Covid-19 Bivalent Booster Effectiveness in People with and without Immune Dysfunction

Background: Data on the effectiveness of the bivalent booster vaccine against COVID-19 breakthrough infection and severe outcomes is limited. Method(s): Using patient-level data from 54 sites in the U.S. National COVID Cohort Collaborative (N3C), we estimated bivalent booster effectiveness against breakthrough infection and outcomes between 09/01/2022 (bivalent vaccine approval date) to 12/15/2022 (most recent data release of N3C) among patients completed 2+ doses of mRNA vaccine. Bivalent booster effectiveness was evaluated among all patients and patients with and without immunosuppressed/compromised conditions (ISC;HIV infection, solid organ/ bone marrow transplant, autoimmune diseases, and cancer). We used logistic regression models to compare the odds of breakthrough infection (COVID-19 diagnosis after the last dose of vaccine) and outcomes (hospitalization, ventilation/ECMO use, or death <=28 days after infection) in the bivalent boosted vs. non-bivalent boosted groups. Models controlled for demographics, comorbidities, geographic region, prior SARS-CoV-2 infection, months since the last dose of non-bivalent vaccine, and prior non-bivalent booster. Result(s): By 12/15/2022, 2,414,904 patients had received 2+ doses of mRNA vaccination, 75,873 of them had received a bivalent booster vaccine, and 24,046 of them had a breakthrough infection. At baseline, the median age was 52 (IQR 36-67) years, 40% male, 63% white, 10% Black, 12% Latinx, 3.5% Asian American/Pacific Islander, and 14% were patients with ISC. Patients received a bivalent booster were more likely to be female and had comorbidities. Bivalent booster was significantly associated with reduced odds of breakthrough infection and hospitalization (Figure). The adjusted odds ratios comparing bivalent vs. non-bivalent group were 0.28 (95% CI 0.25, 0.32) for all patients and 0.33 (95% CI: 0.26, 0.41) for patients with ISC. Compared to the nonbivalent group, the bivalent group had a lower incidence of COVID-19-related hospitalization (151 vs. 41 per 100,000 persons), invasive ventilation/ECMO use (7.5 vs. 1.3 per 100,000 persons), or death (11 vs. 1.3 per 100,000 persons) in all patients during the study period;the incidence of severe outcomes after bivalent boosting was similar among patients with and without ISC. Conclusion(s): A bivalent booster vaccine was highly effective against COVID-19 breakthrough infection and severe outcomes among patients received 2+ doses of mRNA vaccine and offered similar protection in patients with and without ISC. (Figure Presented).

Hormone Replacement Therapy and COVID-19 Outcomes in Kidney Transplant Recipients Compared With the General Population

Background: In the non-immunosuppressed (non-IS) population, female sex is protective against adverse COVID-19 (C19) outcomes, possibly due to estrogenrelated immunity. Sex-based risk is attenuated in IS kidney transplant recipients (KTRs). Exogenous estrogen is associated with reduced C19 mortality in non-IS postmenopausal females. Here, we aimed to study the impact of estrogen or testosterone hormone replacement therapy (HRT) on C19 outcomes in KTRs compared to the general population. Method(s): We studied adult (>45 yrs) KTRs from across the US with C19 from 05-01-20 to 05-12-22, using EHR data from the National COVID Cohort Collaborative. Female and male patients were classified as no HRT, or HRT use in the last 6 months (exogenous systemic estrogens for females;testosterone for males). Using MV cox proportional hazards models and logistic regression, we determined the risk of developing a major adverse renal or cardiac event (MARCE), mortality, and other 90-day post-C19 outcomes. We repeated this analysis in a non-IS control group for comparison. Result(s): Over the study period, 11,498 KTRs and >1.9M non-IS patients were diagnosed with C19. In non-IS, relative to no HRT use, HRT use in the last 6 months was associated with significantly lower risk of MARCE (Hazard Ratio [HR] 0.54, 95% Confidence Interval [CI] 0.51-0.59, for females;0.63, 0.56-0.70, for males), mortality (HR 0.45, CI 0.40-0.51, for females;0.55, 0.45-0.66, for males), and all secondary events for males and females (Figure 1). In KTRs, HRT was not associated with any post-C19 outcome in either males or females;there was a trend towards lower risk in males on HRT vs not on HRT, for most outcomes. Conclusion(s): HRT was protective against adverse C19 outcomes in older non-IS males and females, but not in KTRs. The modifying effects of IS on the benefits of HRT requires further investigation.

