Poor COVID-19 Outcomes Research Articles

Long-Term Mortality Following SARS-CoV-2 Infection in Rural Versus Urban Dwellers With Autoimmune or Inflammatory Rheumatic Disease: A Retrospective Cohort Analysis From the National COVID Cohort Collaborative.

Autoimmune or inflammatory rheumatic diseases (AIRDs) increase the risk for poor COVID-19 outcomes. Although rurality is associated with higher post-COVID-19 mortality in the general population, whether rurality elevates this risk among people with AIRD is unknown. We assessed associations between rurality and post-COVID-19 all-cause mortality, up to two years post infection, among people with AIRD using a large nationally sampled US cohort. This retrospective study used the National COVID Cohort Collaborative, a medical records repository containing COVID-19 patient data. We included adults with two or more AIRD diagnostic codes and a COVID-19 diagnosis documented between April 2020 and March 2023. Rural residency was categorized using patient residential zip codes. We adjusted for AIRD medications and glucocorticoid prescription, age, sex, race and ethnicity, tobacco or substance use, comorbid burden, and SARS-CoV-2 variant-dominant periods. Multivariable Cox proportional hazards with inverse probability treatment weighting assessed associations between rurality and two-year all-cause mortality. Among the 86,467 SARS-CoV-2-infected persons with AIRD, we observed a higher risk for two-year post-COVID-19 mortality in rural versus urban dwellers. Rural-residing persons with AIRD had higher two-year all-cause mortality risk (adjusted hazard ratio 1.24, 95% confidence interval 1.19-1.29). Glucocorticoid, immunosuppressive, and rituximab prescriptions were associated with a higher risk for two-year post-COVID-19 mortality, whereas risk with nonbiologic or biologic disease-modifying antirheumatic drugs was lower. Rural residence in people with AIRD was independently associated with higher two-year post-COVID-19 mortality in a large US cohort after adjusting for background risk factors. Policymakers and health care providers should consider these findings when designing interventions to improve outcomes in people with AIRD following SARS-CoV-2 infection, especially among high-risk rural residents.

COVID-19 Outcomes among People Living with HIV in Colorado.

It is known that people who are immunocompromised or have a comorbidity are at an increased risk for acquiring COVID-19, having a longer duration of COVID-19 symptoms, and a greater likelihood of severe outcomes, including people living with HIV (PLHIV) (Centers for Disease Control and Prevention. (n.d.). Basics of covid-19. Centers for Disease Control and Prevention. Retrieved October 31. 2022, from https://www.cdc.gov/coronavirus/2019-ncov/your-health/about-covid-19/basics-covid-19.html ). However, treatment for PLHIV can greatly reduce the amount of HIV in a person's blood, known as viral suppression. This study compared the outcome of COVID-associated hospitalization among virally suppressed and unsuppressed PLHIV in Colorado. A retrospective cohort analysis was conducted including all known PLHIV in Colorado that were diagnosed with COVID-19 between March 2020 and September 2022. Relevant covariates were identified including race/ethnicity, age at time of diagnosis, region of diagnosis, and vaccination status. An initial univariate logistic regression was then built to test the statistical significance of the association between viral suppression and hospitalization. The final model included all associated covariates and crude and adjusted odds ratios were analyzed. When controlling for covariates, PLHIV who were not virally suppressed at the time of their COVID-19 diagnosis were 2.5 (OR 2.5, 95% CI 1.6-4.0) times as likely to be hospitalized at the time of their first COVID-19 diagnosis compared to those that were suppressed. These findings suggest that viral suppression among PLHIV is protective against poor COVID-19 outcomes. This study is an important first step in highlighting the importance of PLHIV being retained in care and achieving viral suppression in reducing hospitalizations due to COVID-19 in Colorado.

High Income But Poor COVID-19 Outcomes: The Contrasting Results of The Pre-COVID 19 Joint External Evaluation Assessment Tool in Measuring Countries’ Global Health Security Preparedness and Response Capacities

High Income But Poor COVID-19 Outcomes: The Contrasting Results of The Pre-COVID 19 Joint External Evaluation Assessment Tool in Measuring Countries’ Global Health Security Preparedness and Response Capacities

Short-term exposure to air pollution and hospital admission after COVID-19 in Catalonia: the COVAIR-CAT study.

