infusion between November 12, 2020 to February 17, 2021 were compared with a propensity-matched control of 2,335 untreated patients with mild to moderate COVID-19 at Mayo Clinic facilities across 4 states. The primary outcome was the rate of hospitalization at days 14, 21 and 28. ResultsThe median age of the population was 63; 47.3% of the bamlanivimab-treated cohort were [≥]65 years; 49.3% were female. High-risk characteristics included hypertension (54.2%), body mass index [≥]35 (32.4%), diabetes mellitus (26.5%), chronic lung disease (25.1%), malignancy (16.6%), and renal disease (14.5%). Patients who received bamlanivimab had lower all-cause hospitalization rates at days 14 (1.5% vs 3.5%; Odds Ratio [OR], 0.38), 21 (1.9% vs 3.9%; OR, 0.46), and 28 (2.5% vs 3.9%; OR, 0.61). Secondary exploratory outcomes included lower intensive care unit admission rates at days 14 (0.14% vs 1%; OR, 0.12), 21 (0.25% vs 1%; OR: 0.24) and 28 (0.56% vs 1.1%; OR: 0.52), and lower all-cause mortality at days 14 (0% vs 0.33%), 21 (0.05% vs 0.4%; OR,0.08) and 28 (0.11% vs 0.44%; OR, 0.01). Adverse events were uncommon with bamlanivimab, occurring in 19/2355, most commonly fever (n=6), nausea (n=5), and lightheadedness (n=3). ConclusionsAmong high-risk patients with mild to moderate COVID-19, treatment with bamlanivimab was associated with a statistically significant lower rate of hospitalization compared with usual care. FundingMayo Clinic.

Real-world effectiveness of Ad26.COV2.S adenoviral vector vaccine for COVID-19

In light of the massive and rapid vaccination campaign against COVID-19, continuous real-world effectiveness and safety assessment of the FDA-authorized vaccines is critical to amplify transparency, build public trust, and ultimately improve overall health outcomes. In this study, we leveraged large-scale longitudinal curation of electronic health records (EHRs) from the multi-state Mayo Clinic health system (MN, AZ, FL, WN, IA). We compared the infection rate of 2,195 individuals who received a single dose of the Ad26.COV2.S vaccine from Johnson & Johnson (J&J) to the infection rate of 21,950 unvaccinated, propensity-matched individuals between February 27th and April 14th 2021. Of the 1,779 vaccinated individuals with at least two weeks of follow-up, only 3 (0.17%) tested positive for SARS-CoV-2 15 days or more after vaccination compared to 128 of 17,744 (0.72%) unvaccinated individuals (4.34 fold reduction rate). This corresponds to a vaccine effectiveness of 76.7% (95% CI: 30.3-95.3%) in preventing SARS-CoV-2 infection with onset at least two weeks after vaccination. This data is consistent with the clinical trial-reported efficacy of Ad26.COV2.S in preventing moderate to severe COVID-19 with onset at least 14 days after vaccine administration (66.9%; 95% CI: 59.0-73.4%). Due to the recent authorization of the Ad26.COV2.S vaccine, there are not yet enough hospitalizations, ICU admissions, or deaths within this cohort to robustly assess the effect of vaccination on COVID-19 severity, but these outcomes will be continually assessed in near-real-time with our platform. Collectively, this study provides further evidence that a single dose of Ad26.COV2.S is highly effective in preventing SARS-CoV-2 infection and reaffirms the urgent need to continue mass vaccination efforts globally.

Cerebral venous sinus thrombosis (CVST) is not significantly linked to COVID-19 vaccines or non-COVID vaccines in a large multi-state US health system

