Prevalence, Demographic, and Clinical Factors Associated With Cognitive Dysfunction in Patients With Neuromyelitis Optica Spectrum Disorder.

BACKGROUND AND OBJECTIVES: Neuromyelitis optica spectrum disorder (NMOSD) is a chronic CNS demyelinating autoimmune disorder targeting the astrocyte antigen aquaporin-4 (AQP4), typically presenting with optic neuritis, transverse myelitis, and brain syndromes. Cognitive dysfunction (CD) in NMOSD is under-recognized and poorly understood. The purpose of this study was to evaluate the prevalence and clinical variables associated with CD in NMOSD. METHODS: This observational retrospective study with longitudinal follow-up describes a clinical cohort seen in the Collaborative International Research in Clinical and Longitudinal Experience Study in NMOSD. Serial Montreal Cognitive Assessments (MoCAs) were performed upon enrollment and at 6-month intervals to evaluate longitudinal cognitive function relative to demographic and disease-related factors. We used 2-tailed t test, analysis of variance, the χ2 test, linear regression for univariable and adjusted analyses and simultaneous linear regression and mixed-effects model for multivariable analyses. RESULTS: Thirty-four percent (75/219) of patients met criteria for CD (MoCA <26); 29% (64/219) showed mild dysfunction (MoCA 20-26/30), and 5% (11/219) showed moderate (MoCA <20/30) dysfunction. Patients with less neurologic disability and lower pain scores had higher MoCA scores (95% CI 0.24-0.65 and 95% CI 0.09-0.42, respectively). Patients with at least high school education scored higher on the MoCA (95% CI 2.2-5). When comparing patients dichotomized for CD, patients never on rituximab scored higher than patients only treated with rituximab (p < 0.029). There was no significant association between annualized relapse rate, age, sex, disease duration, AQP4 serostatus or brain lesions, and CD. CD was more pronounced among Black than White patients (95% CI -2.7 to -0.7). Multivariable analysis of serial MoCA did not indicate change (p = 0.715). Descriptive analysis of serial MoCA showed 30% (45/150) of patients with worsening MoCA performance had impaired language and verbal recall. DISCUSSION: To our knowledge, this is the largest study of diverse cohort to investigate CD in patients with NMOSD. Our findings demonstrate 34% of patients with NMOSD experience mild-to-moderate CD, while 30% of patients demonstrated decline on serial testing. The substantial prevalence of CD in this pilot report highlights the need for improved and validated screening tools and comprehensive measures to investigate CD in NMOSD.

Bringing Micro to the Macro: How Citizen Science Data Enrich Geospatial Visualizations to Advance Health Equity.

Social and spatial contexts affect health, and understanding nuances of context is key to informing successful interventions for health equity. Layering mixed methods and mixed scale data sources to visualize patterns of health outcomes facilitates analysis of both broad trends and person-level experiences across time and space. We used micro-scale citizen scientist-collected data from four Bay Area communities along with aggregate epidemiologic and population-level data sets to illustrate barriers to, and facilitators of, physical activity in low-income aging adults. These data integrations highlight the synergistic value added by combining data sources, and what might be missed by relying on either a micro- or macro-level data source alone. Mixed methods and granularity data integration can generate a deeper understanding of environmental context, which in turn can inform more relevant and attainable community, advocacy, and policy improvements.

Hybrid Controlled Clinical Trials Using Concurrent Registries in Amyotrophic Lateral Sclerosis: A Feasibility Study.

Hybrid designs with both randomized arms and an external control cohort preserve key features of randomization and utilize external information to augment clinical trials. In this study, we propose to leverage high-quality, patient-level concurrent registries to enhance clinical trials and illustrate the impact on trial design for amyotrophic lateral sclerosis. The proposed methodology was evaluated in a randomized, placebo-controlled clinical trial. We used patient-level information from a well-defined, population-based registry, that was running parallel to the randomized clinical trial, to identify concurrently nonparticipating, eligible patients who could be matched with trial participants, and integrate them into the statistical analysis. We assessed the impact of the addition of the external controls on the treatment effect estimate, precision, and time to reach a conclusion. During the runtime of the trial, a total of 1,141 registry patients were alive; 473 (41.5%) of them fulfilled the eligibility criteria and 133 (11.7%) were enrolled in the study. A matched control population could be identified among the nonparticipating patients. Augmenting the randomized controls with matched external controls could have avoided unnecessary randomization of 17 patients (-12.8%) as well as reducing the study duration from 30.1 months to 22.6 months (-25.0%). Matching eligible external controls from a different calendar period led to bias in the treatment effect estimate. Hybrid trial designs utilizing a concurrent registry with rigorous matching can minimize bias due to a mismatch in calendar time and differences in standard of care, and may accelerate the development of new treatments.