A growing body of evidence has reported positive associations between long-term exposure to air pollution and poor COVID-19 outcomes. Inconsistent findings have been reported for short-term air pollution, mostly from ecological study designs. Using individual-level data, we studied the association between short-term variation in air pollutants [nitrogen dioxide (NO2), particulate matter with a diameter of <2.5 µm (PM2.5) and a diameter of <10 µm (PM10) and ozone (O3)] and hospital admission among individuals diagnosed with COVID-19. The COVAIR-CAT (Air pollution in relation to COVID-19 morbidity and mortality: a large population-based cohort study in Catalonia, Spain) cohort is a large population-based cohort in Catalonia, Spain including 240902 individuals diagnosed with COVID-19 in the primary care system from 1 March until 31 December 2020. Our outcome was hospitalization within 30 days of COVID-19 diagnosis. We used individual residential address to assign daily air-pollution exposure, estimated using machine-learning methods for spatiotemporal prediction. For each pandemic wave, we fitted Cox proportional-hazards models accounting for non-linear-distributed lagged exposure over the previous 7days. Results differed considerably by pandemic wave. During the second wave, an interquartile-range increase in cumulative weekly exposure to air pollution (lag0_7) was associated with a 12% increase (95% CI: 4% to 20%) in COVID-19 hospitalizations for NO2, 8% (95% CI: 1% to 16%) for PM2.5 and 9% (95% CI: 3% to 15%) for PM10. We observed consistent positive associations for same-day (lag0) exposure, whereas lag-specific associations beyond lag0 were generally not statistically significant. Our study suggests positive associations between NO2, PM2.5 and PM10 and hospitalization risk among individuals diagnosed with COVID-19 during the second wave. Cumulative hazard ratios were largely driven by exposure on the same day as hospitalization.

Serological responses and clinical outcomes following a three-dose primary COVID-19 vaccine schedule in kidney transplant recipients and people on dialysis.

Despite vaccination strategies, people with chronic kidney disease, particularly kidney transplant recipients (KTRs), remained at high risk of poor COVID-19 outcomes. We assessed serological responses to the three-dose COVID-19 vaccine schedule in KTRs and people on dialysis, as well as seroresponse predictors and the relationship between responses and breakthrough infection. Plasma from 30 KTRs and 17 people receiving dialysis was tested for anti-Spike receptor binding domain (RBD) IgG and neutralising antibodies (NAb) to the ancestral and Omicron BA.2 variant after Doses 2 and 3 of vaccination. After three doses, KTRs achieved lower anti-Spike RBD IgG levels (P < 0.001) and NAb titres than people receiving dialysis (P = 0.002). Seropositive cross-reactive Omicron neutralisation levels were achieved in 11/27 (40.7%) KTRs and 11/14 (78.6%) dialysis recipients. ChAdOx1/viral-vector vaccine type, higher mycophenolate dose (> 1 g per day) and lower absolute B-cell counts predicted poor serological responses in KTRs. ChAdOx-1 vaccine type and higher monocyte counts were negative predictors in dialysis recipients. Among ancestral NAb seroresponders, higher NAb levels positively correlated with higher Omicron neutralisation (R = 0.9, P < 0.001). More KTRs contracted SARS-CoV-2 infection (14/30; 47%) than dialysis recipients (5/17; 29%) and had more severe disease. Those with breakthrough infections had significantly lower median interdose incremental change in anti-Spike RBD IgG and ancestral NAb titres. Serological responses to COVID-19 vaccines in KTRs lag behind their dialysis counterparts. KTRs remained at high risk of breakthrough infection after their primary vaccination schedule underlining their need for booster doses, strict infection prevention measures and close surveillance.

Social determinants of health disparities in Staten Island compared with Manhattan, Queens, Brooklyn, and the Bronx: Contribution to COVID-19 outcomes.

Social determinants of health (SDH) negatively affectedCoronavirus disease-2019 (COVID-19) outcomes within the five boroughs of New York City. The goal of this study was to determine whether differences in social demographics within the borough of Staten Island, compared with the other four boroughs, may have contributed to poor COVID-19 outcomes in Staten Island. Data were obtained from public data sources. Social demographics obtained included age, household income, poverty status, and education level. COVID-19 infection, hospitalization, and death rates reported from Staten Island were compared with rates from Manhattan, Queens, Brooklyn, and the Bronx (February 29, 2020-October 31, 2022). Mean differences in case rates of COVID-19 were higher in Staten Island compared to all four boroughs. Mean differences in hospitalization and death rates were higher than Manhattan but similar to the other four boroughs. Within Staten Island, case rates were highest in zip codes 10306 and 10309. Hospitalization and death rates were highest in Staten Island zip code 10304. We found that the zip codes of Staten Island with poorer COVID-19 outcomes had more individuals with less than a high school degree, lower mean household income, higher proportion of households earning less than $25,000 a year, and a greater proportion of individuals using public transportation. Differences in COVID-19 infection, hospitalization, and death rates exist between the five boroughs and between the 12 zip codes within Staten Island. These differences in COVID-19 outcomes can be attributed to different SDH.

