Social Determinants of Health and Cardiovascular Risk among Adults with Diabetes: The Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study.

Background: Social determinants of health (SDOH) have been associated with diabetes risk; however, their association with cardiovascular disease (CVD) events in individuals with diabetes is poorly described. We hypothesized that a greater number of SDOH among individuals with diabetes would be associated with a higher risk of CVD events. Methods: The REasons for Geographic and Racial Differences in Stroke (REGARDS) study is a national, biracial cohort of 30,239 individuals ≥45 years old recruited in 2003-2007. We included 6,322 participants with diabetes at baseline, defined as healthcare professional diagnosis, diabetes medication use, or blood glucose values. Seven SDOH that were individually associated with CVD events were included (P<0.20). The outcome was CVD events, a composite of expert-adjudicated myocardial infarction, stroke, or cardiovascular death. We estimated Cox proportional hazard models to examine associations between number of SDOH (0, 1, 2, ≥3) and CVD events. Results: In an age and sex adjusted model, the presence of multiple SDOH significantly increased the risk of any CVD event (hazard ratio [HR], 1.48; 95% confidence interval [CI], 1.26 to 1.74 for two SDOH; HR, 1.68; 95% CI, 1.43 to 1.96 for ≥3 SDOH). This finding was attenuated but remained statistically significant in a fully adjusted model (HR, 1.19; 95% CI, 1.01 to 1.40 for two SDOH; HR, 1.27; 95% CI, 1.07 to 1.50 for ≥3 SDOH). Conclusion: Having multiple SDOH was independently associated with an increased risk of CVD events, a finding driven by cardiovascular death. Identifying individuals with diabetes who have multiple SDOH may be helpful for detecting those at higher risk of experiencing or dying from CVD events.

The Designed Ankyrin Repeat Protein Antiviral Ensovibep for Nonhospitalized Patients With Coronavirus Disease 2019: Results From EMPATHY, a Randomized, Placebo-Controlled Phase 2 Study.

Background: The coronavirus disease 2019 (COVID-19) pandemic was characterized by rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, affecting viral transmissibility, virulence, and response to vaccines/therapeutics. EMPATHY (NCT04828161), a phase 2 study, investigated the safety/efficacy of ensovibep, a multispecific designed ankyrin repeat protein (DARPin) with multivariant in vitro activity, in ambulatory patients with mild to moderate COVID-19. Methods: Nonhospitalized, symptomatic patients (N = 407) with COVID-19 were randomized to receive single-dose intravenous ensovibep (75, 225, or 600 mg) or placebo and followed until day 91. The primary endpoint was time-weighted change from baseline in log10 SARS-CoV-2 viral load through day 8. Secondary endpoints included proportion of patients with COVID-19-related hospitalizations, emergency room (ER) visits, and/or all-cause mortality to day 29; time to sustained clinical recovery to day 29; and safety to day 91. Results: Ensovibep showed superiority versus placebo in reducing log10 SARS-CoV-2 viral load; treatment differences versus placebo in time-weighted change from baseline were -0.42 (P = .002), -0.33 (P = .014), and -0.59 (P < .001) for 75, 225, and 600 mg, respectively. Ensovibep-treated patients had fewer COVID-19-related hospitalizations, ER visits, and all-cause mortality (relative risk reduction: 78% [95% confidence interval, 16%-95%]) and a shorter median time to sustained clinical recovery than placebo. Treatment-emergent adverse events occurred in 44.3% versus 54.0% of patients in the ensovibep and placebo arms; grade 3 events were consistent with COVID-19 morbidity. Two deaths were reported with placebo and none with ensovibep. Conclusions: All 3 doses of ensovibep showed antiviral efficacy and clinical benefits versus placebo and an acceptable safety profile in nonhospitalized patients with COVID-19.

Development and validation of mortality prediction models based on the social determinants of health.