Role of Vaccination in the COVID-19 Nationwide Cohort (N3C) of Solid Organ Transplant Recipients

Purpose: Immunosuppressed solid organ transplant (SOT) patients have been repeatedly challenged in the COVID-19 pandemic with significant morbidities and mortality following infection and a suppressed immune response to vaccination. The aim of this study was to assess the impact on COVID-19 morbidity and mortality in the presence and absence of vaccination. Method(s): We studied adult (>18 years) patients from across the United States identified using the National COVID Cohort Collaborative (N3C) Enclave from Dec 10, 2020-Oct 12, 2021. Using multivariable logistic regression, we determined the odds of developing COVID-19 infection in the 6 months after full vaccination (defined as a breakthrough (BT) infection) in SOT recipients relative to nonimmunosuppressed (non-IS) patients. In SOT patients with BT COVID-19 infection, we then used multivariable logistic regression to determine the association of full and partial vaccination status with major adverse cardiac events, mortality, and additional secondary outcomes in the 90 days following COVID-19 diagnosis relative to unvaccinated/unconfirmed vaccination status SOT recipients). Result(s): Over the study period, 16,075 SOT patients were diagnosed with COVID-19 (515 were partially vaccinated, and 1,868 were fully vaccinated). Relative to non- IS, SOT was associated with an increased odds of BT COVID-19 infection in the 6 months post vaccine, that varied by organ type (i.e. OR 1.97, 95% CI 1.75-2.25 for kidney;OR 2.30, 95% CI 1.70-3.06 for lung), Table 1. In SOT patients who experienced BT COVID-19, full vaccination was associated with a small reduction in adverse outcomes relative to unvaccinated/unconfirmed vaccination status (OR 0.91, 95% CI 0.89-0.93 for MARCE;OR 0.92, 95% CI 0.90-0.93 for death;OR 0.90, 95% CI 0.88-0.92 for hospitalization), Table 2. Conclusion(s): SOT patients are at a ~2-fold increased odds of BT COVID-19 infection after vaccination compared with non-IS patients. Vaccination in SOT patients, regardless of product, has a small but significant reduction in the risk of adverse outcomes after a diagnosis of COVID-19, however SOT recipients remain at high risk and should continue to use caution even after vaccination. (Table Presented).

Association of Vitamin D Prescribing and Clinical Outcomes in Adults Hospitalized with COVID-19.

It is unclear whether vitamin D benefits inpatients with COVID-19. Objective: To examine the relationship between vitamin D and COVID-19 outcomes. Design: Cohort study. Setting: National COVID Cohort Collaborative (N3C) database. Patients: 158,835 patients with confirmed COVID-19 and a sub-cohort with severe disease (n = 81,381) hospitalized between 1 January 2020 and 31 July 2021. Methods: We identified vitamin D prescribing using codes for vitamin D and its derivatives. We created a sub-cohort defined as having severe disease as those who required mechanical ventilation or extracorporeal membrane oxygenation (ECMO), had hospitalization >5 days, or hospitalization ending in death or hospice. Using logistic regression, we adjusted for age, sex, race, BMI, Charlson Comorbidity Index, and urban/rural residence, time period, and study site. Outcomes of interest were death or transfer to hospice, longer length of stay, and mechanical ventilation/ECMO. Results: Patients treated with vitamin D were older, had more comorbidities, and higher BMI compared with patients who did not receive vitamin D. Vitamin D treatment was associated with an increased odds of death or referral for hospice (adjusted odds ratio (AOR) 1.10: 95% CI 1.05-1.14), hospital stay >5 days (AOR 1.78: 95% CI 1.74-1.83), and increased odds of mechanical ventilation/ECMO (AOR 1.49: 95% CI 1.44-1.55). In the sub-cohort of severe COVID-19, vitamin D decreased the odds of death or hospice (AOR 0.90, 95% CI 0.86-0.94), but increased the odds of hospital stay longer >5 days (AOR 2.03, 95% CI 1.87-2.21) and mechanical ventilation/ECMO (AOR 1.16, 95% CI 1.12-1.21). Limitations: Our findings could reflect more aggressive treatment due to higher severity. Conclusion: Vitamin D treatment was associated with greater odds of extended hospitalization, mechanical ventilation/ECMO, and death or hospice referral.