Abstract 13200: Changes in Thrombi-Inflammatory Biomarkers Associated With Therapeutic Heparin in Non-Critically Ill Patients Hospitalized With COVID-19: A Pre-Specified Secondary Analysis of the ACTIV4a and ATTACC Randomized Clinical Trial

Background: SARS-CoV-2 infection potentiates thromboinflammation contributing to poor outcomes in COVID-19. In non-critically ill patients hospitalized for COVID-19, therapeutic-dose heparin improves clinical outcomes. We hypothesized therapeutic-dose heparin impacts thromboinflammatory biomarkers in patients hospitalized for COVID-19 infection. Methods: We conducted a pre-specified secondary analysis of a multi-platform open-label, randomized trial comparing therapeutic-dose versus usual-care thromboprophylaxis-dose heparin in non-critically ill patients hospitalized for COVID-19. Inflammatory markers were analyzed using Wilcoxon rank-sum test and compared based on treatment. Ordinal logistic regression models evaluated for relative D-Dimer change (measured at baseline, day 1, day 3). Odds ratio of a 3-level ordinal outcome (death, survival with organ support, or survival without organ support through 21 days) was determined for relative change. Results: Of 1510 patients, 528 had a D-Dimer on baseline and day 1, and 432 on baseline and day 3. Median age was 60 years (IQR: 50-69) with 41% female and 66% under-represented minorities. Compared to usual-care, therapeutic-dose heparin was associated with a greater drop in D-Dimer at days 1 and 3; other biomarkers were unaffected by treatment (Table 1). D-Dimer at baseline and day 1 had an OR 0.93 (95% CI: 0.88, 0.98) whereas baseline and day 3 had an OR 0.86 (95% CI: 0.78, 0.94) of the ordinal outcome translating in a higher odds of surviving without the need for organ support (adjusted for treatment, gender, and age). Conclusion: In this randomized controlled trial therapeutic-dose heparin was associated with an early reduction in D-Dimer and clinical improvement, suggesting thromboinflammatory mechanisms whereby treatment conferred a clinical benefit. Temporal changes in D-dimer could predict treatment response or may signal need for alternative therapies.

The immune response to SARS-CoV-2 in people with HIV.

This review examines the intersection of the HIV and SARS-CoV-2 pandemics. People with HIV (PWH) are a heterogeneous group that differ in their degree of immune suppression, immune reconstitution, and viral control. While COVID-19 in those withwell-controlled HIV infection poses no greater risk than that for HIV-uninfected individuals, people with advanced HIV disease are more vulnerable to poor COVID-19 outcomes. COVID-19 vaccines are effective and well tolerated in the majority of PWH, though reduced vaccine efficacy, breakthrough infections and faster waning of vaccine effectiveness have been demonstrated in PWH. This is likely a result of suboptimal humoral and cellular immune responses after vaccination. People with advanced HIV may also experience prolonged infection that may give rise to new epidemiologically significant variants, but initiation or resumption of antiretroviral therapy (ART) can effectively clear persistent infection. COVID-19 vaccine guidelines reflect these increased risks and recommend prioritization for vaccination and additional booster doses for PWH who are moderately to severely immunocompromised. We recommend continued research and monitoring of PWH with SARS-CoV-2 infection, especially in areas with a high HIV burden.

THU333 Race Was Not A Predictor Of Poor Outcomes From COVID-19 At University Of Chicago Medicine Hospital