Cerebral venous sinus thrombosis (CVST) has been reported in a small number of individuals who have received the mRNA vaccines1 or the adenoviral vector vaccines for COVID-19 in the US2 and Europe3. Continued pharmacovigilance is integral to mitigating the risk of rare adverse events that clinical trials are underpowered to detect, however, these anecdotal reports have led to the pause or withdrawal of some vaccines in many jurisdictions and exacerbated vaccine hesitancy at a critical moment in the fight against the COVID-19 pandemic. We investigated the frequencies of CVST seen among individuals who received FDA-authorized COVID-19 vaccines from Pfizer-BioNTech (n = 94,818 doses), Moderna (n = 36,350 doses) and Johnson & Johnson - J&J (n = 1,745 doses), and among individuals receiving one of 10 FDA-approved non-COVID-19 vaccines (n = 771,805 doses). Comparing the incidence rates of CVST in 30-day time windows before and after vaccination, we found no statistically significant differences for the COVID-19 vaccines or any other vaccines studied in this population. In total, we observed 3 cases of CVST within the 30 days following Pfizer-BioNTech vaccination (2 females, 1 male; Ages (years): [79, 80, 84]), including one individual with a prior history of thrombosis and another individual with recent trauma in the past 30 days. We did not observe any cases of CVST among the patients receiving Moderna or J&J vaccines in this study 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. Overall, this real-world evidence-based study highlights that CVST is rare and is not significantly associated with COVID-19 vaccination. In addition, there is a need for a concerted international effort to monitor EHR data across diverse patient populations and to investigate the underlying biological mechanisms leading to these rare clotting events.

Case fatality rates for COVID-19 are higher than case fatality rates for motor vehicle accidents for individuals over 40 years of age

The death toll of the COVID-19 pandemic has been unprecedented, due to both the high number of SARS-CoV-2 infections and the seriousness of the disease resulting from these infections. Here, we present mortality rates and case fatality rates for COVID-19 over the past year compared with other historic leading causes of death in the United States. Among the risk categories considered, COVID-19 is the third leading cause of death for individuals 40 years old and over, with an overall annual mortality rate of 325 deaths per 100K individuals, behind only cancer (385 deaths per 100K individuals) and heart disease (412 deaths per 100K individuals). In addition, for individuals 40 years old and over, the case fatality rate for COVID-19 is greater than the case fatality rate for motor vehicle accidents. In particular, for the age group 40-49, the relative case fatality rate of COVID-19 is 1.5 fold (95% CI: [1.3, 1.7]) that of a motor vehicle accident, demonstrating that SARS-CoV-2 infection may be significantly more dangerous than a car crash for this age group. For older adults, COVID-19 is even more dangerous, and the relative case fatality rate of COVID-19 is 29.4 fold (95% CI: [23.2, 35.7]) that of a motor vehicle accident for individuals over 80 years old. On the other hand, motor vehicle accidents have a 4.5 fold (95% CI: [3.9, 5.1]) greater relative case fatality rate compared to COVID-19 for the age group of 20-29 years. These results highlight the severity of the COVID-19 pandemic especially for adults above 40 years of age and underscore the need for large-scale preventative measures to mitigate risks for these populations. Given that FDA-authorized COVID-19 vaccines have now been validated by multiple studies for their outstanding real-world effectiveness and safety, vaccination of all individuals who are over 40 years of age is one of the most pressing public health priorities of our time.

COVID-associated pediatric hospitalization and ICU admission trends across a multi-state health system and the broader US population

Public health concerns are emerging based on reports of new SARS-CoV-2 variant strains purportedly triggering a rise in COVID-associated hospitalizations and ICU admissions, particularly in younger patients and the pediatric population. However, analyzing health records of COVID patients from the electronic health records (EHRs) of a multi-state US healthcare system, we find that there is actually a significant drop in COVID-associated hospitalization rates and ICU admission rates in March 2021 compared to February 2021. We further triangulate these EHR-derived insights with the official US government epidemiological data sets to show that during this same time period, there is no apparent nation-wide spike in pediatric hospitalizations. Our study motivates the need to develop a real-time system that integrates various COVID hospitalization and ICU monitoring efforts from the EHR databases of various health systems together with national epidemiological data sets. By infusing SARS-CoV-2 genomic sequencing data to flag potentially new or emergent viral strains, as well as county-level COVID vaccine rollout rates and shifts in SARS-CoV-2 PCR positivity rates into such a real-time monitoring system, public health policies and media reporting can be more effectively informed through the rigor of holistic biomedical data sciences.