COVID-19 BOOSTER VACCINE EFFECTIVENESS in PEOPLE with and WITHOUT IMMUNE DYSFUNCTION

Background: Real-world evidence on effectiveness of booster or additional doses of COVID-19 vaccine is limited. Methods: Using patient-level data from 50 sites in the U.S. National COVID Cohort Collaborative (N3C), we estimated COVID-19 booster vaccine effectiveness compared to full vaccination alone (completed 2 doses mRNA or 1 dose Janssen vaccine). At each month following full vaccination, we created comparable cohorts of patients with boosters propensity-score matched to those without boosters by age, sex, race/ethnicity, comorbidities, geographic region, prior COVID-19 infection, and calendar month of full vaccination. Booster efficacy was evaluated among patients with and without immunosuppressed/compromised conditions (ISC;HIV infection, solid organ or bone marrow transplant, autoimmune diseases, and cancer). We used Cox regression models to estimate hazards of breakthrough infection (COVID-19 diagnosis after last dose of vaccine) and logistic regression models to compare the risk of death ≤45 days after a breakthrough infection in the boosted vs. matched non-boosted groups. Results: By 11/18/2021, 656390 patients had received full vaccination, and 125409 fully vaccinated had received an additional booster (median time from last vaccine to booster dose: 7.4 months, IQR:6.6, 8.2). At completion of full vaccination, median age was 50 (IQR 33-64) years, 43% male, 50% white, 11% Black, 18% Latinx, 4.8% Asian American/Pacific Islander, and 20% had ISC. People receiving a booster were more likely to be older, male, white, and have ISC. Booster vaccine was significantly associated with a reduced hazard of breakthrough infection (Table). Booster efficacy ranged from 46% (booster receipt 1-4 months after full vaccination) to 83% (receipt 7 months after full vaccination) in people without ISC. Vaccine efficacy was lower, ranging from 43%-65%, in ISC patients (Table). Compared to fully vaccinated patients without booster receipt, patients with booster had an 83% (OR: 0.17, 95% CI: 0.11, 0.28) reduced risk of COVID-19 related death, independent of demographics, geographic region, comorbidities, ISC, prior COVID-19 infection, and time of full vaccination. Conclusion: A booster dose of COVID-19 vaccine has high effectiveness in reducing breakthrough infection risk among all fully vaccinated individuals, though only with moderate effectiveness among ISC patients. Nonetheless, booster vaccination significantly reduced risk for COVID-19 related death regardless of ISC status.

THE IMPACT of COVID-19 TREATMENTS on PATIENT OUTCOMES: A PROBABILISTIC VIEW

Background: The World Health Organization (WHO) ordinal scale (OS) is used to evaluate participant outcomes in clinical trials. We modified the WHO OS to enable assessment of patient outcomes associated with various treatment agents using the National COVID Cohort Collaborative (N3C), a national database containing electronic Health Record (EHR) data from > 2.7 million persons with a COVID-19 diagnosis from > 55 U.S. sites. Methods: Modified OS severity scores (Table 1) were assigned in the first through fourth weeks following COVID-19 diagnosis for a sample of patients in N3C. To adjust for disease severity at patient hospitalization, we developed separate models to examine OS levels of 3, 5, 7, and 9. Elastic net penalized multinomial logistic regression was used to simultaneously identify risk factors and predict the probability of each level of the ordinal scale at week 4. We studied groups of anticoagulants (AC), steroids, antibiotics, antiviral agents (AA), monoclonal antibodies (MA), and a miscellaneous group that included all other treatments. Other factors considered were presence of comorbid conditions using the Charlson Comorbidity Index (CCI), ethnicity, age, gender, and time of diagnosis (by quarter). Results: We included 1,489,191 COVID-19 (161,385 outpatients were excluded) patients. Patient characteristics and treatment approaches applied to each OS level were analyzed (Table 1). For hospitalized patients with a Week 1 OS score of 3,5,7, or 9, we found that increased CCI values are associated with higher probabilities of a worsened OS score at Week 4. Given that MAs are a standard treatment for patients at OS levels 3 and 5, and that steroids are typically used at OS 7 and 9, we studied treatment combinations related to MA and steroids given during Week 1. Improved outcomes by Week 4 were demonstrated with AA+MA for OS 3 and for AC+MA for OS 5 (Table 1). Patients at OS 7 in Week 1 had improved Week 4 outcomes with steroids alone while OS 7 patients with CCI>10 had better outcomes with steroids+AC. OS 9 patients treated with steroids+MA had better outcomes compared with those not given that combination. Conclusion: Our analyses identify relationships between COVID-19 serverity, specific treatments and outcomes at 4 weeks after diagnosis. Use of MA at lower levels of severity, and steroids at higher severity levels were associated with survival to hospital discharge.