Population-Based Estimates for the Prevalence of Multiple Sclerosis in the United States by Race, Ethnicity, Age, Sex, and Geographic Region.

Importance: Racial, ethnic, and geographic differences in multiple sclerosis (MS) are important factors to assess when determining the disease burden and allocating health care resources. Objective: To calculate the US prevalence of MS in Hispanic, non-Hispanic Black (hereafter referred to as Black), and non-Hispanic White individuals (hereafter referred to as White) stratified by age, sex, and region. Design, Setting, and Participants: A validated algorithm was applied to private, military, and public (Medicaid and Medicare) administrative health claims data sets to identify adult cases of MS between 2008 and 2010. Data analysis took place between 2019 and 2022. The 3-year cumulative prevalence overall was determined in each data set and stratified by age, sex, race, ethnicity, and geography. The insurance pools included 96 million persons from 2008 to 2010. Insurance and stratum-specific estimates were applied to the 2010 US Census data and the findings combined to calculate the 2010 prevalence of MS cumulated over 10 years. No exclusions were made if a person met the algorithm criteria. Main Outcomes and Measurements: Prevalence of MS per 100 000 US adults stratified by demographic group and geography. The 95% CIs were approximated using a binomial distribution. Results: A total of 744 781 persons 18 years and older were identified with MS with 564 426 cases (76%) in females and 180 355 (24%) in males. The median age group was 45 to 54 years, which included 229 216 individuals (31%), with 101 271 aged 18 to 24 years (14%), 158 997 aged 35 to 44 years (21%), 186 758 aged 55 to 64 years (25%), and 68 539 individuals (9%) who were 65 years or older. White individuals were the largest group, comprising 577 725 cases (77%), with 80 276 Black individuals (10%), 53 456 Hispanic individuals (7%), and 33 324 individuals (4%) in the non-Hispanic other category. The estimated 2010 prevalence of MS per 100 000 US adults cumulated over 10 years was 161.2 (95% CI, 159.8-162.5) for Hispanic individuals (regardless of race), 298.4 (95% CI, 296.4-300.5) for Black individuals, 374.8 (95% CI, 373.8-375.8) for White individuals, and 197.7 (95% CI, 195.6-199.9) for individuals from non-Hispanic other racial and ethnic groups. During the same time period, the female to male ratio was 2.9 overall. Age stratification in each of the racial and ethnic groups revealed the highest prevalence of MS in the 45- to 64-year-old age group, regardless of racial and ethnic classification. With each degree of latitude, MS prevalence increased by 16.3 cases per 100 000 (95% CI, 12.7-19.8; P < .001) in the unadjusted prevalence estimates, and 11.7 cases per 100 000 (95% CI, 7.4-16.1; P < .001) in the direct adjusted estimates. The association of latitude with prevalence was strongest in women, Black individuals, and older individuals. Conclusions and Relevance: This study found that White individuals had the highest MS prevalence followed by Black individuals, individuals from other non-Hispanic racial and ethnic groups, and Hispanic individuals. Inconsistent racial and ethnic classifications created heterogeneity within groups. In the United States, MS affects diverse racial and ethnic groups. Prevalence of MS increases significantly and nonuniformly with latitude in the United States, even when adjusted for race, ethnicity, age, and sex. These findings are important for clinicians, researchers, and policy makers.

Prevalence of amyotrophic lateral sclerosis in the United States using established and novel methodologies, 2017.

