Association of Plasma Amyloid-ß and Dementia Among Black and White Older Adults.

Background: Plasma amyloid-ß (Aß) has emerged as an important tool to detect risks of Alzheimer's disease and related dementias, although research in diverse populations is lacking. Objective: We compared plasma Aß42/40 by race with dementia risk over 15 years among Black and White older adults. Methods: In a prospective cohort of 997 dementia-free participants (mean age 74±2.9 years, 55% women, 54% Black), incident dementia was identified based on hospital records, medication, and neurocognitive test over 15 years. Plasma Aß42/40 was measured at Year 2 and categorized into low, medium, and high tertile. We used linear regression to estimate mean Aß42/40 by race and race-stratified Cox proportional hazards models to assess the association between Aß42/40 tertile and dementia risk. Results: Black participants had a lower age-adjusted mean Aß 42/40 compared to White participants, primarily among APOE ɛ4 non-carriers (Black: 0.176, White: 0.185, p = 0.035). Among Black participants, lower Aß 42/40 was associated with increased dementia risk: 33% in low (hazard ratios [HR] = 1.77, 95% confidence interval 1.09-2.88) and 27% in medium tertile (HR = 1.67, 1.01-2.78) compared with 18% in high Aß 42/40 tertile; Increased risks were attenuated among White participants: 21% in low (HR = 1.43, 0.81-2.53) and 23% in medium tertile (HR = 1.27, 0.68-2.36) compared with 15% in high Aß 42/40 tertile. The interaction by race was not statistically significant. Conclusions: Among community-dwelling, non-demented older adults, especially APOE ɛ4 non-carriers, Black individuals had lower plasma Aß 42/40 and demonstrated a higher dementia risk with low Aß42/40 compared with White individuals.

Association of cardiovascular risk factors and blood biomarkers with cognition: The HABS-HD study.

Introduction: To determine if cardiovascular risk factor (CVRF) burden is associated with Alzheimer's disease (AD) biomarkers and whether they synergistically associate with cognition. Methods: We cross-sectionally studied 1521 non-demented Mexican American (52%) and non-Hispanic White individuals aged ≥50 years. A composite score was calculated by averaging the z-scores of five cognitive tests. Plasma ß-amyloid (Aß) 42/40, total tau (t-tau), and neurofilament light (NfL) were assayed using Simoa. CVRF burden was assessed using the Framingham Risk Score (FRS). Results: Compared to low FRS (< 10% risk), high FRS (≥ 20% risk) was independently associated with increased t-tau and NfL. High FRS was significantly associated with higher NfL only among Mexican American individuals. Intermediate or high FRS (vs. low FRS) were independently associated with lower cognition, and the association remained significant after adjusting for plasma biomarkers. Hypertension synergistically interacted with t-tau and NfL (p < 0.05). Discussion: CVRFs play critical roles, both through independent and neurodegenerative pathways, on cognition.

Premature Cardiovascular Disease and Brain Health in Midlife: The CARDIA Study.

BACKGROUND AND OBJECTIVES: To understand the role of premature (defined as ≤ 60 years) cardiovascular disease (CVD) in brain health earlier in life, we examined the associations of premature CVD with midlife cognition and white matter health. METHODS: We studied a prospective cohort in the Coronary Artery Risk Development in Young Adults study, who were 18-30 years at baseline (1985-1986) and followed up to 30 years when 5 cognitive tests measuring different domains were administered. A subset (656 participants) had brain MRI measures of white matter hyperintensity (WMH) and white matter integrity. A premature CVD event was adjudicated based on medical records of coronary heart disease, stroke/TIA, congestive heart failure, carotid artery disease, and peripheral artery disease. We conducted linear regression to determine the associations of nonfatal premature CVD with cognitive performance (z-standardized), cognitive decline, and MRI measures. RESULTS: Among 3,146 participants, the mean age (57% women and 48% Black) was 55.1 ± 3.6 years, with 5% (n = 147) having premature CVD. Adjusting for demographics, education, literacy, income, depressive symptoms, physical activity, diet, and APOE, premature CVD was associated with lower cognition in 4 of 5 domains: global cognition (-0.22, 95% CI -0.37 to -0.08), verbal memory (-0.28, 95% CI -0.44 to -0.12), processing speed (-0.46, 95% CI -0.62 to -0.31), and executive function (-0.38, 95% CI -0.55 to -0.22). Premature CVD was associated with greater WMH (total, temporal, and parietal lobes) and higher white matter mean diffusivity (total and temporal lobes) after adjustment for covariates. These associations remained significant after adjusting for cardiovascular risk factors (CVRFs) and excluding those with stroke/TIA. Premature CVD was also associated with accelerated cognitive decline over 5 years (adjusted OR 3.07, 95% CI 1.65-5.71). DISCUSSION: Premature CVD is associated with worse midlife cognition and white matter health, which is not entirely driven by stroke/TIA and even independent of CVRFs. Preventing CVD in early adulthood may delay the onset of cognitive decline and promote brain health over the life course.