Abstract Disclosure: A. Rashied: None. J. Cursio: None. E.C. Hanlon: None. S. Pannain: None. University of Chicago Medicine (UCM) is a large, 800 bed, urban hospital located on the south side of Chicago that cares for a substantial number of African-American (AA) patients. The COVID-19 pandemic has impacted health drastically, especially for minorities (including AAs) and those with comorbid conditions. We examined COVID outcomes in our UCM patient population, including patterns by race, other demographic information (age, sex), and comorbidities, and the relationship with deaths, intensive care unit (ICU), and mechanical ventilator use. From the period March 2020 to February 2021, 61.6% (11,071/17,945) patients tested for COVID-19 at UCM were positive, and 52.8% (5,850/11,071) of these were hospitalized for further care. Of these hospitalized patients 3,171 were AA and 2,679 were all other races. AA had a higher percentage of patients who were female (62% vs 54%, p&amp;lt;0.0001), were older (49 vs 43 years, p&amp;lt;0.0001), had longer hospital stays (13.5 vs 13.0 days, p&amp;lt;0.0001), were admitted to the ICU (9% vs 4%, p&amp;lt;0.0001), and died (5% vs 2%, p&amp;lt;0.0001) compared to non-AA patients. In addition, the rates of comorbid conditions were higher for AAs compared to non-AAs for hypertension (52% vs 32%, p&amp;lt;0.0001), heart disease (15% vs 9%, p&amp;lt;0.0001), diabetes (36% vs 22%, p&amp;lt;0.0001), kidney disease (21% vs 8%, p&amp;lt;0.0001), and obesity (53% vs 40%, p&amp;lt;0.0001). To explore the relationship of race and death among patients hospitalized with COVID-19, a predictive model for death was estimated including age, race, gender, hospital stay in days, ICU length of stay, and indicators for obesity, heart disease, kidney disease, hypertension, and diabetes. The model shows that AA adults have a higher odds ratio (OR=1.08, p=0.71) for death than non-AA adults, however the p-value was insignificant. Instead, significant predictors of death included age (OR=1.058, p&amp;lt;0.0001) and kidney disease (OR=2.108, p=0.0002). Neither diabetes nor obesity were significant predictors of death in our cohort. Race was also not a predictor of mechanical ventilation or ICU status. However, obesity, diabetes and kidney disease were all significant predictors of requiring ventilation (all p&amp;lt;0.05). Moreover, age (OR=1.013, p=0.001), female gender (OR=0.687, p=0.002), kidney disease (OR=2.431, p&amp;lt;0.0001), and diabetes (OR=2.224, p&amp;lt;0.0001) were significant predictors of ICU admission. The model for death, ventilator, and ICU status for patients with COVID-19 at UCM show increased risks for AA versus non-AAs, however the odds ratios were insignificant. Instead, comorbidities like kidney disease were a significant predicator of death, as were obesity and diabetes for COVID-19 related ventilation and ICU admission. Thus, in our patient population that includes a significant number of AA adults, race was not a predictor of poor COVID-19 outcomes, but kidney disease, obesity, and diabetes were – irrespective of race. Presentation: Thursday, June 15, 2023

Elevated Level of Circulating but Not Urine S100A8/A9 Identifies Poor COVID-19 Outcomes.

The alarmin calprotectin (S100A8/A9) is thought to drive a cytokine storm, a hallmark of severe COVID-19. Recent studies report circulating S100A8/A9 levels can distinguish COVID-19 severity but have only been conducted in non-U.S. cohorts and mainly focus on serum S100A8/A9 levels. Thus, we quantified S100A8/A9 in serum and urine samples from a hospital cohort in St. Louis, Missouri, to expand the understanding of S100A8/A9 as a prognostic biomarker for COVID-19. Elevated S100A8/A9 serum levels were observed in ICU patients (n = 49, p = 0.0370) and patients with fatal cases of COVID-19 (n = 76, p = 0.0018). We observed no correlation in the S100A8/A9 levels in matched serum and urine samples. Our results support the association of serum S100A8/A9 levels with COVID-19 severity and suggest that further investigation of urine S100A8/A9 as a COVID-19 biomarker is not warranted.

Identification of early predictors of clinical outcomes of COVID-19 outbreak in an Italian single center using a machine-learning approach.

SARS-CoV-2 disease (COVID-19) has become a pandemic disease, determining a public health emergency. The use of artificial intelligence in identifying easily available biomarkers capable of predicting the risk for severe disease may be helpful in guiding clinical decisions. The aim of the study was to investigate the ability of interleukin (IL)-6, troponin I, and D-dimer to identify patients with COVID-19 at risk for intensive care unit (ICU)-admission and death by using a machine-learning predictive model. Data on demographic characteristics, underlying comorbidities, symptoms, physical and radiological findings, and laboratory tests have been retrospectively collected from electronic medical records of patients admitted to Policlinico A. Gemelli Foundation from March 1, 2020, to September 15, 2020, by using artificial intelligence techniques. From an initial cohort of 425 patients, 146 met the inclusion criteria and were enrolled in the study. The in-hospital mortality rate was 15%, and the ICU admission rate was 41%. Patients who died had higher troponin I (p-value<0.01) and IL-6 values (p-value=0.04), compared to those who survived. Patients admitted to ICU had higher levels of troponin I (p-value<0.01) and IL-6 (p-value<0.01), compared to those not admitted to ICU. Threshold values to predict in-hospital mortality and ICU admission have been identified. IL-6 levels higher than 15.133 ng/L have been associated with a 22.91% risk of in-hospital mortality, and IL-6 levels higher than 25.65 ng/L have been associated with a 56.16% risk of ICU admission. Troponin I levels higher than 12 ng/L have been associated with a 26.76% risk of in-hospital mortality and troponin I levels higher than 12 ng/L have been associated with a 52.11% risk of ICU admission. Levels of IL-6 and troponin I are associated with poor COVID-19 outcomes. Cut-off values capable of predicting in-hospital mortality and ICU admission have been identified. Building a predictive model using a machine-learning approach may be helpful in supporting clinical decisions in a more precise and personalized way.