Objective:To estimate the prevalence of amyotrophic lateral sclerosis (ALS) in the United States for 2017 using data from the National ALS Registry (Registry) as well as capture-recapture methodology to account for under-ascertainment. Established in 2010, the Registry collects and examines data on ALS patients in the US to better describe the epidemiology of ALS (i.e. risk factor exposures, demographics).Methods: The Registry compiled data from national administrative databases (from the Centers for Medicare and Medicaid Services, the Veterans Health Administration, and the Veterans Benefits Administration) and a voluntary enrollment data through a web portal (www.cdc.gov/als). To estimate the number of missing cases, capture-recapture methodology was utilized.Results: The Registry conservatively identified 17,800 adult persons (lower-bound estimate) who met the Registry definition of ALS for an age-adjusted prevalence of 5.5 per 100,000 US population. Using capture-recapture methodology, we obtained a "mean case count" of 24,821 ALS cases (prevalence of 7.7 per 100,000 U.S. population) and estimated the upper-bound estimate to be 31,843 cases (prevalence of 9.9 per 100,000 U.S. population). The pattern of patient characteristics (e.g. age, sex, and race/ethnicity) remained unchanged from previous Registry reports. Overall, ALS was most common among whites, males, and persons aged 60-69 years. The age groups with the lowest number of cases were persons aged 18-39 years. Males had a higher prevalence than females overall and across all data sources.Conclusions: Existing Registry methodology, along with capture-recapture methodology, are being used to better describe the epidemiology and demographics of ALS in the US.

Telemedicine Utilization Among Patients With Multiple Sclerosis in the US Veterans Health Administration, 2010-2020.

Background and Objectives: Telemedicine may help to bridge the specialty care access gap for patients with MS (PwMS) restricted by distance or disability. The objective of this study is to assess the frequency and longitudinal patterns of telemedicine utilization among PwMS and controls. Methods: We conducted a population-based nested case-control study within the Veterans Health Administration (VHA) from January 1, 2010, to December 31, 2020. MS cases and controls were individually matched on sex, age, and Veterans Affair (VA) service region (Veterans Integrated Service Network). MS case and control participants sample sizes by year included 2010: 19,387/86,379; 2016: 19,752/88,535; and 2020: 16,451/78,315. Telemedicine encounter codes were used to identify telemedicine utilization among MS cases and controls in the VHA for 2010, 2016, and 2020. Telemedicine encounters were categorized according to mode (video, phone, and supplementary remote) and type of care provided. Results: Patients in the VHA have had increasing utilization of telemedicine over the past decade. Among PwMS, mean telemedicine encounters increased steadily from 2010 to 2020 (5.6-10.5 encounters/patient, respectively). Across all years, MS cases were significantly more likely than controls to use telemedicine. The odds ratios (ORs) (95% confidence interval [CI]) of any telemedicine utilization comparing MS cases with controls in 2010, 2016, and 2020, respectively, were 1.5 (CI: 1.3-1.5), 1.9 (CI: 1.8-2.0), and 1.7 (CI: 1.6-1.8). Compared with non-Hispanic White veterans, non-Hispanic Black veterans were more likely to use telemedicine (adjusted OR = 1.5; [CI: 1.40-1.60]). The most common and least common modes of telemedicine among cases and controls were telephone and supplementary remote, respectively. Comparing 2010 with 2020, the largest increases in telemedicine utilization exhibited among MS cases were among primary care, specialty care, specialty neurology care, and other types of health care. States with the highest increases in telemedicine utilization were AL, CA, CO, FL, GA, KS, IL, NY, and SC. PwMS tended to live in counties with more adverse social determinants of health compared with controls. Discussion: PwMS were significantly more likely to use telemedicine than their matched controls. There were significant increases in telemedicine utilization between 2010 and 2020. The VHA has a robust telemedicine system of care that has grown to supplement in person care more so than other US health care systems. Future work is needed to assess the determinants of telemedicine utilization.

Cardiovascular Diseases, Medications, and ALS: A Population-Based Case-Control Study.