Rapid prediction of in-hospital mortality among adults with COVID-19 disease.

BACKGROUND: We developed a simple tool to estimate the probability of dying from acute COVID-19 illness only with readily available assessments at initial admission. METHODS: This retrospective study included 13,190 racially and ethnically diverse adults admitted to one of the New York City Health + Hospitals (NYC H+H) system for COVID-19 illness between March 1 and June 30, 2020. Demographic characteristics, simple vital signs and routine clinical laboratory tests were collected from the electronic medical records. A clinical prediction model to estimate the risk of dying during the hospitalization were developed. RESULTS: Mean age (interquartile range) was 58 (45-72) years; 5421 (41%) were women, 5258 were Latinx (40%), 3805 Black (29%), 1168 White (9%), and 2959 Other (22%). During hospitalization, 2,875 were (22%) died. Using separate test and validation samples, machine learning (Gradient Boosted Decision Trees) identified eight variables-oxygen saturation, respiratory rate, systolic and diastolic blood pressures, pulse rate, blood urea nitrogen level, age and creatinine-that predicted mortality, with an area under the ROC curve (AUC) of 94%. A score based on these variables classified 5,677 (46%) as low risk (a score of 0) who had 0.8% (95% confidence interval, 0.5-1.0%) risk of dying, and 674 (5.4%) as high-risk (score ≥ 12 points) who had a 97.6% (96.5-98.8%) risk of dying; the remainder had intermediate risks. A risk calculator is available online at https://danielevanslab.shinyapps.io/Covid_mortality/. CONCLUSIONS: In a diverse population of hospitalized patients with COVID-19 illness, a clinical prediction model using a few readily available vital signs reflecting the severity of disease may precisely predict in-hospital mortality in diverse populations and can rapidly assist decisions to prioritize admissions and intensive care.

Multiple Chronic Conditions Explain Ethnic Differences in Functional Outcome Among Patients With Ischemic Stroke.

BACKGROUND AND PURPOSE: Mexican Americans (MAs) have worse stroke outcomes and a different profile of multiple chronic conditions (MCC) compared with non-Hispanic White people. MCC has implications for stroke treatment, complications, and poststroke care, which impact poststroke functional outcome (FO). We sought to assess the contribution of MCC to the ethnic difference in FO at 90 days between MAs and non-Hispanic White people. METHODS: In a prospective cohort of ischemic stroke patients (2008-2016) from Nueces County, Texas, data were collected from patient interviews, medical records, and hospital discharge data. MCC was assessed using a stroke-specific and function-relevant index (range, 0-35; higher scores greater MCC burden). Poststroke FO was measured by an average score of 22 activities of daily living (ADLs) and instrumental ADLs at 90 days (range, 1-4; higher scores worse FO). The contribution of MCC to the ethnic difference in FO was assessed using Tobit regression. Effect modification by ethnicity was examined. RESULTS: Among the 896 patients, 70% were MA and 51% were women. Mean age was 68±12.2 years; 33% of patients were dependent in ADL/instrumental ADLs (FO score >3, representing a lot of difficulty with ADL/instrumental ADLs) at 90 days. MAs had significantly higher age-adjusted MCC burden compared with non-Hispanic White people. Patients with high MCC score (at the 75th percentile) on average scored 0.70 points higher in the FO score (indicating worse FO) compared with those with low MCC score (at the 25th percentile) after adjusting for age, initial National Institutes of Health Stroke Scale, and sociodemographic factors. MCC explained 19% of the ethnic difference in FO, while effect modification by ethnicity was not statistically significant. CONCLUSIONS: MAs had a higher age-adjusted MCC burden, which partially explained the ethnic difference in FO. The prevention and treatment of MCC could potentially mitigate poststroke functional impairment and lessen ethnic disparities in stroke outcomes.