BACKGROUND: There is no standardised approach to screening adults for social risk factors. The goal of this study was to develop mortality risk prediction models based on the social determinants of health (SDoH) for clinical risk stratification. METHODS: Data were used from REasons for Geographic And Racial Differences in Stroke (REGARDS) study, a national, population-based, longitudinal cohort of black and white Americans aged ≥45 recruited between 2003 and 2007. Analysis was limited to participants with available SDoH and mortality data (n=20 843). All-cause mortality, available through 31 December 2018, was modelled using Cox proportional hazards with baseline individual, area-level and business-level SDoH as predictors. The area-level Social Vulnerability Index (SVI) was included for comparison. All models were adjusted for age, sex and sampling region and underwent internal split-sample validation. RESULTS: The baseline prediction model including only age, sex and REGARDS sampling region had a c-statistic of 0.699. An individual-level SDoH model (Model 1) had a higher c-statistic than the SVI (0.723 vs 0.708, p<0.001) in the testing set. Sequentially adding area-level SDoH (c-statistic 0.723) and business-level SDoH (c-statistics 0.723) to Model 1 had minimal improvement in model discrimination. Structural racism variables were associated with all-cause mortality for black participants but did not improve model discrimination compared with Model 1 (p=0.175). CONCLUSION: In conclusion, SDoH can improve mortality prediction over 10 years relative to a baseline model and have the potential to identify high-risk patients for further evaluation or intervention if validated externally.

Association between city-wide lockdown and COVID-19 hospitalization rates in multigenerational households in New York City.

BACKGROUND: City-wide lockdowns and school closures have demonstrably impacted COVID-19 transmission. However, simulation studies have suggested an increased risk of COVID-19 related morbidity for older individuals inoculated by house-bound children. This study examines whether the March 2020 lockdown in New York City (NYC) was associated with higher COVID-19 hospitalization rates in neighborhoods with larger proportions of multigenerational households. METHODS: We obtained daily age-segmented COVID-19 hospitalization counts in each of 166 ZIP code tabulation areas (ZCTAs) in NYC. Using Bayesian Poisson regression models that account for spatiotemporal dependencies between ZCTAs, as well as socioeconomic risk factors, we conducted a difference-in-differences study amongst ZCTA-level hospitalization rates from February 23 to May 2, 2020. We compared ZCTAs in the lowest quartile of multigenerational housing to other quartiles before and after the lockdown. FINDINGS: Among individuals over 55 years, the lockdown was associated with higher COVID-19 hospitalization rates in ZCTAs with more multigenerational households. The greatest difference occurred three weeks after lockdown: Q2 vs. Q1: 54% increase (95% Bayesian credible intervals: 22-96%); Q3 vs. Q1: 48% (17-89%); Q4 vs. Q1: 66% (30-211%). After accounting for pandemic-related population shifts, a significant difference was observed only in Q4 ZCTAs: 37% (7-76%). INTERPRETATION: By increasing house-bound mixing across older and younger age groups, city-wide lockdown mandates imposed during the growth of COVID-19 cases may have inadvertently, but transiently, contributed to increased transmission in multigenerational households.

The Diagnostic Accuracy Of Procalcitonin for Urinary Tract Infection in Hospitalized Older Adults: a Prospective Study.

BACKGROUND: The diagnosis of urinary tract infection (UTI) is challenging among hospitalized older adults, particularly among those with altered mental status. OBJECTIVE: To determine the diagnostic accuracy of procalcitonin (PCT) for UTI in hospitalized older adults. DESIGN: We performed a prospective cohort study of older adults (≥65 years old) admitted to a single hospital with evidence of pyuria on urinalysis. PCT was tested on initial blood samples. The reference standard was a clinical definition that included the presence of a positive urine culture and any symptom or sign of infection referable to the genitourinary tract. We also surveyed the treating physicians for their clinical judgment and performed expert adjudication of cases for the determination of UTI. PARTICIPANTS: Two hundred twenty-nine study participants at a major academic medical center. MAIN MEASURES: We calculated the area under the receiver operating characteristic curve (AUC) of PCT for the diagnosis of UTI. KEY RESULTS: In this study cohort, 61 (27%) participants met clinical criteria for UTI. The median age of the overall cohort was 82.6 (IQR 74.9-89.7) years. The AUC of PCT for the diagnosis of UTI was 0.56 (95% CI, 0.46-0.65). A series of sensitivity analyses on UTI definition, which included using a decreased threshold for bacteriuria, the treating physicians' clinical judgment, and independent infectious disease specialist adjudication, confirmed the negative result. CONCLUSIONS: Our findings demonstrate that PCT has limited value in the diagnosis of UTI among hospitalized older adults. Clinicians should be cautious using PCT for the diagnosis of UTI in hospitalized older adults.