Evaluation of Rural-Urban Differences in Hospitalization and Mortality Rates for US COVID-19 Patients in the United States

Background. Rural communities are among the most vulnerable and resourcescarce populations in the United States. Rural data is rarely centralized, precluding comparability across regions, and no significant studies have studied this population at scale. The purpose of this study is to present findings from the National COVID Cohort Collaborative (N3C) to provide insight into future research and highlight the urgent need to address health disparities in rural populations. N3C Patient Distribution This figure shows the geospatial distribution of the N3C COVID-19 positive population. N3C contains data from 55 data contributors from across the United States, 40 of whom include sufficient location information to map by ZIP Code centroid spatially. Of those sites, we selected 27 whose data met our minimum robustness qualifications for inclusion in our study. This bubble map is to scale with larger bubbles representing more patients. A. shows all N3C patients. B. shows only urban N3C distribution. C. shows the urban-adjacent rural patient distribution. D. shows the nonurban-adjacent rural patient distribution, representing the most isolated patients in N3C. Methods. This retrospective cohort of 573,018 patients from 27 hospital systems presenting with COVID-19 between January 2020 and March 2021, of whom 117,897 were admitted (see Data Analysis Plan diagram for inclusion/exclusion criteria), analyzes outcomes and 30-day survival for the hospitalized population by the degree of rurality. Multivariate Cox regression analysis and mixed-effects models were used to estimate the association between rurality, hospitalization, and all-cause mortality, controlling for major risk factors associated with rural-urban health discrepancies and differences in health system outcomes. The difference in distribution by rurality is described as well as supplemented by population-level statistics to confirm representativeness. Data Analysis Plan This data analysis plan includes an overview of study inclusion and exclusion criteria, the matrix for data robustness to determine potential sites to include, and our covariate selection, model building, and residual testing strategy. Results. This study demonstrates a significant difference between hospital admissions and outcomes in urban versus urban-adjacent rural (UAR) and nonurban-adjacent rural (NAR) lines. Hospital admissions for UAR (OR 1.41, p< 0.001, 95% CI: 1.37 - 1.45) and NAR (OR 1.42, p< 0.001, 95% CI: 1.35 - 1.50) were significantly higher than their urban counterparts. Similar distributions were present for all-cause mortality for UAR (OR 1.39, p< 0.001, 95% CI: 1.30 - 1.49) and NAR (OR 1.38, p< 0.001, 95% CI: 1.22 - 1.55) compared to urban populations. These associations persisted despite adjustments for significant differences in BMI, Charlson Comorbidity index Score, gender, age, and the quarter of diagnosis for COVID-19. Baseline Characteristics Hospitalized COVID-19 Positive Population by Rurality Category, January 2020 - March 2021 Survival Curves in Hospitalized Patients Over 30 Days from Day of Admission This figure shows a survival plot of COVID-19 positive hospitalized patients in N3C by rural category (A), Charlson Comorbidity Index (B), Quarter of Diagnosis (C), and Age Group (D) from hospital admission through day 30. Events were censored at day 30 based on the incidence of death or transfer to hospice care. These four factors had the highest predictive power of the covariates evaluated in this study. Unadjusted and Adjusted Odds Ratios for Hospitalization and All-Cause Mortality by Rural Category, January 2020 - March 2021 This figure shows the adjusted and unadjusted odds ratios for being hospitalized or dying after hospitalization for the COVID-19 positive population in N3C. Risk is similar between adjusted and unadjusted models, suggesting a real impact of rurality on all-cause mortality. A shows the unadjusted odds ratios for admission to the hospital after a positive COVID-19 diagnosis for all N3C patients. B shows the unadjusted odds ratios for all-cause mortalit at any point after hospitalization for COVID-19 positive patients. C shows the adjusted odds ratios for being admitted to the hospital after a positive COVID-19 diagnosis for all N3C patients. D shows the adjusted odds ratios for all-cause mortality for all-cause mortality at any point after hospitalization for COVID-19 positive patients. Adjusted models include adjustments for gender, race, ethnicity, BMI, age, Charlson Comorbidity Index (CCI) composite score, rurality, and quarter of diagnosis. The data provider is included as a random effect in all models. Conclusion. In N3C, we found that hospitalizations and all-cause mortality were greater among rural populations when compared to urban populations after adjustment for several factors, including age and co-morbidities. This study also identified key demographic and clinical disparities among rural patients that require further investigation.