New Index for Multiple Chronic Conditions Predicts Functional Outcome in Ischemic Stroke.

OBJECTIVE: To determine whether a new index for multiple chronic conditions (MCCs) predicts poststroke functional outcome (FO), we developed and internally validated the new MCC index in patients with ischemic stroke. METHODS: A prospective cohort of patients with ischemic stroke (2008-2017) was interviewed at baseline and 90 days in the Brain Attack Surveillance in Corpus Christi Project. An average of 22 activities of daily living (ADL)/instrumental ADL (IADL) items measured the FO score (range 1-4) at 90 days. A FO score >3 (representing a lot of difficulty with ADL/IADLs) was considered unfavorable FO. A new index was developed using machine learning techniques to select and weight conditions and prestroke impairments. RESULTS: Prestroke modified Rankin Scale (mRS) score, age, congestive heart failure (CHF), weight loss, diabetes, other neurologic disorders, and synergistic effects (dementia × age, CHF × renal failure, and prestroke mRS × prior stroke/TIA) were identified as important predictors in the MCC index. In the validation dataset, the index alone explained 31% of the variability in the FO score, was well-calibrated (p = 0.41), predicted unfavorable FO well (area under the receiver operating characteristic curve 0.81), and outperformed the modified Charlson Comorbidity Index in predicting the FO score and poststroke mRS. CONCLUSIONS: A new MCC index was developed and internally validated to improve the prediction of poststroke FO. Novel predictors and synergistic interactions were identified. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with ischemic stroke, an index for MCC predicts FO at 90 days.

Multiple Chronic Conditions and Functional Outcome after Ischemic Stroke: A Systematic Review and Meta-Analysis.

BACKGROUND: Multiple chronic conditions (MCC) contribute to functional disability in the general population although its role in predicting functional outcome (FO) among patients with stroke is not well understood. There is no universal agreement on the approach to measuring MCC in stroke, and findings have been mixed regarding MCC being an independent predictor for poststroke FO. OBJECTIVES: This review aims to summarize the findings of studies that have investigated the relationship between MCC and FO after ischemic stroke using a MCC index. METHOD: PubMed and Embase were systematically searched for studies conducted among ischemic stroke patients that have examined the adjusted association between prestroke MCC and FO. The quality of the included studies was appraised using a risk of bias (RoB) assessment checklist. A meta-analysis was performed for the association between MCC and FO using a random effects model to estimate the overall pooled ORs. RESULTS: Twelve of the 18 studies included were hospital-based cohort studies, with a median RoB score of 4.75 points (range 1-9, higher scores for higher RoB). Studies predominantly used the Charlson Comorbidity Index (CCI), or the Modified CCI to measure MCC burden, and the modified Rankin scale to measure FO. Half of the studies reported a significant negative association between MCC and FO, which was also found by the meta-analysis with a pooled OR of 1.11 (95% CI 1.05-1.18). CONCLUSIONS: The current review supports that increased MCC is associated with worse poststroke FO although population-based studies of this association are lacking. Future research should aim to develop more refined measures of MCC that consider the severity and interactions of comorbid conditions reflective of the broader stroke population and to understand the relationship between MCC and poststroke FO with thorough adjustment for confounding factors.

Sleep apnea screening is uncommon after stroke.

