Cardiometabolic Disease Severity, Social Determinants of Health and Poor COVID-19 Outcomes

Background: Social determinants of health (SDoH) contribute to disparities in obesity and diabetes yet relative contributions of SDoH and cardiometabolic disease on COVID-19 outcomes are unknown. We sought to determine the ability of SDoH and cardiometabolic disease staging (CMDS) data to predict subsequent COVID-19 outcomes, and to investigate the degree to which adding SDoH to the clinical CMDS improved prediction accuracy. Methods: Individual and neighborhood level SDoH and cardiometabolic disease staging (CMDS) data [BMI, glucose, blood pressure, HDL, triglycerides], collected at a medical encounter prior to a positive COVID-19 test, were extracted from the electronic medical record (EMR) at an academic medical center in the Southeastern US. We used Bayesian logistic regression to model each COVID-19 outcome [hospitalization, intensive care unit (ICU) admission, and mortality] using CMDS components, individual and neighborhood SDoH, controlling for age, race and gender. Models were cross-validated and areas under the curve (AUC) were compared using Delongs test. Results: A total of 2,873 patients were identified [mean age: 58 years (SD 13.2), 59% female, 45% non-Hispanic Black]. CMDS score, insurance status, male sex and higher glucose values were associated with increased odds of all outcomes;area level social vulnerability was associated with increased odds of hospitalization [odds ratio (OR): 1.84, 95% confidence interval (CI): 1.38-2.45] and ICU admission [OR 1.98, 95 % CI: 1.45-2.85]. AUCs improved when SDoH were added to CMDS (p<0.001): hospitalization (AUC 0.78 vs. 0.82);ICU admission (AUC 0.77 vs. 0.81);and mortality (AUC 0.77 vs. 0.83). Conclusions: Clinical markers of cardiometabolic disease and SDoH, collected up to 3 years in advance of COVID-19 infection, were independently highly predictive of subsequent COVID-19 outcomes in our population. Both clinical and SDoH factors should be utilized to identify individuals at high risk for poor outcomes.

Race Versus Social Determinants of Health in COVID-19 Hospitalization Prediction.

INTRODUCTION: Including race as a biological construct in risk prediction models may guide clinical decisions in ways that cause harm and widen racial disparities. This study reports on using race versus social determinants of health (SDoH) in predicting the associations between cardiometabolic disease severity (assessed using cardiometabolic disease staging) and COVID-19 hospitalization. METHODS: Electronic medical record data on patients with a positive COVID-19 polymerase chain reaction test in 2020 and a previous encounter in the electronic medical record where cardiometabolic disease staging clinical data (BMI, blood glucose, blood pressure, high-density lipoprotein cholesterol, and triglycerides) were available from 2017 to 2020, were analyzed in 2021. Associations between cardiometabolic disease staging and COVID-19 hospitalization adding race and SDoH (individual and neighborhood level [e.g., Social Vulnerability Index]) in different models were examined. Area under the curve was used to assess predictive performance. RESULTS: A total of 2,745 patients were included (mean age of 58 years, 59% female, 47% Black). In the cardiometabolic disease staging model, area under the curve was 0.767 vs 0.777 when race was included. Adding SDoH to the cardiometabolic model improved the area under the curve to 0.809 (p<0.001), whereas the addition of SDoH and race increased the area under the curve to 0.811. In race-stratified models, the area under the curve for non-Hispanic Blacks was 0.781, whereas the model for non-Hispanic Whites performed better with an area under the curve of 0.821. CONCLUSIONS: Cardiometabolic disease staging was predictive of hospitalization after a positive COVID-19 test. Adding race did not markedly increase the predictive ability; however, adding SDoH to the model improved the area under the curve to ≥0.80. Future research should include SDoH with biological variables in prediction modeling to capture social experience of race.

COVID-19 Antibodies and Outcomes among Outpatient Maintenance Hemodialysis Patients.