Social determinants of health and cancer mortality in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort study.

BACKGROUND: Social determinants of health (SDOHs) cluster together and can have deleterious impacts on health outcomes. Individually, SDOHs increase the risk of cancer mortality, but their cumulative burden is not well understood. The authors sought to determine the combined effect of SDOH on cancer mortality. METHODS: Using the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, the authors studied 29,766 participants aged 45+ years and followed them 10+ years. Eight potential SDOHs were considered, and retained SDOHs that were associated with cancer mortality (P < .10) were retained to create a count (0, 1, 2, 3+). Cox proportional hazard models estimated associations between the SDOH count and cancer mortality through December 31, 2017, adjusting for confounders. Models were age-stratified (45-64 vs 65+ years). RESULTS: Participants were followed for a median of 10.6 years (interquartile range [IQR], 6.5, 12.7 years). Low education, low income, zip code poverty, poor public health infrastructure, lack of health insurance, and social isolation were significantly associated with cancer mortality. In adjusted models, among those <65 years, compared to no SDOHs, having 1 SDOH (adjusted hazard ratio [aHR], 1.39; 95% CI, 1.11-1.75), 2 SDOHs (aHR, 1.61; 95% CI, 1.26-2.07), and 3+ SDOHs (aHR, 2.09; 95% CI, 1.58-2.75) were associated with cancer mortality (P for trend <.0001). Among individuals 65+ years, compared to no SDOH, having 1 SDOH (aHR, 1.16; 95% CI, 1.00-1.35) and 3+ SDOHs (aHR, 1.26; 95% CI, 1.04-1.52) was associated with cancer mortality (P for trend = .032). CONCLUSIONS: A greater number of SDOHs were significantly associated with an increased risk of cancer mortality, which persisted after adjustment for confounders.

Clinical Characteristics and Outcomes of Adults With a History of Heart Failure Hospitalized for COVID-19.

BACKGROUND: It is important to understand the risk for in-hospital mortality of adults hospitalized with acute coronavirus disease 2019 (COVID-19) infection with a history of heart failure (HF). METHODS: We examined patients hospitalized with COVID-19 infection from January 1, 2020 to July 22, 2020, from 88 centers across the US participating in the American Heart Association's COVID-19 Cardiovascular Disease registry. The primary exposure was history of HF and the primary outcome was in-hospital mortality. To examine the association between history of HF and in-hospital mortality, we conducted multivariable modified Poisson regression models that included sociodemographics and comorbid conditions. We also examined HF subtypes based on left ventricular ejection fraction in the prior year, when available. RESULTS: Among 8920 patients hospitalized with COVID-19, mean age was 61.4±17.5 years and 55.5% were men. History of HF was present in 979 (11%) patients. In-hospital mortality occurred in 31.6% of patients with history of HF, and 16.9% in patients without a history of HF. In a fully adjusted model, history of HF was associated with increased risk for in-hospital mortality (relative risk: 1.16 [95% CI, 1.03-1.30]). Among 335 patients with left ventricular ejection fraction, heart failure with reduced ejection fraction was significantly associated with in-hospital mortality in a fully adjusted model (heart failure with reduced ejection fraction relative risk: 1.40 [95% CI, 1.10-1.79]; heart failure with mid-range ejection fraction relative risk: 1.06 [95% CI, 0.65-1.73]; heart failure with preserved ejection fraction relative risk, 1.06 [95% CI, 0.84-1.33]). CONCLUSIONS: Risk for in-hospital mortality was substantial among adults with history of HF, in large part due to age and comorbid conditions. History of heart failure with reduced ejection fraction may confer especially elevated risk. This population thus merits prioritization for the COVID-19 vaccine.

