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.

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.

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.

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.

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.

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.

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.

Impact of Multiple Social Determinants of Health on Incident Stroke.

BACKGROUND AND PURPOSE: Social determinants of health (SDOH) have been previously associated with incident stroke. Although SDOH often cluster within individuals, few studies have examined associations between incident stroke and multiple SDOH within the same individual. The objective was to determine the individual and cumulative effects of SDOH on incident stroke. METHODS: This study included 27 813 participants from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) Study, a national, representative, prospective cohort of black and white adults aged ≥45 years. SDOH was the primary exposure. The main outcome was expert adjudicated incident stroke. Cox proportional hazards models examined associations between incident stroke and SDOH, individually and as a count of SDOH, adjusting for potential confounders. RESULTS: The mean age was 64.7 years (SD 9.4) at baseline; 55.4% were women and 40.4% were blacks. Over a median follow-up of 9.5 years (IQR, 6.0-11.5), we observed 1470 incident stroke events. Of 10 candidate SDOH, 7 were associated with stroke (P<0.10): race, education, income, zip code poverty, health insurance, social isolation, and residence in one of the 10 lowest ranked states for public health infrastructure. A significant age interaction resulted in stratification at 75 years. In fully adjusted models, among individuals <75 years, risk of stroke rose as the number of SDOH increased (hazard ratio for one SDOH, 1.26 [95% CI, 1.02-1.55]; 2 SDOH hazard ratio, 1.38 [95% CI, 1.12-1.71]; and ≥3 SDOH hazard ratio, 1.51 [95% CI, 1.21-1.89]) compared with those without any SDOH. Among those ≥75 years, none of the observed effects reached statistical significance. CONCLUSIONS: Incremental increases in the number of SDOH were independently associated with higher incident stroke risk in adults aged <75 years, with no statistically significant effects observed in individuals ≥75 years. Targeting individuals with multiple SDOH may help reduce risk of stroke among vulnerable populations.

Differences in ambulatory care fragmentation between cancer survivors and noncancer controls.

BACKGROUND: Patients with chronic conditions are treated by many providers, which can increase the risk of communication gaps across providers and potential harm to patients. However, to the authors' knowledge, the extent of fragmented care among this population is unknown. In the current study, the authors sought to determine whether cancer survivors have more fragmented care than noncancer controls and to quantify the extent of fragmentation. METHODS: Data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study linked to Medicare claims were used. The authors included beneficiaries with continuous Part A and B coverage for 12 months at the time of their baseline REGARDS survey. The primary outcome of the current study was claims-based fragmentation over 12 months, which was calculated using the reversed Bice-Boxerman Index so a higher score reflected greater fragmentation. Unadjusted differences in fragmentation were compared between cancer survivors and controls. Beta regression models were used to estimate associations between cancer status and fragmentation, adjusting for potential confounders. RESULTS: The authors included 4922 participants aged ≥65 years at baseline. Of these patients, approximately 21% were cancer survivors. Survivors had a median of 11 visits (interquartile range, 7-15 visits) with 5 providers compared with controls, who had a median of 9 visits (interquartile range, 6-14 visits) with 4 providers (P < .0001). Cancer survivors had significantly more fragmented care compared with controls (median reversed Bice-Boxerman Index, 0.80 vs 0.76; P < .0001). After adjusting for confounders, cancer survivors had an increased odds of having fragmented care (odds ratio, 1.08; 95% CI, 1.02-1.14). CONCLUSIONS: Care fragmentation is more prevalent among cancer survivors compared with those without a history of cancer. Future studies should examine whether fragmentation puts survivors at risk of worse outcomes.

Association Between Patients' Self-Reported Gaps in Care Coordination and Preventable Adverse Outcomes: a Cross-Sectional Survey.