Counties with lower insurance coverage are associated with both slower vaccine rollout and higher COVID-19 incidence across the United States

Efficient and equitable vaccination distribution is a priority for effectively outcompeting the transmission of COVID-19 globally. A recent study from the Centers for Disease Control and Prevention (CDC) identified that US counties with high social vulnerability according to metrics such as poverty, unemployment, low income, and no high school diploma, have significantly lower rates of vaccination compared to the national average1. Here, we build upon this analysis to consider associations between county-level vaccination rates and 68 different demographic, socioeconomic, and environmental factors for 1,510 American counties with over 228 million individuals for which vaccination data was also available. Our analysis reveals that counties with high levels of uninsured individuals have significantly lower COVID-19 vaccination rates (Spearman correlation: -0.264), despite the fact that the CDC has mandated that all COVID-19 vaccines are free and cannot be denied to anyone based upon health insurance coverage or immigration status. Furthermore, we find that the counties with high levels of uninsured individuals tend to have the highest COVID-19 incidence rates in March 2021 relative to December 2020 (Spearman correlation: 0.388). Among the 68 factors analyzed, insurance coverage is the only factor which is highly correlated with both vaccination rate and change in COVID-19 incidence during the vaccination period (|Spearman correlation|> 0.25). We also find that counties with higher percentages of Black and Hispanic individuals have significantly lower vaccination rates (Spearman correlations: -0.128, -0.136) and lesser declines of COVID-incidence rates (Spearman correlations: 0.334, 0.330) during the vaccination period. Surprisingly however, after controlling for race, we find that the association between lack of insurance coverage and vaccination rate as well as COVID-19 incidence rates is largely driven by counties with a majority white population. Among the counties with high proportions of white residents (top 10% decile), the association between insurance coverage and vaccination rate is significant (Spearman correlation: -0.210, p-value: 0.002), but among counties with low proportions of white residents (bottom 10% decile) this association is not significant (Spearman correlation: 0.072, p-value: 0.088). Taken together, this study highlights the fact that intricate socioeconomic factors are correlated not just to COVID-19 vaccination rates, but also to COVID-19 incidence fluctuations, underscoring the need to improve COVID-19 vaccination campaigns in marginalized communities. The strong positive correlation between low levels of health insurance coverage and low vaccination rates is particularly concerning, and calls for improved public health messaging to emphasize the fact that health insurance is not required to be eligible for any of the FDA-authorized COVID-19 vaccines in the United States

Higher COVID-19 vaccination rates are linked to decreased county-level COVID-19 incidence across USA

Real world evidence studies of mass vaccination across health systems have reaffirmed the safety1 and efficacy2,3 of the FDA-authorized mRNA vaccines for COVID-19. However, the impact of vaccination on community transmission remains to be characterized. Here, we compare the cumulative county-level vaccination rates with the corresponding COVID-19 incidence rates among 87 million individuals from 580 counties in the United States, including 12 million individuals who have received at least one vaccine dose. We find that cumulative county-level vaccination rate through March 1, 2021 is significantly associated with a concomitant decline in COVID-19 incidence (Spearman correlation {rho} = -0.22, p-value = 8.3e-8), with stronger negative correlations in the Midwestern counties ({rho} = -0.37, p-value = 1.3e-7) and Southern counties ({rho} = -0.33, p-value = 4.5e-5) studied. Additionally, all examined US regions demonstrate significant negative correlations between cumulative COVID-19 incidence rate prior to the vaccine rollout and the decline in the COVID-19 incidence rate between December 1, 2020 and March 1, 2021, with the US western region being particularly striking ({rho} = -0.66, p-value = 5.3e-37). However, the cumulative vaccination rate and cumulative incidence rate are noted to be statistically independent variables, emphasizing the need to continue the ongoing vaccination roll out at scale. Given confounders such as different coronavirus restrictions and mask mandates, varying population densities, and distinct levels of diagnostic testing and vaccine availabilities across US counties, we are advancing a public health resource to amplify transparency in vaccine efficacy monitoring (https://public.nferx.com/covid-monitor-lab/vaccinationcheck). Application of this resource highlights outliers like Dimmit county (Texas), where infection rates have increased significantly despite higher vaccination rates, ostensibly owing to amplified travel as a "vaccination hub"; as well as Henry county (Ohio) which encountered shipping delays leading to postponement of the vaccine clinics. This study underscores the importance of tying the ongoing vaccine rollout to a real-time monitor of spatio-temporal vaccine efficacy to help turn the tide of the COVID-19 pandemic.