Racial Disparities in Preventable Adverse Events Attributed to Poor Care Coordination Reported in a National Study of Older US Adults.

BACKGROUND: Previous work found that Black patients experience worse care coordination than White patients. OBJECTIVE: The aim was to determine if there are racial disparities in self-reported adverse events that could have been prevented with better communication. RESEARCH DESIGN: We used data from a cross-sectional survey that was administered to participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study in 2017-2018. SUBJECTS: REGARDS participants aged 65+ years of age who reported >1 ambulatory visits and >1 provider in the prior 12 months (thus at risk for gaps in care coordination). MEASURES: Our primary outcome was any repeat test, drug-drug interaction, or emergency department visit or hospitalization that respondents thought could have been prevented with better communication. We used Poisson models with robust standard error to determine if there were differences in preventable events by race. RESULTS: Among 7568 REGARDS respondents, the mean age was 77 years (SD: 6.7), 55.4% were female, and 33.6% were Black. Black participants were significantly more likely to report any preventable adverse events compared with Whites [adjusted risk ratio (aRR): 1.64; 95% confidence interval (CI): 1.42-1.89]. Specifically, Blacks were more likely than Whites to report a repeat test (aRR: 1.77; 95% CI: 1.38-2.29), a drug-drug interaction (aRR: 1.76; 95% CI: 1.46-2.12), and an emergency department visit or hospitalization (aRR: 1.45; 95% CI: 1.01-2.08). CONCLUSIONS: Black participants were significantly more likely to report a preventable adverse event attributable to poor care coordination than White participants, independent of demographic and clinical characteristics.

Association between overcrowded households, multigenerational households, and COVID-19: a cohort study.

INTRODUCTION: The role of overcrowded and multigenerational households as a risk factor for COVID-19 remains unmeasured. The objective of this study is to examine and quantify the association between overcrowded and multigenerational households, and COVID-19 in New York City (NYC). METHODS: We conducted a Bayesian ecological time series analysis at the ZIP Code Tabulation Area (ZCTA) level in NYC to assess whether ZCTAs with higher proportions of overcrowded (defined as proportion of estimated number of housing units with more than one occupant per room) and multigenerational households (defined as the estimated percentage of residences occupied by a grandparent and a grandchild less than 18 years of age) were independently associated with higher suspected COVID-19 case rates (from NYC Department of Health Syndromic Surveillance data for March 1 to 30, 2020). Our main measure was adjusted incidence rate ratio (IRR) of suspected COVID-19 cases per 10,000 population. Our final model controlled for ZCTA-level sociodemographic factors (median income, poverty status, White race, essential workers), prevalence of clinical conditions related to COVID-19 severity (obesity, hypertension, coronary heart disease, diabetes, asthma, smoking status, and chronic obstructive pulmonary disease), and spatial clustering. RESULTS: 39,923 suspected COVID-19 cases presented to emergency departments across 173 ZCTAs in NYC. Adjusted COVID-19 case rates increased by 67% (IRR 1.67, 95% CI = 1.12, 2.52) in ZCTAs in quartile four (versus one) for percent overcrowdedness and increased by 77% (IRR 1.77, 95% CI = 1.11, 2.79) in quartile four (versus one) for percent living in multigenerational housing. Interaction between both exposures was not significant (ß interaction = 0.99, 95% CI: 0.99-1.00). CONCLUSIONS: Over-crowdedness and multigenerational housing are independent risk factors for suspected COVID-19. In the early phase of surge in COVID cases, social distancing measures that increase house-bound populations may inadvertently but temporarily increase SARS-CoV-2 transmission risk and COVID-19 disease in these populations.