The impact of periodontal disease on the clinical outcomes of COVID-19: A systematic review and meta-analysis

BackgroundA possible relationship between periodontitis (PD) and COVID-19 and its adverse outcomes has been suggested. Hence, the present systematic review and meta-analysis aimed to investigate the available evidence regarding the potential association between periodontitis (PD) and COVID-19 and its adverse outcomes.Materials and methodsPubMed, Scopus, Web of Science, and Google Scholar were searched for relevant studies published up to April 15th, 2023. Studies that evaluated the association between PD and COVID-19 were included. Risk of bias was evaluated by two reviewers, and meta-analyses were performed using RevMan 5.3 software.ResultsA total of 22 studies involving 92,535 patients from USA, Europe, Asia, the Middle East and South America were included; of these, 12 were pooled into the meta-analysis. Most of the studies (19 studies) reported a significant association between PD and COVID-19. The pooled data found a significant association between PD and COVID-19 outcomes: more severe symptoms (OR = 6.95, P = 0.0008), ICU admissions (OR = 3.15, P = 0.0001), and mortality (OR = 1.92, P = 0.21). Additionally, compared to mild PD, severe PD was significantly associated with higher risks of severe COVID-19 outcomes: severe symptoms (P = 0.02); ICU admission (P = 0.0001); and higher mortality rates (P = 0.0001). The results also revealed 58% higher risk for COVID-19 infection in patients with PD (P = 0.00001).ConclusionsThe present findings suggest a possible association between poor periodontal health and the risk of poor COVID-19 outcomes. However, owing to the observed methodological heterogeneity across the included studies, further prospective cohort studies with standardized methodologies are warranted to further unravel the potential association between periodontal disease and COVID-19 and its adverse outcomes.

Factors contributing to poor COVID-19 outcomes in diabetic patients: Findings from a single-center cohort study.

Diabetes Mellitus (DM) is a frequent comorbidity in patients infected with the SARS-CoV-2 virus. The risk of developing severe or critical COVID-19 and higher mortality was observed to be increased in diabetic patients hospitalized due to COVID-19. In this study we aimed to find out the impact of clinical characteristics, comorbidities, laboratory results, and complications on the outcomes of diabetic patients hospitalized due to COVID-19. This article is a retrospective cohort study that include diabetic patients hospitalized with COVID-19 infection. A definition of diabetes was based on the past history of diabetes or if the HbA1c was 6.5% or higher. Demographics, clinical characteristics, comorbidities, laboratory results, and complications were extracted from the electronic medical records. The mortality rate increased with increasing age (from 5.56% in younger patients to 46% in the elderly) and with severity (from 25.71% in moderate cases to 43.77% in critical cases). We found that a critical severity on admission (OR: 5.26, 95% CI: 1.28-21.66, p = 0.0214), a history of stroke (OR: 8.37, 95% CI: 2.2-31.88, p = 0.0018), and low calcium levels on admission (OR: 2.23, 95% CI: 1.01-4.91, p = 0.0475) were significant risk factors predicting higher COVID-19 mortality in diabetic patients. The findings of this study suggest that reduced calcium levels could potentially indicate higher mortality due to COVID-19 in patients with DM. Furthermore, careful monitoring of diabetic patients hospitalized due to COVID-19 infection, especially those with critical disease severity or those with a history of stroke, may improve their outcome and lessen mortality.