Background: Patients on maintenance hemodialysis are particularly vulnerable to infection and hospitalization from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to immunocompromised patients and the clustering that occurs in outpatient dialysis units, the seroprevalence of COVID-19 antibodies in this population is unknown and has significant implications for public health. Also, little is known about their risk factors for hospitalization. Methods: Three outpatient maintenance hemodialysis units affiliated with a major teaching hospital in the New York area were studied. We determined rates of SARS-CoV-2 positivity via nasopharyngeal, real-time, reverse-transcriptase PCR (RT-PCR); SARS-CoV-2 IgG seropositivity; hospitalization; and mortality. Results: Of 367 patients, 28% had either SARS-CoV-2 seropositivity or PCR positivity. Prevalence across the three respective units was 7%, 32%, and 70%. Those who were either antibody or PCR positive were significantly younger (65 versus 69 years, P=0.05), and had a higher prevalence of Black race (43% versus 30%, P=0.001) and Hispanic ethnicity (32% versus 12%, P<0.001) compared with those who tested negative. Higher positivity rates were also observed among those who took taxis and ambulettes to and from dialysis, compared with those who used personal transportation. Antibodies were detected in all of the patients with a positive PCR result who underwent serologic testing. Of those that were seropositive, 32% were asymptomatic. The hospitalization rate on the basis of either antibody or PCR positivity was 35%, with a hospital mortality rate of 33%. Aside from COPD, no other variables were more prevalent in patients who were hospitalized. Conclusions: We observed significant differences in rates of COVID-19 infection within three outpatient dialysis units, with universal seroconversion. Among patients with ESKD, rates of asymptomatic infection appear to be high, as do hospitalization and mortality rates.

Associations between cardiometabolic disease severity, social determinants of health (SDoH), and poor COVID-19 outcomes.

OBJECTIVE: This study aimed to determine the ability of retrospective cardiometabolic disease staging (CMDS) and social determinants of health (SDoH) to predict COVID-19 outcomes. METHODS: Individual and neighborhood SDoH and CMDS clinical parameters (BMI, glucose, blood pressure, high-density lipoprotein, triglycerides), collected up to 3 years prior to a positive COVID-19 test, were extracted from the electronic medical record. Bayesian logistic regression was used to model CMDS and SDoH to predict subsequent hospitalization, intensive care unit (ICU) admission, and mortality, and whether adding SDoH to the CMDS model improved prediction was investigated. Models were cross validated, and areas under the curve (AUC) were compared. RESULTS: A total of 2,873 patients were identified (mean age: 58 years [SD 13.2], 59% were female, 45% were Black). CMDS, insurance status, male sex, and higher glucose values were associated with increased odds of all outcomes; area-level social vulnerability was associated with increased odds of hospitalization (odds ratio: 1.84, 95% CI: 1.38-2.45) and ICU admission (odds ratio 1.98, 95% CI: 1.45-2.85). The AUCs improved when SDoH were added to CMDS (p < 0.001): hospitalization (AUC 0.78 vs. 0.82), ICU admission (AUC 0.77 vs. 0.81), and mortality (AUC 0.77 vs. 0.83). CONCLUSIONS: Retrospective clinical markers of cardiometabolic disease and SDoH were independently predictive of COVID-19 outcomes in the population.

Teleassessments for Enrollment of Adults With Physical or Mobility Disability in a Home-Based Exercise Trial in Response to COVID-19: Usability Study.