Ambulatory Care Fragmentation and Incident Stroke.

Background More fragmented ambulatory care (ie, care spread across many providers without a dominant provider) has been associated with excess emergency department and inpatient care. We sought to determine whether more fragmented ambulatory care is associated with an increase in the hazard of incident stroke, overall and stratified by health status and by race. Methods and Results We conducted a secondary analysis of data from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study (2003-2016), including participants aged ≥65 years who had linked Medicare fee-for-service claims and no history of stroke (N=12 510). We measured fragmentation of care with the reversed Bice-Boxerman index. We used Poisson models to determine the association between fragmentation and adjudicated incident stroke. The average age of participants was 70.5 years; 53% were women, 32% were Black participants, and 16% were participants with fair or poor health. Overall, the adjusted rate of incident stroke was similar for high versus low fragmentation (8.2 versus 8.1 per 1000 person-years, respectively; P=0.89). Among participants with fair or poor self-rated health, having high versus low fragmentation was associated with a trend toward a higher adjusted rate of incident strokes (14.8 versus 10.4 per 1000 person-years, respectively; P=0.067). Among Black participants with fair or poor self-rated health, having high versus low fragmentation was associated with a higher adjusted rate of strokes (19.3 versus 10.3 per 1000 person-years, respectively; P=0.02). Conclusions Highly fragmented ambulatory care is independently associated with incident stroke among Black individuals with fair or poor health.

Differences in ambulatory care fragmentation by race.

BACKGROUND: More fragmented ambulatory care (i.e., care spread across many providers without a dominant provider) has been associated with more subsequent healthcare utilization (such as more tests, procedures, emergency department visits, and hospitalizations) than less fragmented ambulatory care. It is not known if race and socioeconomic status are associated with fragmented ambulatory care. METHODS: We conducted a longitudinal analysis of data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, using the REGARDS baseline visit plus the first year of follow-up. We included participants ≥65 years old, who had linked fee-for-service Medicare claims, and ≥ 4 ambulatory visits in the first year of follow-up. We used Tobit regression to determine the associations between race, annual household income, and educational attainment at baseline and fragmentation score in the subsequent year (as measured with the reversed Bice-Boxerman Index). Covariates included other demographic characteristics, medical conditions, medication use, health behaviors, and psychosocial variables. Additional analyses categorized visits by the type of provider (primary care vs. specialist). RESULTS: The study participants (N = 6799) had an average age of 73.0 years, 53% were female, and 30% were black. Nearly half had low annual household income (<$35,000) and 41% had a high school education or less. Overall, participants had a median of 10 ambulatory visits to 4 providers in the 12 months following their baseline study visit. Participants in the highest quintile of fragmentation scores had a median of 11 visits to 7 providers. Black race was associated with an absolute adjusted 3% lower fragmentation score compared to white race (95% confidence interval (2% lower to 4% lower; p < 0.001). This difference was explained by blacks seeing fewer specialists than whites. Income and education were not independent predictors of fragmentation scores. CONCLUSIONS: Among Medicare beneficiaries, blacks had less fragmented ambulatory care than whites, due to lower utilization of specialty care. Future research is needed to determine the effect of fragmented care on health outcomes for blacks and whites.

Healthcare Fragmentation and Incident Acute Coronary Heart Disease Events: a Cohort Study.