BACKGROUND: Whether patients' reports of gaps in care coordination reflect clinically significant problems is unclear. OBJECTIVE: To determine any association between patient-reported gaps in care coordination and patient-reported preventable adverse outcomes. DESIGN AND PARTICIPANTS: We administered a cross-sectional survey on experiences with healthcare to participants in the national Reasons for Geographic and Racial Differences in Stroke (REGARDS) study who were ≥ 65 years old. Of the 15,817 participants in REGARDS at the time of our survey (August 2017-November 2018), 11,138 completed the survey. We restricted the sample to participants who reported ≥ 2 ambulatory visits and ≥ 2 ambulatory providers in the past year (N = 7568). MAIN MEASURES: We considered 7 gaps in ambulatory care coordination, elicited with previously validated questions. We considered 4 outcomes: (1) a test that was repeated because the doctor did not have the result of the first test, (2) a drug-drug interaction that occurred due to multiple prescribers, (3) an emergency department visit that could have been prevented by better communication among providers, and (4) a hospital admission that could have been prevented by better communication among providers. We used logistic regression to determine the association between ≥ 1 gap in care coordination and ≥ 1 preventable outcome, adjusting for potential confounders. KEY RESULTS: The average age of the sample was 77.0 years; 55% were female, and 34% were African-American. More than one-third of participants (38.1%) reported ≥ 1 gap in care coordination and nearly one-tenth (9.8%) reported ≥ 1 preventable outcome. Having ≥ 1 gap in care coordination was associated with an increased odds of ≥ 1 preventable outcome (adjusted odds ratio 1.55; 95% confidence interval 1.33, 1.81). CONCLUSIONS: Participants' reports of gaps in care coordination were associated with an increased odds of preventable adverse outcomes. Future interventions should leverage patients' observations to detect and resolve gaps in care coordination.

Using health-related quality of life to predict cardiovascular disease events.

PURPOSE: Although strong associations between self-reported health and mortality exist, quality of life is not conceptualized as a cardiovascular disease (CVD) risk factor. Our objective was to assess the independent association between health-related quality of life (HRQOL) and incident CVD. METHODS: This study used the REasons for Geographic And Racial Differences in Stroke data, which enrolled 30,239 adults from 2003 to 2007 and followed them over 10 years. We included 22,229 adults with no CVD history at baseline. HRQOL was measured using the SF-12 Physical Component Summary (PCS) and Mental Component Summary (MCS) scores, which range from 0 to 100, with higher scores indicating better HRQOL. Scores were normed to the general US population with mean 50 and standard deviation 10. We constructed a four-level HRQOL variable: (1) individuals with PCS & MCS < 50, (2) PCS < 50 & MCS ≥ 50, (3) MCS < 50 & PCS ≥ 50, and (4) PCS & MCS ≥ 50, which was the reference. The primary outcome was incident CVD (non-fatal myocardial infarction (MI), fatal MI or coronary heart disease (CHD) death, fatal and non-fatal stroke). Cox proportional hazards models examined associations between HRQOL and CVD. RESULTS: Median follow-up was 8.4 (IQR 5.9-10.0) years. We observed 1766 CVD events. Compared to having PCS & MCS ≥ 50, having MCS & PCS < 50 was associated with increased CVD risk (aHR 1.46; 95% 1.24-1.70), adjusting for demographics, comorbidities, and CVD risk factors. Associations between MCS & PCS < 50 and CVD were consistent for CHD (aHR 1.54 [1.26-1.89]) and stroke (aHR 1.35 [1.05-1.72]) endpoints. CONCLUSIONS: Given strong, adjusted associations between poor HRQOL and incident CVD, self-reported health may be an excellent complement to current approaches to CVD risk identification.

Full Information Maximum Likelihood Estimation for Latent Variable Interactions With Incomplete Indicators.

Researchers have developed missing data handling techniques for estimating interaction effects in multiple regression. Extending to latent variable interactions, we investigated full information maximum likelihood (FIML) estimation to handle incompletely observed indicators for product indicator (PI) and latent moderated structural equations (LMS) methods. Drawing on the analytic work on missing data handling techniques in multiple regression with interaction effects, we compared the performance of FIML for PI and LMS analytically. We performed a simulation study to compare FIML for PI and LMS. We recommend using FIML for LMS when the indicators are missing completely at random (MCAR) or missing at random (MAR) and when they are normally distributed. FIML for LMS produces unbiased parameter estimates with small variances, correct Type I error rates, and high statistical power of interaction effects. We illustrated the use of these methods by analyzing the interaction effect between advanced cancer patients' depression and change of inner peace well-being on future hopelessness levels.

Using Marginal Structural Modeling for Grade Retention Effects.

Vandecandelaere, Vansteelandt, De Fraine, and Van Damme (this issue) described marginal structural modeling (MSM) and used it to estimate the effects of a time-varying intervention, retention (holding back) in school grades, on students' math achievement. This commentary supplements Vandecandelaere et al. (this issue) and discusses several topics in retention studies and MSM. First, we discuss the importance of equating time-varying confounders in retention studies. Second, we discuss same-grade and same-age comparisons in retention studies. Third, we discuss one important section in the authors' overview of MSM: why standard methods (e.g., ANCOVA, propensity score analysis) cannot properly adjust for time-varying confounders. Finally, using the grade retention analyses in Vandecandelaere et al. (this issue) as an example, we provide our insights on four aspects of MSM: (a) covariate selection, (b) estimation of weights,

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.

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.

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.

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.

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.