INTRODUCTION: We investigated the associations between antecedent all-cause CVD diagnoses, cause-specific CVD diagnosis, and CVD medication prescriptions with the risk of developing amyotrophic lateral sclerosis (ALS). MATERIALS AND METHODS: We conducted a population-based case-control study of U.S. Medicare enrollees from 2006 to 2013. The final sample included 3,714 incident ALS cases and 18,570 controls (matched on age, sex, enrollment length, and county). Information was collected from Medicare Parts A, B, and D administrative claims data on hypertension, ischemic heart disease, heart failure, acute myocardial infarction, atrial fibrillation, prescriptions of angiotensin-converting enzyme inhibitors, angiotensin II receptors blockers, calcium channel blockers, beta blockers, and antiarrhythmics. Associations were evaluated using conditional logistic regression adjusting for age, sex, race/ethnicity, geographical location, alcohol and tobacco use, and socioeconomic status. RESULTS: The odds ratio (OR) for having one or more ICD-9 codes for any cardiovascular disease diagnosis at least 24 months prior to the date of ALS diagnosis was 0.85 (95% confidence interval [CI]: 0.78-0.92). Cardiovascular conditions that were inversely associated with ALS included heart failure (OR = 0.79; 95% CI 0.70-0.89), atrial fibrillation (OR = 0.81; 95% CI 0.77-0.92), and hypertension (OR = 0.91; 95% CI 0.84-0.98). Exposures to several classes of cardiovascular medications were inversely associated with ALS risk even after adjusting for confounding by indication, including ACE inhibitors (OR = 0.84, 95% CI 0.77-0.91), calcium channel blockers (OR = 0.64, 95% CI 0.59-0.70), and beta blockers (OR = 0.76, 95% CI 0.71-0.83). DISCUSSION/CONCLUSION: These findings merit additional research, including animal studies and pilot clinical trials, to further evaluate and evidence the effects of ACEIs, CCBs, and BBs on the risk of developing and clinical expression of ALS.

Association of cannabis and/or opioid with quality of life and healthcare utilization in patients with chronic pain.

Background: Opioids have been commonly used to treat chronic pain, but they are associated with significant morbidity and mortality. Cannabis has been advocated as an alternative; however, a growing number of patients are now using a combination of opioid and cannabis and the impact of this combination is not well-studied. Aim: We characterized use of opioid and/or cannabis in patients with chronic pain; and compared utilization of healthcare resources. Methods: We conducted a cross-sectional study to determine if measures of physical, psychological and social functioning differed among patients according to whether they used opioids and/or cannabis. We used our learning healthcare system - CHOIR - to capture NIH Patient Reported Outcomes Measure Information System surveys, and legacy pain and treatment specific questions. Results: Patients who report use of opioid and/or cannabis experience higher levels of physical, psychological and social distress. After adjusting for inversed weight of propensity scores, they have higher odds of visiting an emergency room, staying overnight at the hospital, and visiting a physician. Conclusion: Our results show that use of opioid and/or cannabis is associated with worse baseline characteristics and outcomes. Our study however cannot determine if worse outcomes are due to the opioids and/or cannabis or simply that these patients are worse off before using opioids and/or cannabis. Thus, it is important to characterize the trajectory of these patients in a prospective longitudinal study.

Research gaps and opportunities in precision nutrition: an NIH workshop report.

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered many aspects of genetics and physiology that mediate the links between nutrient intake and health conditions such as cardiovascular disease, Alzheimer disease, and cancer; part II reviewed potential contributors to interindividual variability in dietary exposures and responses such as baseline nutritional status, circadian rhythm/sleep, environmental exposures, sensory properties of food, stress, inflammation, and the social determinants of health; part III presented the need for systems approaches, with new methods and technologies that can facilitate the study and implementation of precision nutrition, and workforce development needed to create a new generation of researchers. The workshop concluded that much research will be needed before more precise nutrition recommendations can be achieved. This includes better understanding and accounting for variables such as age, sex, ethnicity, medical history, genetics, and social and environmental factors. The advent of new methods and technologies and the availability of considerably more data bring tremendous opportunity. However, the field must proceed with appropriate levels of caution and make sure the factors listed above are all considered, and systems approaches and methods are incorporated. It will be important to develop and train an expanded workforce with the goal of reducing health disparities and improving precision nutritional advice for all Americans.

Mortality Among Parkinson's Disease Patients Treated With Pimavanserin or Atypical Antipsychotics: An Observational Study in Medicare Beneficiaries.