BACKGROUND: Highly fragmented ambulatory care (i.e., care spread across many providers without a dominant provider) has been associated with excess tests, procedures, emergency department visits, and hospitalizations. Whether fragmented care is associated with worse health outcomes, or whether any association varies with health status, is unclear. OBJECTIVE: To determine whether fragmented care is associated with the risk of incident coronary heart disease (CHD) events, overall and stratified by self-rated general health. DESIGN AND PARTICIPANTS: We conducted a secondary analysis of the nationwide prospective Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort study (2003-2016). We included participants who were ≥ 65 years old, had linked Medicare fee-for-service claims, and had no history of CHD (N = 10,556). MAIN MEASURES: We measured fragmentation with the reversed Bice-Boxerman Index. We used Cox proportional hazards models to determine the association between fragmentation as a time-varying exposure and adjudicated incident CHD events in the 3 months following each exposure period. KEY RESULTS: The mean age was 70 years; 57% were women, and 34% were African-American. Over 11.8 years of follow-up, 569 participants had CHD events. Overall, the adjusted hazard ratio (HR) for the association between high fragmentation and incident CHD events was 1.14 (95% confidence interval (CI) 0.92, 1.39). Among those with very good or good self-rated health, high fragmentation was associated with an increased hazard of CHD events (adjusted HR 1.35; 95% CI 1.06, 1.73; p = 0.01). Among those with fair or poor self-rated health, high fragmentation was associated with a trend toward a decreased hazard of CHD events (adjusted HR 0.54; 95% CI 0.29, 1.01; p = 0.052). There was no association among those with excellent self-rated health. CONCLUSION: High fragmentation was associated with an increased independent risk of incident CHD events among those with very good or good self-rated health.

Healthcare fragmentation and cardiovascular risk control among older cancer survivors in the Reasons for Geographic And Racial Differences in Stroke (REGARDS) study.

PURPOSE: Cardiovascular disease (CVD) is the number one cause of death among 5-year cancer survivors. Survivors see many providers and poor coordination may contribute to worse CVD risk factor control. We sought to determine associations between fragmentation and CVD risk factor control among survivors overall and by self-rated health. METHODS: We included REGARDS participants aged 66+ years who (1) had a cancer history; (2) reported diabetes, hypertension, or hyperlipidemia; and (3) had continuous Medicare coverage. Twelve-month ambulatory care fragmentation was calculated using the Bice-Boxerman Index (BBI). We determined associations between fragmentation and CVD risk factors, defining "control" as fasting glucose < 126 mg/dL or non-fasting glucose < 200 mg/dL for diabetes; blood pressure < 140/90 mmHg for hypertension; and total cholesterol <240 mg/dL, low-density lipoprotein cholesterol < 160 mg/dL, or high-density lipoprotein cholesterol >40 mg/dL for hyperlipidemia. RESULTS: The 1002 cancer survivors (2+ years since cancer treatment) had mean age of 75 years, 39% were women, and 23% were Black. Among individuals with diabetes (N = 225), hypertension (N = 660), and hyperlipidemia (N = 516), separately, approximately 60% had CVD risk factor control. Overall, more fragmented care was not associated with worse control. However, among cancer survivors with excellent, very good, or good health, more fragmentation was associated with a decreased likelihood of diabetes control (OR 0.78, 95% CI 0.61-0.99), adjusting for confounders. CONCLUSIONS: More fragmented care was associated with worse glycemic control among cancer survivors with diabetes who reported excellent, very good, or good health. Associations were not observed for control of hypertension or hyperlipidemia. IMPLICATIONS FOR CANCER SURVIVORS: Reducing fragmentation may support glucose control among survivors with diabetes.

Number of Social Determinants of Health and Fatal and Nonfatal Incident Coronary Heart Disease in the REGARDS Study.