Risk factors for poor COVID-19 outcomes in patients with psychiatric disorders

BackgroundCoronavirus disease 2019 (COVID-19) has been found to have a greater impact on individuals with pre-existing psychiatric disorders. However, the underlying reasons for this increased risk have yet to be determined. This study aims to investigate the potential factors contributing poor outcomes among COVID-19 patients with psychiatric disorders, including delayed diagnosis of infection, vaccination rates, immune response, and the use of psychotropic medications. MethodsThis retrospective cohort study analyzed medical records of 15,783 adult patients who were diagnosed with COVID-19 infection by positive PCR tests between January and September 2022 at a single medical center. We identified psychiatric diagnoses using ICD-9 diagnostic codes from the preceding 3 years before COVID infection. Primary outcome was in-hospital mortality and secondary outcomes were severe illness requiring intensive care or mechanical ventilation, and hospitalization within 45 days after a positive COVID-19 test. We compared the rates of outcomes, viral load, vaccination status at the time of positive test, psychotropic medications prescription within 90 days prior, antiviral medication use, and blood inflammation markers between patients with and without psychiatric disorders. The Cox proportional hazard model was used to examine the association of psychiatric diagnoses, vaccination status, and psychotropic medication prescription with poor outcomes. ResultsPatients with psychiatric disorders demonstrated higher rates of severe illness (10.4% v.s. 7.1%) and hospitalization (16.4% vs. 11.3%), as well as a shorter duration to in-hospital mortality (6 vs. 12.5 days) compared to non-psychiatric patients. Psychiatric patients had higher vaccination rates and lower levels of inflammatory markers than non-psychiatric patients. Antipsychotic medication use was associated with in-hospital mortality (hazard ratio [HR] = 4.79, 95% confidence interval [CI] = 1.23–18.7), while being unvaccinated was associated with hospitalization (HR = 1.81, 95% CI = 1.29 to 2.54) and severe illness (HR = 3.23, 95% CI = 1.95 to 5.34) among patients with psychiatric disorders. Sedatives prescription was associated with all poor outcomes in general patients. ConclusionConsidering the narrow time window between a positive COVID-19 test and poor outcomes, healthcare providers should undertake close monitoring of patients with preexisting psychiatric disorders during the initial days after a positive PCR test. Furthermore, caution should be taken when prescribing psychotropic medications, with special attention to antipsychotics.

Comorbidities associated with the severity of COVID-19, and differences across ethnic groups: a UK Biobank cohort study

BackgroundDisparities in COVID-19 outcomes exist on the basis of ethnicity and comorbidities. Minority ethnic groups in the UK are known to have poorer COVID-19 outcomes, but also an increased prevelance of certain comorbidities associated with severe outcomes. Additionally, despite the prevalence of certain psychiatric disorders there is a lack of research establishing their relationship with COVID-19 outcomes.MethodsWe used UK Biobank data, involving 472,182 participants, to test for an association between comorbidities and COVID-19 diagnosis (n = 30,901); and to test for an association between comorbidities and severe COVID-19 (n = 3182). This was done by performing univariable and multivariable logistic regression analysis, estimating odds ratios (ORs) and their 95% confidence intervals (95% CIs). The comorbidities studied were coronary heart disease (CHD), hypertension, type II diabetes mellitus (T2DM), obesity, chronic kidney disease (CKD), depression and anxiety. Multivariable models were adjusted for various socioeconomic, demographic and health-related confounders. We then performed sub-group analysis by common UK ethnic groups (White, South Asian, and Black).ResultsIncreased prevalence of all studied comorbidities was seen in both outcomes, compared to the rest of the cohort. All studied comorbidities were associated with an increased risk of COVID-19 infection and severity across all models. For example, the adjusted ORs (95% CI) for depression were 1.112 (1.083 – 1.161) for COVID-19 diagnosis and 2.398 (2.163 – 2.658) for severe COVID-19. Sub-group analysis revealed stronger associations of COVID-19 diagnosis and severe COVID-19 for South-Asian participants for CHD (OR 1.585 [95% CI 1.194–2.105] for COVID-19 diagnosis and 3.021 [1.683–5.390] for severe COVID-19), hypertension (1.488 [1.231–1.799]; 3.399 [1.862–6.206]) and T2DM (1.671 [1.346–2.076]; 5.412 [3.130–9.357]) compared to White participants (1.264 [1.195–1.336] and 1.627 [1.441–1.837] for CHD; 1.131 [1.097–1.116] and 2.075 [1.885–2.284] for hypertension; 1.402 [1.331–1.476] and 2.890 [2.596–3.216] for T2DM). Similar results were seen for Black participants with CKD and hypertension.ConclusionSpecific comorbidities are risk factors for poorer COVID-19 outcomes, supporting targeted interventions and policy aimed at individuals with these comorbidities. Although further research is required, there’s also a need for targeted policies for ethnic minorities assessing the unique reasons they are at greater risk of poor COVID-19 outcomes.

COVID-19 Outcomes Among People With HIV and COVID-19 in New York City.