OBJECTIVE: Pimavanserin, a serotonin 5-HT2 antagonist, is indicated for treatment of hallucinations and delusions associated with Parkinson's disease psychosis. In premarketing trials in patients with Parkinson's disease psychosis, 11% of patients died during open-label pimavanserin treatment. Antipsychotics, which are used off-label in Parkinson's disease psychosis, increase mortality in dementia patients. The authors compared mortality with pimavanserin and atypical antipsychotics in a large database. METHODS: This was a retrospective new-user cohort study of Medicare beneficiaries with Parkinson's disease initiating pimavanserin (N=3,227) or atypical antipsychotics (N=18,442) from April 2016 to March 2019. All-cause mortality hazard ratios and 95% confidence intervals were estimated for pimavanserin compared with atypical antipsychotics, using segmented proportional hazards regression over 1-180 and 181+ days of treatment. Potential confounding was addressed through inverse probability of treatment weighting (IPTW). RESULTS: Pimavanserin users had a mean age of approximately 78 years, and 45% were female. Before IPTW, some comorbidities were more prevalent in atypical antipsychotic users; after IPTW, comorbidities were well balanced between groups. In the first 180 days of treatment, mortality was approximately 35% lower with pimavanserin than with atypical antipsychotics (hazard ratio=0.65, 95% CI=0.53, 0.79), with approximately one excess death per 30 atypical antipsychotic-treated patients; however, during treatment beyond 180 days, there was no additional mortality advantage with pimavanserin (hazard ratio=1.05, 95% CI=0.82, 1.33). Pimavanserin showed no mortality advantage in nursing home patients. CONCLUSIONS: Pimavanserin use was associated with lower mortality than atypical antipsychotic use during the first 180 days of treatment, but only in community-dwelling patients, not nursing home residents.

Racial and Ethnic Disparities in Multiple Sclerosis Prevalence.

BACKGROUND AND OBJECTIVES: The goal of this work was to determine whether the prevalence of multiple sclerosis (MS) varies by race and ethnicity. METHODS: We conducted a retrospective cohort study of >2.6 million adults from the multiethnic, community-dwelling members of Kaiser Permanente Southern California. The complete electronic health records of individuals with at least 1 ICD-9 code for MS between January 1, 2008 and December 31, 2010 were reviewed. MS prevalence and 95% CIs stratified by age, sex, and race and ethnicity among 2010 members were estimated with binomial regression. Age- and sex-standardized prevalence was estimated according to the 2010 US Census population. RESULTS: We identified 3,863 patients with MS. The average age of patients with prevalent MS was 51.7 years (SD 13.1 years), and 76.8% were women. The female preponderance was more pronounced among Black (81.2%) and Asian (83.6%) than White (76.3%) or Hispanic (74.5%) individuals with MS. Age- and sex-standardized MS prevalence per 100,000 was similarly high among Black (225.8, 95% CI 207.1-244.5) and White (237.7, 95% CI 228.2-247.2) and significantly lower among Hispanic (69.9, 95% CI 64.4-75.5) and Asian (22.6, 95% CI 17.1-28.1) persons. MS prevalence was highest between the ages of 35 and 64 years and declined after 65 years of age across all racial and ethnic groups. Among adults 18 to 24 years of age, the crude MS prevalence was low but was highest among Black and Hispanic young adults, lower in White people, and lowest in Asian/Pacific Islander individuals (48.5, 25.0, 18.0, and 7.1 per 100,000, respectively). DISCUSSION: MS prevalence varies by race and ethnicity, being similarly high in White and Black and significantly lower in Hispanic and Asian persons in Southern California. Taken together with previous studies, these findings indicate that the burden of MS in the US Black community has long been underrecognized. More studies are needed to determine whether MS is an emerging disease among US Hispanic adults and whether MS susceptibility and prevalence vary among Hispanic or Asian individuals from different cultures or ancestral backgrounds.

The timed 25-foot walk in a large cohort of multiple sclerosis patients.