BACKGROUND: Social determinants of health (SDH) are individually associated with incident coronary heart disease (CHD) events. Indices reflecting social deprivation have been developed for population management, but are difficult to operationalize during clinical care. We examined whether a simple count of SDH is associated with fatal incident CHD and nonfatal myocardial infarction (MI). METHODS: We used data from the prospective longitudinal REGARDS cohort study (Reasons for Geographic and Racial Differences in Stroke), a national population-based sample of community-dwelling Black and White adults age ≥45 years recruited from 2003 to 2007. Seven SDH from the 5 Healthy People 2020 domains included social context (Black race, social isolation); education (educational attainment); economic stability (annual household income); neighborhood (living in a zip code with high poverty); and health care (lacking health insurance, living in 1 of the 9 US states with the least public health infrastructure). Outcomes were expert adjudicated fatal incident CHD and nonfatal MI. RESULTS: Of 22 152 participants free of CHD at baseline, 58.8% were women and 42.0% were Black; 20.6% had no SDH, 30.6% had 1, 23.0% had 2, and 25.8% had ≥3. There were 463 fatal incident CHD events and 932 nonfatal MIs over a median of 10.7 years (interquartile range, 6.6 to 12.7). Fewer SDHs were associated with nonfatal MI than with fatal incident CHD. The age-adjusted incidence per 1000 person-years increased with the number of SDH for both fatal incident CHD (0 SDH, 1.30; 1 SDH, 1.44; 2 SDH, 2.05; ≥3 SDH, 2.86) and nonfatal MI (0 SDH, 3.91; 1 SDH, 4.33; ≥2 SDH, 5.44). Compared with those without SDH, crude and fully adjusted hazard ratios for fatal incident CHD among those with ≥3 SDH were 3.00 (95% CI, 2.17 to 4.15) and 1.67 (95% CI, 1.18 to 2.37), respectively; hazard ratios for nonfatal MI among those with ≥2 SDH were 1.57 (95% CI, 1.30 to 1.90) and 1.14 (95% CI, 0.93 to 1.41), respectively. CONCLUSIONS: A greater burden of SDH was associated with a graded increase in risk of incident CHD, with greater magnitude and independent associations for fatal incident CHD. Counting the number of SDHs may be a promising approach that could be incorporated into clinical care to identify individuals at high risk of CHD.

Ambulatory Care Fragmentation and Subsequent Hospitalization: Evidence From the REGARDS Study.

BACKGROUND: Previous studies have suggested that highly fragmented ambulatory care increases the risk of subsequent hospitalization, but those studies used claims only and were not able to adjust for many clinical potential confounders. OBJECTIVE: The objective of this study was to determine the association between fragmented ambulatory care and subsequent hospitalization, adjusting for demographics, medical conditions, medications, health behaviors, psychosocial variables, and physiological variables. DESIGN: Longitudinal analysis of data (2003-2016) from the nationwide REasons for Geographic And Racial Differences in Stroke (REGARDS) study, linked to Medicare fee-for-service claims. SUBJECTS: A total of 12,693 Medicare beneficiaries 65 years and older from the REGARDS study who had at least 4 ambulatory visits in the first year of observation and did not have a hospitalization in the prior year. MEASURES: We defined high fragmentation as a reversed Bice-Boxerman score above the 75th percentile. We used Cox proportional hazards models to determine the association between fragmentation as a time-varying exposure and incident hospitalization in the 3 months following each exposure period. RESULTS: The mean age was 70.4 years; 54% were women, and 33% were African American. During the first year of observation, participants with high fragmentation had a median of 8 ambulatory visits with 6 providers, whereas participants with low fragmentation had a median of 7 visits with 3 providers. Over 11.8 years of follow-up, 6947 participants (55%) had a hospitalization. High fragmentation was associated with an increased hazard of hospitalization (adjusted hazard ratio=1.18; 95% confidence interval: 1.12, 1.24). CONCLUSION: Highly fragmented ambulatory care is an independent risk factor for hospitalization.

Implementation of Video Visits During COVID-19: Lessons Learned From a Primary Care Practice in New York City.

Background: During the height of the coronavirus (COVID-19) pandemic, there was an unprecedented demand for "virtual visits," or ambulatory visits conducted via video interface, in order to decrease the risk of transmission. Objective: To describe the implementation and evaluation of a video visit program at a large, academic primary care practice in New York, NY, the epicenter of the COVID-19 pandemic. Design and participants: We included consecutive adults (age > 18) scheduled for video visits from March 16, 2020 to April 17, 2020 for COVID-19 and non-COVID-19 related complaints. Intervention: New processes were established to prepare the practice and patients for video visits. Video visits were conducted by attendings, residents, and nurse practitioners. Main measures: Guided by the RE-AIM Framework, we evaluated the Reach, Effectiveness, Adoption, and Implementation of video visits. Key results: In the 4 weeks prior to the study period, 12 video visits were completed. During the 5-weeks study period, we completed a total of 1,030 video visits for 817 unique patients. Of the video visits completed, 42% were for COVID-19 related symptoms, and the remainder were for other acute or chronic conditions. Video visits were completed more often among younger adults, women, and those with commercial insurance, compared to those who completed in-person visits pre-COVID (all p < 0.0001). Patients who completed video visits reported high satisfaction (mean 4.6 on a 5-point scale [SD: 0.97]); 13.3% reported technical challenges during video visits. Conclusions: Video visits are feasible for the delivery of primary care for patients during the COVID-19 pandemic.