Literature on the impact of human immunodeficiency virus (HIV) on coronavirus disease 2019 (COVID-19)-related outcomes remains mixed. Few studies have evaluated COVID-19 outcomes by HIV status using population-based data. Using data from New York City COVID-19 surveillance and HIV surveillance systems prior to the widespread availability of COVID-19 vaccines, we conducted a retrospective cohort study comparing the risk of COVID-19 hospitalization and mortality by HIV status among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnoses from 29 February to 17 October 2020. Risk of hospitalization and death among people with HIV (PWH) withCOVID-19 were both nearly 30% higher compared with people without HIV. In crude models, incidence of adverse COVID-19 outcomes among PWH compared to people without HIV was elevated in certain groups, including women, and black, Hispanic/Latino, Native American, and multiracial people. CD4 cell count at SARS-CoV-2 diagnosis and presence of an underlying, non-HIV-related condition were independently and strongly associated with risk for COVID-19 hospitalization and death among PWH. New Yorkers with HIV experienced elevated risk for poor COVID-19 outcomes compared to those without HIV during 2020. PWH, particularly those with low CD4 counts or underlying conditions, should be an ongoing focus for COVID-19 vaccination and rigorous identification and treatment of SARS-CoV-2 infections to prevent adverse outcomes.

What Chicago community organizations needed to implement COVID-19 interventions: lessons learned in 2021.

As the COVID-19 pandemic placed a spotlight on the health inequities in the United States, this study aimed to determine the local programmatic needs of community organizations (CO) delivering COVID-19 interventions across Chicago. In the summer of 2021, the Chicagoland CEAL Program interviewed 34 COs that were providing education, testing, and/or vaccinations in communities experiencing poor COVID-19 outcomes. The interviews were analyzed thematically and organized around logistical challenges and funding/resource needs. The COs routinely offered testing (50%) or vaccinations (74%), with most (56%) employing some programmatic evaluation. Programs utilizing trusted-messenger systems were deemed most effective, but resource-intensive. CO specific needs clustered around sustaining effective outreach strategies, better CO coordination, wanting comprehensive trainings, improving program evaluation, and promoting services and programs. The COs reached populations with low-vaccine confidence using trusted messengers to overcome mistrust. However, replenishment of the resources needed to sustain such strategies should be prioritized. Leveraging the Chicagoland CEAL Program to help negotiate community organizations' interorganizational coordination, create training programs, and provide evaluation expertise are deliverable supports that may bolster COVID-19 prevention. Achieving health justice requires that all institutions of power participate in meaningful community engagement, help build community capacity, and infuse health equity throughout all aspects of the research and program evaluation processes.

Association of frailty index of laboratory tests (FI-LAB) and COVID-19 clinical outcomes in veterans with cancer.

e24023 Background: Veterans with cancer have high COVID-19-attributable mortality. Frailty, a multisystem syndrome characterized by vulnerability to stressors from loss of physiological reserve, is common in cancer patients and confers worse clinical outcomes. In hospitalized cancer patients with COVID-19 infection, the role of frailty remains unclear. Our study aim was to compare clinical and utilization outcomes of cancer patients hospitalized with COVID-19 according to frailty status. Methods: The retrospective cohort study included hospitalized veterans with cancer and acute COVID-19 infection at 7 VA facilities in Florida and Puerto Rico from March-August 2020. Frailty was assessed using a 31-item frailty index of laboratory tests and vital signs (FI-LAB) with scores grouped by tertiles. We chart reviewed VA databases to collect Veterans’ socio-demographics, COVID-19 Polymerase Chain Reaction (PCR) results, and clinical and utilization outcomes. We ran binomial logistic regression analyses to calculate the odds of inpatient death, ICU admission, ICU transfer, prolonged length of stay, new nursing home placement, 30-day readmission, 30-day mortality, 6-month,1-year, and 2-year mortality according to the tertiles, adjusted for age, BMI, sex, race, ethnicity, and other conditions with greater risk for poor COVID-19 outcomes. Patients were followed until death or August 13, 2022. Results: 143 older Veterans with cancer were hospitalized with a mean age of 74.4 years (SD = 11.5) years, 95.9% (n = 117) male, 66.4% white (n = 81), and 9.8% (n = 12) Hispanic. 122 (85.3%) met the inclusion criteria. There were no differences in baseline sociodemographic or clinical characteristics except for a higher prevalence of congestive heart failure. The upper FI-LAB tertile had a higher risk of inpatient death, OR 12.47 (95%CI:1.3-121.4), p = 0.03, 30-day post-discharge mortality, OR 9.78 (95%CI:.21-79.4), p = .03 and 2-yr post-discharge mortality OR 4.9 (1.2-19.6) p &lt; 0.03. There were no differences in other clinical and utilization outcomes. Conclusions: In hospitalized Veterans with cancer and coexistent COVID-19 infection, patients with higher levels of frailty have a greater risk of inpatient death, 30-day post-discharge mortality, and 2-year post-discharge mortality. More studies are needed to confirm the utility of FI-LAB in hospitalized patients with COVID-19 and cancer.

