Understanding temporal dynamics of COVID-19 patient symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVIDpos; n=2,317) versus COVID-19-negative (COVIDneg; n=74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVIDpos over COVIDneg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVIDpos patients during the week prior to PCR testing, and along with anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.

IMPORTANCEContinuous 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 largescale 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 trialreported 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.

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.

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.

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.