Polypharmacy in Older Adults Hospitalized for Heart Failure.

BACKGROUND: Despite potential harm that can result from polypharmacy, real-world data on polypharmacy in the setting of heart failure (HF) are limited. We sought to address this knowledge gap by studying older adults hospitalized for HF derived from the REGARDS study (Reasons for Geographic and Racial Differences in Stroke). METHODS: We examined 558 older adults aged ≥65 years with adjudicated HF hospitalizations from 380 hospitals across the United States. We collected and examined data from the REGARDS baseline assessment, medical charts from HF-adjudicated hospitalizations, the American Hospital Association annual survey database, and Medicare's Hospital Compare website. We counted the number of medications taken at hospital admission and discharge; and classified each medication as HF-related, non-HF cardiovascular-related, or noncardiovascular-related. RESULTS: The vast majority of participants (84% at admission and 95% at discharge) took ≥5 medications; and 42% at admission and 55% at discharge took ≥10 medications. The prevalence of taking ≥10 medications (polypharmacy) increased over the study period. As the number of total medications increased, the number of noncardiovascular medications increased more rapidly than the number of HF-related or non-HF cardiovascular medications. CONCLUSIONS: Defining polypharmacy as taking ≥10 medications might be more ideal in the HF population as most patients already take ≥5 medications. Polypharmacy is common both at admission and hospital discharge, and its prevalence is rising over time. The majority of medications taken by older adults with HF are noncardiovascular medications. There is a need to develop strategies that can mitigate the negative effects of polypharmacy among older adults with HF.

COVID-19 Severity and Outcomes in Patients With Cancer: A Matched Cohort Study.

PURPOSE: SARS-CoV-2 (COVID-19) is a systemic infection. Patients with cancer are immunocompromised and may be vulnerable to COVID-related morbidity and mortality. The objectives of this study were to determine if patients with cancer have worse outcomes compared with patients without cancer and to identify demographic and clinical predictors of morbidity and mortality among patients with cancer. METHODS: We used data from adult patients who tested positive for COVID-19 and were admitted to two New York-Presbyterian hospitals between March 3 and May 15, 2020. Patients with cancer were matched 1:4 to controls without cancer in terms of age, sex, and number of comorbidities. Using Kaplan-Meier curves and the log-rank test, we compared morbidity (intensive care unit admission and intubation) and mortality outcomes between patients with cancer and controls. Among those with cancer, we identified demographic and clinical predictors of worse outcomes using Cox proportional hazard models. RESULTS: We included 585 patients who were COVID-19 positive, of whom 117 had active malignancy, defined as those receiving cancer-directed therapy or under active surveillance within 6 months of admission. Presenting symptoms and in-hospital complications were similar between the cancer and noncancer groups. Nearly one half of patients with cancer were receiving therapy, and 45% of patients received cytotoxic or immunosuppressive treatment within 90 days of admission. There were no statistically significant differences in morbidity or mortality (P = .894) between patients with and without cancer. CONCLUSION: We observed that patients with COVID-19 and cancer had similar outcomes compared with matched patients without cancer. This finding suggests that a diagnosis of active cancer alone and recent anticancer therapy do not predict worse COVID-19 outcomes and therefore, recommendations to limit cancer-directed therapy must be considered carefully in relation to cancer-specific outcomes and death.