BACKGROUND: The timed 25-foot walk (T25FW) is a key clinical outcome measure in multiple sclerosis patient management and clinical research. OBJECTIVES: To evaluate T25FW performance and factors associated with its change in the Multiple Sclerosis Outcome Assessments Consortium (MSOAC) Placebo Database (n = 2465). METHODS: We created confirmed disability progression (CDP) variables for T25FW and Expanded Disability Status Scale (EDSS) outcomes. We used intraclass correlation coefficients (ICCs) and Bland Altman plots to evaluate reliability. We evaluated T25FW changes and predictive validity using a mixed-effects model, survival analysis, and nested case-control analysis. RESULTS: The mean baseline score for the T25FW in this study population was 9.2 seconds, median = 6.1 (standard deviation = 11.0, interquartile range (IQR) = 4.8, 9.0). The T25FW measure demonstrated excellent test-retest reliability (ICC = 0.98). Walk times increased with age, disability, disease type, and disease duration; relapses were not associated with an increase. Patients with T25FW progression had a faster time to EDSS-CDP compared to those without (hazards ratio (HR): 2.6; confidence interval (CI): 2.2, 3.1). Changes in the T25FW were more likely to precede changes in EDSS. CONCLUSION: This research confirms the association of the T25FW with disability and provides some evidence of predictive validity. Our findings support the continued use of the T25FW in clinical practice and clinical trials.

Prevalence of amyotrophic lateral sclerosis (ALS), United States, 2016.

Objective: To estimate the prevalence of amyotrophic lateral sclerosis (ALS) in the United States for 2016 using data from the National ALS Registry (Registry). Established in 2009, the Registry collects data on ALS patients in the U.S. to better describe the epidemiology of ALS, examine risk factors such as environmental and occupational exposures, and characterize the demographics of those living with the disease. Methods: To identify adult prevalent cases of ALS, the Registry compiles data from three national administrative databases (maintained by the Centers for Medicare and Medicaid Services, the Veterans Health Administration, and the Veterans Benefits Administration). To ascertain cases not necessarily included in these databases and to better understand risk-factors associated with ALS and disease progression, the Registry also includes data collected from patients who voluntarily enroll via a web portal to complete online surveys. Results: In 2016, the Registry conservatively identified 16,424 adult persons who met the Registry definition of ALS for an age-adjusted prevalence rate of 5.2 per 100,000 U.S. population. The pattern of patient characteristics (e.g., age, sex, and race/ethnicity) has not changed from previous Registry reports. Overall, ALS was more common among whites, males, and persons aged 60-69 years. The age groups with the lowest number of ALS cases were persons aged 18-39 years. Males had a higher prevalence rate of ALS than females overall and across all data sources. Conclusions: Data collected by the National ALS Registry are being used to better describe the epidemiology and demographics of ALS in the U.S.

Evaluation of the Completeness of ALS Case Ascertainment in the US National ALS Registry: Application of the Capture-Recapture Method.

INTRODUCTION: The Centers for Disease Control and Prevention (CDC) National Amyotrophic Lateral Sclerosis (ALS) Registry is the first national registry for a chronic neurologic disease in the USA and uses a combination of case-finding methods including administrative healthcare data and patient self-registration. METHODS: We applied capture-recapture methodology to estimate the completeness of the Registry for ascertaining patients with ALS for the first full year and the fourth year of the Registry (2011, 2014). The Registry uses the combination of two national administrative claims databases (Medicare and Veterans Affairs) with a self-register option at the registry portal. We conducted descriptive analyses of the demographic and clinical characteristics of the ALS cases identified by each of the sources and estimated the completeness of case ascertainment for each of the three ALS Registry sources individually, pairwise, and in all combinations. RESULTS: Case-finding completeness was 54% in 2011 and improved to 56% in 2014. A smaller proportion of ALS patients under age 65 were ascertained than those 65 or older, and ascertainment was also lower for nonwhite than white patients. The uncorrected ALS prevalence was 4.3/100,000 in 2011 (in 2014, 5.0/100,000), but after correction for underascertainment, annual prevalence in 2011 was 7.9/100,000 (95% CI: 7.6-8.2) (in 2014 was 8.9/100,000 [95% CI: 8.7-9.2]). DISCUSSION/CONCLUSION: Our findings indicate that administrative healthcare databases are a very efficient method for identifying the majority of ALS prevalent cases in the National ALS Registry and that the inclusion of a web registry portal for patients to self-register is important to ensure a more representative population for estimating ALS prevalence. Nonetheless, more than 40% of ALS cases were not ascertained by the Registry, with individuals younger than age 65 and people of color underrepresented. Recommendations are provided for additional methods that can be considered to improve the completeness of case ascertainment.