BACKGROUND: The Scale-Up Project Evaluating Responsiveness to Home Exercise And Lifestyle Tele-Health (SUPER-HEALTH) initiative is a large randomized controlled study that aims to overcome logistical barriers to exercise via telehealth for people with physical disabilities. However, at the start of the COVID-19 pandemic, enrollment was halted due to limited operations at the testing site, which included no onsite visits that involved participant data collection. In response to the limited operations, a modified data collection protocol was developed for virtual enrollment of study participants. OBJECTIVE: This paper presents feasibility data on using teleassessments to enroll people with mobility impairment into a home-based exercise trial. METHODS: The modified protocol replaced onsite enrollment and data collection visits with teleassessments using a computer tablet and testing equipment that was shipped to the participants' home address prior to the synchronous teleassessments conducted by an exercise physiologist through Zoom. The participants were mailed a teleassessment toolkit that included a digital blood pressure cuff, spirometer, hand dynamometer, mini disc cone, and measuring tape (to complete standardized testing). The teleassessment measures included resting blood pressure and heart rate, forced vital capacity, grip strength, Five Times Sit to Stand, and Timed Up and Go. Feasibility metrics included technological effectiveness, efficiency, and safety. The technological effectiveness of the telehealth assessment was determined by the percentage of sessions completed without technical issues with ≥90% criteria set a priori. Efficiency was measured by a session duration of ≤2 hours. Safety was measured by the number of adverse events related to the teleassessments reported. RESULTS: Data from 36 participants were included in this feasibility study, and 34 (94%) participants completed all teleassessments without technical issues. For efficiency, the teleassessment sessions were completed in a mean time of 65 minutes and a maximum session length of 110 minutes. There were no adverse events reported to indicate concerns with the safety of teleassessments. CONCLUSIONS: The modified teleassessment protocol, in response to COVID-19 restrictions, may be a feasible process for enrolling adults with mobility impairment into a home exercise trial who otherwise would have not been able to participate. TRIAL REGISTRATION: ClinicalTrials.gov NCT03024320; https://clinicaltrials.gov/ct2/show/NCT03024320.

COVID-19 Modifications for Remote Teleassessment and Teletraining of a Complementary Alternative Medicine Intervention for People With Multiple Sclerosis: Protocol for a Randomized Controlled Trial.

BACKGROUND: Access to comprehensive exercise and rehabilitation services for people with multiple sclerosis (MS) remains a major challenge, especially in rural, low-income areas. Hence, the Tele-Exercise and Multiple Sclerosis (TEAMS) study aims to provide patient-centered, coordinated care by implementing a 12-week complementary and alternative medicine (CAM) intervention for adults with MS. However, due to the societal impact of coronavirus disease (COVID-19) in mid-March 2020, the University of Alabama at Birmingham announced a limited business model halting all nonessential research requiring on-site visits, which includes the TEAMS study. OBJECTIVE: In compliance with the shelter-in-place policy and quarantine guidance, a modified testing and training protocol was developed to allow participants to continue the study. METHODS: The modified protocol, which replaces on-site data collection and training procedures, includes a teleassessment package (computer tablet, blood pressure cuff, hand dynamometer, mini disc cone, measuring tape, an 8" step, and a large-print 8" × 11" paper with ruler metrics and wall-safe tape) and a virtual meeting platform for synchronous interactive training between the therapist and the participant. The teleassessment measures include resting blood pressure and heart rate, grip strength, Five Times Sit to Stand, Timed Up & Go, and the Berg Balance Scale. The teletraining component includes 20 sessions of synchronous training sessions of dual tasking, yoga, and Pilates exercises designed and customized for a range of functional levels. Teletraining lasts 12 weeks and participants are instructed to continue exercising for a posttraining period of 9 months. RESULTS: The protocol modifications were supported with supplemental funding (from the Patient-Centered Outcomes Research Institute) and approved by the University Institutional Review Board for Human Use. At the time nonessential research visits were halted by the university, there were 759 people enrolled and baseline tested, accounting for 92.5% of our baseline testing completion target (N=820). Specifically, 325 participants completed the 12-week intervention and follow-up testing visits, and 289 participants needed to complete either the intervention or follow-up assessments. A modified analysis plan will include sensitivity analyses to ensure the robustness of the study results in the presence of uncertainty and protocol deviations. Study results are projected to be published in 2021. CONCLUSIONS: This modified remote teleassessment/teletraining protocol will impact a large number of participants with MS who would otherwise have been discontinued from the study. TRIAL REGISTRATION: ClinicalTrials.gov NCT03117881; https://clinicaltrials.gov/ct2/show/NCT03117881. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18415.