Real-time analysis of a mass vaccination effort via an Artificial Intelligence platform confirms the safety of FDA-authorized COVID-19 vaccines

As the COVID-19 vaccination campaign unfolds as one of the most rapid and widespread in history, it is important to continuously assess the real world safety of the FDA-authorized vaccines. Curation from large-scale electronic health records (EHRs) allows for near real-time safety evaluations that were not previously possible. Here, we advance context- and sentiment-aware deep neural networks over the multi-state Mayo Clinic enterprise (Minnesota, Arizona, Florida, Wisconsin) for automatically curating the adverse effects mentioned by physicians in over 108,000 EHR clinical notes between December 1st 2020 to February 8th 2021. We retrospectively compared the clinical notes of 31,069 individuals who received at least one dose of the Pfizer/BioNTech or Moderna vaccine to those of 31,069 unvaccinated individuals who were propensity matched by demographics, residential location, and history of prior SARS-CoV-2 testing. We find that vaccinated and unvaccinated individuals were seen in the the clinic at similar rates within 21 days of the first or second actual or assigned vaccination dose (first dose Odds Ratio = 1.13, 95% CI: 1.09-1.16; second dose Odds Ratio = 0.89, 95% CI: 0.84-0.93). Further, the incidence rates of all surveyed adverse effects were similar or lower in vaccinated individuals compared to unvaccinated individuals after either vaccine dose. Finally, the most frequently documented adverse effects within 7 days of each vaccine dose were arthralgia (Dose 1: 0.59%; Dose 2: 0.39%), diarrhea (Dose 1: 0.58%; Dose 2: 0.33%), erythema (Dose 1: 0.51%; Dose 2: 0.31%), myalgia (Dose 1: 0.40%; Dose 2: 0.34%), and fever (Dose 1: 0.27%; Dose 2: 0.31%). These remarkably low frequencies of adverse effects recorded in EHRs versus those derived from active solicitation during clinical trials (arthralgia: 24-46%; erythema: 9.5-14.7%; myalgia: 38-62%; fever: 14.2-15.5%) emphasize the rarity of vaccine-associated adverse effects requiring clinical attention. This rapid and timely analysis of vaccine-related adverse effects from contextually rich EHR notes of 62,138 individuals, which was enabled through a large scale Artificial Intelligence (AI)-powered platform, reaffirms the safety and tolerability of the FDA-authorized COVID-19 vaccines in practice.

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

Large Phase 3 clinical trials of the two FDA-authorized COVID-19 vaccines, mRNA-1273 (Moderna) and BNT162b2 (Pfizer/BioNTech), have demonstrated efficacies of 94.1% (n = 30,420, 95% CI: 89.3-96.8) and 95% (n = 43,448, 95% CI: 90.3-97.6) in preventing symptomatic COVID-19, respectively. Given the ongoing vaccine rollout to healthcare personnel and residents of long-term care facilities, here we provide a preliminary assessment of real-world vaccination efficacy in 62,138 individuals from the Mayo Clinic and associated health system (Arizona, Florida, Minnesota, Wisconsin) between December 1st 2020 and February 8th 2021. Our retrospective analysis contrasts 31,069 individuals receiving at least one dose of either vaccine with 31,069 unvaccinated individuals who are propensity-matched based on demographics, location (zip code), and number of prior SARS-CoV-2 PCR tests. 8,041 individuals received two doses of a COVID-19 vaccine and were at risk for infection at least 36 days after their first dose. Administration of two COVID-19 vaccine doses was 88.7% effective in preventing SARS-CoV-2 infection (95% CI: 68.4-97.1%) with onset at least 36 days after the first dose. Furthermore, vaccinated patients who were subsequently diagnosed with COVID-19 had significantly lower 14-day hospital admission rates than propensity-matched unvaccinated COVID-19 patients (3.7% vs. 9.2%; Relative Risk: 0.4; p-value: 0.007). Building upon the previous randomized trials of these vaccines, this study demonstrates their real-world effectiveness in reducing the rates of SARS-CoV-2 infection and COVID-19 severity among individuals at highest risk for infection.

Mapping each pre-existing conditions 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 1,903 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 (23% of 383 complications) followed by cardiac arrhythmia (12% of 383 complications). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia and anemia. Furthermore, novel associations between cancer (risk ratio: 3, p=0.02) or immunosuppression (risk ratio: 4.3, p=0.04) with early-onset heart failure have also been identified. Onset of new complications after 30 days is rare and most commonly involves pleural effusion (31-60 days: 24% of 45 patients, 61-90 days: 25% of 36 patients). 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.