Association Between Income Inequality and County-Level COVID-19 Cases and Deaths in the US.

Importance: Socioeconomically marginalized communities have been disproportionately affected by the COVID-19 pandemic. Income inequality may be a risk factor for SARS-CoV-2 infection and death from COVID-19. Objective: To evaluate the association between county-level income inequality and COVID-19 cases and deaths from March 2020 through February 2021 in bimonthly time epochs. Design, Setting, and Participants: This ecological cohort study used longitudinal data on county-level COVID-19 cases and deaths from March 1, 2020, through February 28, 2021, in 3220 counties from all 50 states, Puerto Rico, and the District of Columbia. Main Outcomes and Measures: County-level daily COVID-19 case and death data from March 1, 2020, through February 28, 2021, were extracted from the COVID-19 Data Repository by the Center for Systems Science and Engineering at Johns Hopkins University in Baltimore, Maryland. Exposure: The Gini coefficient, a measure of unequal income distribution (presented as a value between 0 and 1, where 0 represents a perfectly equal geographical region where all income is equally shared and 1 represents a perfectly unequal society where all income is earned by 1 individual), and other county-level data were obtained primarily from the 2014 to 2018 American Community Survey 5-year estimates. Covariates included median proportions of poverty, age, race/ethnicity, crowding given by occupancy per room, urbanicity and rurality, educational level, number of physicians per 100 000 individuals, state, and mask use at the county level. Results: As of February 28, 2021, on average, each county recorded a median of 8891 cases of COVID-19 per 100 000 individuals (interquartile range, 6935-10 666 cases per 100 000 individuals) and 156 deaths per 100 000 individuals (interquartile range, 94-228 deaths per 100 000 individuals). The median county-level Gini coefficient was 0.44 (interquartile range, 0.42-0.47). There was a positive correlation between Gini coefficients and county-level COVID-19 cases (Spearman ρ = 0.052; P < .001) and deaths (Spearman ρ = 0.134; P < .001) during the study period. This association varied over time; each 0.05-unit increase in Gini coefficient was associated with an adjusted relative risk of COVID-19 deaths: 1.25 (95% CI, 1.17-1.33) in March and April 2020, 1.20 (95% CI, 1.13-1.28) in May and June 2020, 1.46 (95% CI, 1.37-1.55) in July and August 2020, 1.04 (95% CI, 0.98-1.10) in September and October 2020, 0.76 (95% CI, 0.72-0.81) in November and December 2020, and 1.02 (95% CI, 0.96-1.07) in January and February 2021 (P < .001 for interaction). The adjusted association of the Gini coefficient with COVID-19 cases also reached a peak in July and August 2020 (relative risk, 1.28 [95% CI, 1.22-1.33]). Conclusions and Relevance: This study suggests that income inequality within US counties was associated with more cases and deaths due to COVID-19 in the summer months of 2020. The COVID-19 pandemic has highlighted the vast disparities that exist in health outcomes owing to income inequality in the US. Targeted interventions should be focused on areas of income inequality to both flatten the curve and lessen the burden of inequality.

The Impact of the first COVID-19 shelter-in-place announcement on social distancing, difficulty in daily activities, and levels of concern in the San Francisco Bay Area: A cross-sectional social media survey.