OBJECTIVE/BACKGROUND: To assess (1) pre and post-stroke screening for sleep apnea (SA) within a population-based study without an academic medical center, and (2) ethnic differences in post-stroke sleep apnea screening among Mexican Americans (MAs) and non-Hispanic whites (NHWs). PATIENTS/METHODS: MAs and NHWs with stroke in the Brain Attack Surveillance in Corpus Christi project (2011-2015) were interviewed shortly after stroke about the pre-stroke period, and again at approximately 90 days after stroke in reference to the post-stroke period. Questions included whether any clinical provider directly asked about snoring or daytime sleepiness or had offered polysomnography. Logistic regression tested the association between these outcomes and ethnicity both unadjusted and adjusted for potential confounders. RESULTS: Among 981 participants, 63% were MA. MAs in comparison to NHWs were younger, had a higher prevalence of hypertension, diabetes, and never smoking, a higher body mass index, and a lower prevalence of atrial fibrillation. Only 17% reported having been offered SA diagnostic testing pre-stroke, without a difference by ethnicity. In the post-stroke period, only 50 (5%) participants reported being directly queried about snoring; 86 (9%) reported being directly queried about sleepiness; and 55 (6%) reported having been offered polysomnography. No ethnic differences were found for these three outcomes, in unadjusted or adjusted analyses. CONCLUSIONS: Screening for classic symptoms of SA, and formal testing for SA, are rare within the first 90 days after stroke, for both MAs and NHWs. Provider education is needed to raise awareness that SA affects most patients after stroke and is associated with poor outcomes.

The difficulty of studying race-ethnic stroke rehabilitation disparities in a community.

OBJECTIVE: Minority populations have worse stroke outcomes compared with non-Hispanic whites (NHWs). One possible explanation for this disparity is differential allocation of stroke rehabilitation. We utilized a population-based stroke study to determine the feasibility of studying Mexican American-NHW differences in stroke rehabilitation in a population-based design including identification of community partners, development of standardized data collection instruments, and collection of pilot data. METHODS: As part of the Brain Attack Surveillance in Corpus Christi project, we followed 48 patients for the first 90 days after stroke, and attempted to work with community partners to garner information on rehabilitation modalities used. With input from local occupational and physical therapists and speech language pathologists, we created data collection forms to capture rehabilitation activities and time spent on these activities and conducted a 3-month data collection pilot. RESULTS: Of the 79 rehabilitation venues in the community, 63 (80%) agreed to participate. During the pilot, 545 data forms from 20 stroke patients were collected corresponding to ~18% of stroke patients. Forms were used by 13 partners during the pilot including 3 of 4 inpatient rehabilitation facilities, 4 of 13 skilled nursing facilities, 4 of 26 home health agencies, and 2 of 36 outpatient rehabilitation providers. CONCLUSIONS: Initial agreement from rehabilitation providers to participate in research was excellent, but completion of study related data collection forms was sub-optimal suggesting this approach is not feasible for a future population-based stroke rehabilitation study. Further methods to study post-stroke rehabilitation disparities in communities are needed.

Mexican Americans Receive Less Intensive Stroke Rehabilitation Than Non-Hispanic Whites.

BACKGROUND AND PURPOSE: Mexican Americans (MAs) have worse neurological, functional, and cognitive outcomes after stroke. Stroke rehabilitation is important for good outcome. In a population-based study, we sought to determine whether allocation of stroke rehabilitation services differed by ethnicity. METHODS: Patients with stroke were identified as part of the Brain Attack Surveillance in Corpus Christi (BASIC) project, TX, USA. Cases were validated by physicians using source documentation. Patients were followed prospectively for 3 months after stroke to determine rehabilitation services and transitions. Descriptive statistics were used to depict the study population. Continuous baseline variables were compared using 2 sample t tests or Wilcoxon rank-sum tests by ethnicity. Categorical baseline variables were compared using χ2 tests. Ethnic comparisons of rehabilitation services were compared using χ2 tests, Fisher's exact tests, and logistic regression. RESULTS: Seventy-two subjects (50 MA and 22 non-Hispanic white [NHW]) were followed. Mean age, NHW-69 (SD 13), MA-66 (SD 11) years, sex (NHW 55% male, MA 50% male) and median presenting National Institutes of Health Stroke Scale did not differ significantly. There were no ethnic differences among the proportion of patients who were sent home without any rehabilitation services (P=0.9). Among those who received rehabilitation, NHWs were more likely to get inpatient rehabilitation (73%) compared with MAs (30%), P=0.016. MAs (51%) were much more likely to receive home rehabilitation services compared with NHWs (0%) (P=0.0017). CONCLUSIONS: In this population-based study, MAs were more likely to receive home-based rehabilitation, whereas NHWs were more likely to get inpatient rehabilitation. This disparity may, in part, explain the worse stroke outcome in MAs.