Utilizing data to foster equity in infection prevention outreach among skilled nursing facilities in Michigan

Background: Since October 2020, the Infection Prevention Resource and Assessment Team (IPRAT) has provided infection prevention guidance and support to congregate-care settings throughout Michigan. Specifically, outreach to skilled nursing facilities (SNFs) in response to reported positive COVID-19 resident and staff cases. Case rates provide limited data and do not factor in additional variables, such as staffing shortages, geographical location, or access to supplies, which can increase the vulnerability of staff and residents to outbreaks. To facilitate equitable outreach, a risk assessment was developed using variables related to infection prevention and poor COVID-19 outcomes utilizing local, state, and federal data reporting websites. Methods: A retrospective data review of IPRAT’s electronic data repository was performed, and 2 distinct periods were identified between November 6, 2020, and December 5, 2022. Outreach method 1 involved only using case counts from November 6, 2020, to September 24, 2021. Outreach method 2 (new risk-assessment–based outreach) involved additional data points from April 12, 2021, to December 5, 2022. Data included 17 self-reported items from the NHSN, 3 characteristics regarding facilities’ COVID-19 units, and 7 community-level variables derived from county vaccine rates, social vulnerability index (SVI), and COVID-19 community transmission level. The scoring of each data point ranged from 0–10, and outreach was prioritized to facilities with the highest overall scores. Successful referrals (resulting in a site visit) were compared to the SVI and healthcare emergency regional maps to determine whether the new outreach method reached more facilities in vulnerable communities. Results: Of 358 outreach attempts, IPRAT had a higher success rate with method 2 (6.9%) compared to method 1 (5.3%) and improved outreach in rural Michigan regions 7 and 8 (15% vs 3%). Site visits in counties with a high SVI rating with method 2 were 14.5% versus 10.6% using method 1. COVID-19 prevention referral success rates were higher (4.4% vs 3.1%) using method 2. Conclusions: The risk-assessment–based outreach method showed improvement in overall referral success rates among facilities in rural and higher-SVI counties. These communities tend to experience higher health disparities and poorer health outcomes. Incorporating the more nuanced data variables correlated with at-risk congregate-care settings receiving timelier outreach. The limitations of the study include sample size, period of data collected (2 years), and the complexity of objectively measuring equity.Disclosures: None

Humoral response after a BNT162b2 heterologous third dose of COVID-19 vaccine following two doses of BBIBP-CorV among healthcare personnel in Peru

BackgroundThe inactivated virus vaccine, BBIBP-CorV, was principally distributed across low- and middle-income countries as primary vaccination strategy to prevent poor COVID-19 outcomes. Limited information is available regarding its effect on heterologous boosting. We aim to evaluate the immunogenicity and reactogenicity of a third booster dose of BNT162b2 following a double BBIBP-CorV regime. MethodsWe conducted a cross-sectional study among healthcare providers from several healthcare facilities of the Seguro Social de Salud del Perú - ESSALUD. We included participants two-dose BBIBP-CorV vaccinated who presented a three-dose vaccination card at least 21 days passed since the vaccinees received their third dose and were willing to provide written informed consent. Antibodies were determined using LIAISON® SARS-CoV-2 TrimericS IgG (DiaSorin Inc., Stillwater, USA). Factors potentially associated with immunogenicity, and adverse events, were considered. We used a multivariable fractional polynomial modeling approach to estimate the association between anti-SARS-CoV-2 IgG antibodies’ geometric mean (GM) ratios and related predictors. ResultsWe included 595 subjects receiving a third dose with a median (IQR) age of 46 [37,54], from which 40% reported previous SARS-CoV-2 infection. The overall geometric mean (IQR) of anti-SARS-CoV-2 IgG antibodies was 8,410 (5,115 – 13,000) BAU/mL. Prior SARS-CoV-2 history and full/part-time in-person working modality were significantly associated with greater GM. Conversely, time from boosting to IgG measure was associated with lower GM levels. We found 81% of reactogenicity in the study population; younger age and being a nurse were associated with a lower incidence of adverse events. ConclusionsAmong healthcare providers, a booster dose of BNT162b2 following a full BBIBP-CorV regime provided high humoral immune protection. Thus, SARS-CoV-2 previous exposure and working in person displayed as determinants that increase anti-SARS-CoV-2 IgG antibodies.