BACKGROUND: The U.S. has experienced an unprecedented number of orders to shelter in place throughout the ongoing COVID-19 pandemic. We aimed to ascertain whether social distancing; difficulty with daily activities; and levels of concern regarding COVID-19 changed after the March 16, 2020 announcement of the nation's first shelter-in-place orders (SIPO) among individuals living in the seven affected counties in the San Francisco Bay Area. METHODS: We conducted an online, cross-sectional social media survey from March 14 -April 1, 2020. We measured changes in social distancing behavior; experienced difficulties with daily activities (i.e., access to healthcare, childcare, obtaining essential food and medications); and level of concern regarding COVID-19 after the March 16 shelter-in-place announcement in the San Francisco Bay Area versus elsewhere in the U.S. RESULTS: In this non-representative sample, the percentage of respondents social distancing all of the time increased following the shelter-in-place announcement in the Bay Area (9.2%, 95% CI: 6.6, 11.9) and elsewhere in the U.S. (3.4%, 95% CI: 2.0, 5.0). Respondents also reported increased difficulty obtaining hand sanitizer, medications, and in particular respondents reported increased difficulty obtaining food in the Bay Area (13.3%, 95% CI: 10.4, 16.3) and elsewhere (8.2%, 95% CI: 6.6, 9.7). We found limited evidence that level of concern regarding the COVID-19 crisis changed following the announcement. CONCLUSION: This study characterizes early changes in attitudes, behaviors, and difficulties. As states and localities implement, rollback, and reinstate shelter-in-place orders, ongoing efforts to more fully examine the social, economic, and health impacts of COVID-19, especially among vulnerable populations, are urgently needed.

Development and Internal Validation of a Multivariable Prediction Model for Individual Episodic Migraine Attacks Based on Daily Trigger Exposures.

OBJECTIVE: To develop and internally validate a multivariable predictive model for days with new-onset migraine headaches based on patient self-prediction and exposure to common trigger factors. BACKGROUND: Accurate real-time forecasting of one's daily risk of migraine attack could help episodic migraine patients to target preventive medications for susceptible time periods and help decrease the burden of disease. Little is known about the predictive utility of common migraine trigger factors. METHODS: We recruited adults with episodic migraine through online forums to participate in a 90-day prospective daily-diary cohort study conducted through a custom research application for iPhone. Every evening, participants answered questions about migraine occurrence and potential predictors including stress, sleep, caffeine and alcohol consumption, menstruation, and self-prediction. We developed and estimated multivariable multilevel logistic regression models for the risk of a new-onset migraine day vs a healthy day and internally validated the models using repeated cross-validation. RESULTS: We had 178 participants complete the study and qualify for the primary analysis which included 1870 migraine events. We found that a decrease in caffeine consumption, higher self-predicted probability of headache, a higher level of stress, and times within 2 days of the onset of menstruation were positively associated with next-day migraine risk. The multivariable model predicted migraine risk only slightly better than chance (within-person C-statistic: 0.56, 95% CI: 0.54, 0.58). CONCLUSIONS: In this study, episodic migraine attacks were not predictable based on self-prediction or on self-reported exposure to common trigger factors. Improvements in accuracy and breadth of data collection are needed to build clinically useful migraine prediction models.

Implications of the COVID-19 San Francisco Bay Area Shelter-in-Place Announcement: A Cross-Sectional Social Media Survey.

BACKGROUND: The U.S. has experienced an unprecedented number of shelter-in-place orders throughout the COVID-19 pandemic. There is limited empirical research that examines the impact of these orders. We aimed to rapidly ascertain whether social distancing; difficulty with daily activities (obtaining food, essential medications and childcare); and levels of concern regarding COVID-19 changed after the March 16, 2020 announcement of shelter-in-place orders for seven counties in the San Francisco Bay Area. METHODS: We conducted an online, cross-sectional social media survey from March 14 - April 1, 2020. We measured changes in social distancing behavior; experienced difficulties with daily activities (i.e., access to healthcare, childcare, obtaining essential food and medications); and level of concern regarding COVID-19 after the March 16 shelter-in-place announcement in the San Francisco Bay Area and elsewhere in the U.S. RESULTS: The percentage of respondents social distancing all of the time increased following the shelter-in-place announcement in the Bay Area (9.2%, 95% CI: 6.6, 11.9) and elsewhere in the U.S. (3.4%, 95% CI: 2.0, 5.0). Respondents also reported increased difficulty with obtaining food, hand sanitizer, and medications, particularly with obtaining food for both respondents from the Bay Area (13.3%, 95% CI: 10.4, 16.3) and elsewhere (8.2%, 95% CI: 6.6, 9.7). We found limited evidence that level of concern regarding the COVID-19 crisis changed following the shelter-in-place announcement. CONCLUSION: These results capture early changes in attitudes, behaviors, and difficulties. Further research that specifically examines social, economic, and health impacts of COVID-19, especially among vulnerable populations, is urgently needed. =.