Socioeconomic factors related to surgical treatment for localized, non-small cell lung cancer.

Various socioeconomic factors were reported to be associated with receiving surgical treatment in localized, non-small cell lung cancer (NSCLC) patients in previous studies. We wanted to assess the impact of residential poverty on receiving surgical treatment in a state-wide population of localized NSCLC, adjusting for demographic, clinical, residence and tumor factors. Data on 970 patients with primary localized NSCLC were collected from the Nebraska Cancer Registry (NCR), and linked with the Nebraska Hospital Discharge Data (NHDD) between 2005 and 2009, as well as the 2010 Census data. Characteristics of patients with and without surgery were compared using Chi-square tests. Unadjusted and adjusted odds ratios (ORs) of receiving surgery for low versus high poverty were generated based on the series of logistic regression models controlling for demographics, comorbidity, residence and tumor histology. Patients who were 65 year old or younger, without comorbidities, single or married, and with adenocarcinoma histologic type were more likely to receive surgery. Without adjustment, poverty was negatively associated with receiving surgery. Patients who resided in low poverty neighborhoods (less than 5% of the households under poverty line) were twice more likely to receive surgery than those who lived in high poverty neighborhoods (more than 15% of the households under poverty line) (OR 2.13, 95% CI 1.33-3.40). After adjustment, poverty was independently and negatively associated with receiving surgery treatment. Residents in low poverty neighborhoods were still about twice more likely to receive surgery than those in high poverty neighborhoods when the other demographic, urban/rural residency and clinical factors were adjusted (ORs 2.01-2.18, all p < 0.05). The mechanism of how living in poverty interacts with other factors and its impact on patient's choice and their chance of getting surgical treatment invites future studies.

Comorbidity and Survival in Lung Cancer Patients.

BACKGROUND: As the population of the United States ages, there will be increasing numbers of lung cancer patients with comorbidities at diagnosis. Comorbid conditions are important factors in both the choice of the lung cancer treatment and outcomes. However, the impact of individual comorbid conditions on patient survival remains unclear. METHODS: A population-based cohort study of 5,683 first-time diagnosed lung cancer patients was captured using the Nebraska Cancer Registry (NCR) linked with the Nebraska Hospital Discharge Data (NHDD) between 2005 and 2009. A Cox proportional hazards model was used to analyze the effect of comorbidities on the overall survival of patients stratified by stage and adjusting for age, race, sex, and histologic type. RESULTS: Of these patients, 36.8% of them survived their first year after lung cancer diagnosis, with a median survival of 9.3 months for all stages combined. In this cohort, 26.7% of the patients did not have any comorbidity at diagnosis. The most common comorbid conditions were chronic pulmonary disease (52.5%), diabetes (15.7%), and congestive heart failure (12.9%). The adjusted overall survival of lung cancer patients was negatively associated with the existence of different comorbid conditions such as congestive heart failure, diabetes with complications, moderate or severe liver disease, dementia, renal disease, and cerebrovascular disease, depending on the stage. CONCLUSIONS: The presence of comorbid conditions was associated with worse survival. Different comorbid conditions were associated with worse outcomes at different stages. IMPACT: Future models for predicting lung cancer survival should take individual comorbid conditions into consideration.