An Ordinal Scale Assessing SARS-CoV-2 Infected Patient Outcomes Using Electronic Health Records

Background. A major challenge to identifying effective treatments for COVID-19 has been the conflicting results offered by small, often underpowered clinical trials. The World Health Organization (WHO) Ordinal Scale (OS) has been used to measure clinical improvement among clinical trial participants and has the benefit of measuring effect across the spectrum of clinical illness. We modified the WHO OS to enable assessment of COVID-19 patient outcomes using electronic health record (EHR) data. Methods. Employing the National COVID Cohort Collaborative (N3C) database of EHR data from 50 sites in the United States, we assessed patient outcomes, April 1,2020 to March 31, 2021, among those with a SARS-CoV-2 diagnosis, using the following modification of the WHO OS: 1=Outpatient, 3=Hospitalized, 5=Required Oxygen (any), 7=Mechanical Ventilation, 9=Organ Support (pressors;ECMO), 11=Death. OS is defined over 4 weeks beginning at first diagnosis and recalculated each week using the patient's maximum OS value in the corresponding 7-day period. Modified OS distributions were compared across time using a Pearson Chi-Squared test. Results. The study sample included 1,446,831 patients, 54.7% women, 14.7% Black, 14.6% Hispanic/Latinx. Pearson Chi-Sq P< 0.0001 was obtained comparing the distribution of 2nd Quarter 2020 OS with the distribution of later time points for Week 4. The study sample included 1,446,831 patients, 54.7% women, 14.7% Black, 14.6% Hispanic/Latinx. Pearson Chi-Sq P< 0.0001 was obtained comparing the distribution of 2nd Quarter 2020 OS with the distribution of later time points for Week 4. Conclusion. All Week 4 OS distributions significantly improved from the initial period (April-June 2020) compared with subsequent months, suggesting improved management. Further work is needed to determine which elements of care are driving the improved outcomes. Time series analyses must be included when assessing impact of therapeutic modalities across the COVID pandemic time frame.

COVID-19 in solid organ transplantation (SOT): Results of the national covid cohort collaborative (N3C)

Purpose: SARS-CoV-2 infection has resulted in significant mortality in solid organ transplant (SOT) recipients based on reports from single centers or voluntary registries. The N3C Enclave was developed to facilitate analysis of patient-level data across the US for multiple conditions, consisting of weekly electronic medical record (EMR) data extraction and transmission into a federally secured platform. Herein is our report of the largest cohort of US COVID-19 positive SOT patients to date. Methods: We identified a cohort of SOT recipients who received a positive or negative COVID-19 test (COVID+ and COVID-, respectively) between 01/01/2020 and 11/23/2020. In COVID+ SOT, we evaluated outcomes including requirement for hospitalization, major adverse cardiac events (MACE), and graft rejection and failure occurring until study end. Significant differences between COVID+ and COVID- patients were identified using t-test and chi-square testing, as indicated. Results: 34 sites account for 2.15 million patients in the Enclave, of whom 292,226 are COVID+. We identified 19,031 SOT patients, of whom 2,183 were COVID+ (11.5%) with a median follow-up time of 119 days. Demographics are shown in Figure 1. Compared to COVID- SOT patients, COVID+ SOT patients were more likely to have a kidney transplant and be non-white or Hispanic. Hypertension, diabetes, coronary artery disease and chronic kidney disease were common comorbidities in all SOT, but significantly more common in those who were COVID+. Of COVID+ SOT, 51.8% required hospital admission for a median of 1 days (range 0-114). Following COVID diagnosis, 13.7% of COVID+ SOT patients experienced MACE, 3.8% had graft rejection and 3.4% had graft loss over the study period. Conclusions: In the largest US cohort of COVID+ SOT recipients to date, we identify patient factors associated with the diagnosis of COVID-19 and outcomes following infection including a relatively high incidence of MACE. This is an evolving dataset and provides novel opportunities for analyses of COVID in SOT recipients on a granular level.