Healthcare disparities among anticoagulation therapies for severe COVID-19 patients in the multi-site VIRUS registry

COVID-19 patients are at an increased risk of thrombosis and various anticoagulants are being used in patient management without an established standard-of-care. Here, we analyze hospitalized and ICU patient outcomes from the Viral Infection and Respiratory illness Universal Study (VIRUS) registry. We find that severe COVID patients administered unfractionated heparin but not enoxaparin have a higher mortality-rate (311 deceased patients out of 760 total patients = 41%) compared to patients administered enoxaparin but not unfractionated heparin (214 deceased patients out of 1,432 total patients = 15%), presenting a risk ratio of 2.74 (95% C.I.: [2.35, 3.18]; p-value: 1.4e-41). This difference persists even after balancing on a number of covariates including: demographics, comorbidities, admission diagnoses, and method of oxygenation, with an amplified mortality rate of 39% (215 of 555) for unfractionated heparin vs. 23% (119 of 522) for enoxaparin, presenting a risk ratio of 1.70 (95% C.I.: [1.40, 2.05]; p-value: 2.5e-7). In these balanced cohorts, a number of complications occurred at an elevated rate for patients administered unfractionated heparin compared to those administered enoxaparin, including acute kidney injury (227 of 642 [35%] vs. 156 of 608 [26%] respectively, adjusted p-value 0.0019), acute cardiac injury (40 of 642 [6.2%] vs. 15 of 608 [2.5%] respectively, adjusted p-value 0.01), septic shock (118 of 642 [18%] vs. 73 of 608 [12%] respectively, adjusted p-value 0.01), and anemia (81 of 642 [13%] vs. 46 of 608 [7.6%] respectively, adjusted p-value 0.02). Furthermore, a higher percentage of Black/African American COVID patients (375 of 1,203 [31%]) were noted to receive unfractionated heparin compared to White/Caucasian COVID patients (595 of 2,488 [24%]), for a risk ratio of 1.3 (95% C.I.: [1.17, 1.45], adjusted p-value: 1.6e-5). After balancing upon available clinical covariates, this difference in anticoagulant use remained statistically significant (272 of 959 [28%] for Black/African American vs. 213 of 959 [22%] for White/Caucasian, adjusted p-value: 0.01, relative risk: 1.28, 95% C.I.: [1.09, 1.49]). While retrospective studies cannot suggest any causality, these findings motivate the need for follow-up prospective research in order to elucidate potential socioeconomic, racial, or other disparities underlying the use of anticoagulants to treat severe COVID patients.

Pre-existing conditions are associated with long-COVID patients hospitalization, despite confirmed clearance of SARS-CoV-2 virus

The current diagnostic gold-standard for SARS-CoV-2 clearance from infected patients is two consecutive negative PCR test results. However, there are anecdotal reports of hospitalization from protracted COVID complications despite such confirmed viral clearance, presenting a clinical conundrum. We conducted a retrospective analysis of 266 COVID patients to compare those that were admitted/re-admitted post-viral clearance (hospitalized post-clearance cohort, n=93) with those that were hospitalized pre-clearance but were not re-admitted post-viral clearance (non-hospitalized post-clearance cohort, n=173). In order to differentiate these two cohorts, we used neural network models for the augmented curation of comorbidities and complications with positive sentiment in the EHR physician notes. In the year preceding COVID onset, acute kidney injury (n=15 (16.1%), p-value: 0.03), anemia (n=20 (21.5%), p-value: 0.02), and cardiac arrhythmia (n=21 (22.6%), p-value: 0.05) were significantly enriched in the physician notes of the hospitalized post-clearance cohort. This study highlights that these specific pre-existing conditions are associated with amplified hospitalization risk in COVID patients, despite their successful SARS-CoV-2 viral clearance. Our finding that pre-COVID anemia amplifies risk of post-COVID hospitalization is particularly concerning given the high prevalence and endemic nature of anemia in many low- and middle-income countries (per the World Bank definition; e.g. India, Brazil), which are unfortunately also seeing high rates of SARS-CoV-2 infection and COVID-induced mortality. This study motivates follow-up prospective research into the specific risk factors we have identified that appear to predispose some patients towards the after effects of COVID-19. Article summary - Strengths and limitations of this studyO_LIThis is the first study at a major healthcare center analyzing risk factors for post-viral clearance hospitalization of COVID-19 patients. C_LIO_LIThis analysis uses augmented curation methods to identify complications and comorbidities from the physician notes, rather than relying upon ICD codes. C_LIO_LIThe statistical analysis identifies specific comorbidities in the year preceding PCR diagnosis of SARS-CoV-2 which are associated with increased rates of post-viral clearance hospitalization. C_LIO_LIThe dataset used for this study is limited to a single healthcare system, so the underlying clinical characteristics of the study population are biased to reflect the clinical characteristics of individuals that receive medical treatment in certain regions of the United States (Arizona, Florida, Minnesota). C_LIO_LIIn this study, we use the first of two consecutive negative PCR tests to estimate the viral clearance date for each patient, however the true viral clearance date for each patient is unknown. C_LI

Enoxaparin is associated with lower rates of thrombosis, kidney injury, and mortality than Unfractionated Heparin in hospitalized COVID patients

Although anticoagulants such as unfractionated heparin and low molecular weight heparin (LMWH, e.g. enoxaparin) are both being used for therapeutic mitigation of COVID associated coagulopathy (CAC), differences in their clinical outcomes remain to be investigated. Here, we employ automated neural networks supplemented with expert curation ( augmented curation) for retrospectively analyzing the complete electronic health records (EHRs) of 671 hospitalized COVID-19 patients administered either enoxaparin or unfractionated heparin, but not both. We find that COVID-19 patients administered unfractionated heparin but not enoxaparin have higher rates of mortality (risk ratio: 2.6; 95% C.I.: [1.2-5.4]; p-value: 0.02; BH adjusted p-value: 0.09), thrombotic events (risk ratio: 5.7, 95% C.I.: [2.1, 33.9], p-value: 0.024), acute kidney injury (risk ratio: 5.5; 95% C.I.: [1.2-17.7]; p-value: 0.02; BH adjusted p-value: 0.10), and bacterial pneumonia (risk ratio undefined; 95% C.I.: [1.0, 292]; p-value:0.02; BH adjusted p-value:0.10), compared to patients administered enoxaparin but not unfractionated heparin. Notably, even after controlling for potential confounding factors such as demographics, comorbidities, admission diagnosis, initial ICU status, and initial level of oxygen support, the above differences between the enoxaparin and unfractionated heparin patient cohorts remain statistically significant. This study emphasizes the need for mechanistically investigating differential modulation of the COVID-associated coagulation cascades by enoxaparin versus unfractionated heparin.

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

Multiple 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, Hemophilus 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). These findings suggest that additional pre-clinical and clinical studies are warranted to assess the protective effects of existing non-COVID-19 vaccines and explore underlying immunologic mechanisms. We note that the findings in this study are preliminary and are subject to change as more data becomes available and as further analysis is conducted.

Longitudinal laboratory testing tied to PCR diagnostics in COVID-19 patients reveals temporal evolution of distinctive coagulopathy signatures

Temporal inference from laboratory testing results and their triangulation with clinical outcomes as described in the associated unstructured text from the providers notes in the Electronic Health Record (EHR) is integral to advancing precision medicine. Here, we studied 181 COVIDpos and 7,775 COVIDneg patients subjected to 1.3 million laboratory tests across 194 assays during a two-month observation period centered around their SARS-CoV-2 PCR testing dates. We found that compared to COVIDneg at the time of clinical presentation and diagnostic testing, COVIDpos patients tended to have higher plasma fibrinogen levels and similarly low platelet counts, with approximately 25% of patients in both cohorts showing outright thrombocytopenia. However, these measures show opposite longitudinal trends as the infection evolves, with declining fibrinogen and increasing platelet counts to levels that are lower and higher compared to the COVIDneg cohort, respectively. Our EHR augmented curation efforts suggest a minority of patients develop thromboembolic events after the PCR testing date, including rare cases with disseminated intravascular coagulopathy (DIC), with most patients lacking the platelet reductions typically observed in consumptive coagulopathies. These temporal trends present, for the first time, fine-grained resolution of COVID-19 associated coagulopathy (CAC), via a digital framework that synthesizes longitudinal lab measurements with structured medication data and neural network-powered extraction of outcomes from the unstructured EHR. This study demonstrates how a precision medicine platform can help contextualize each patients specific coagulation profile over time, towards the goal of informing better personalization of thromboprophylaxis regimen.