Faculty Bibliography

BACKGROUND:While survival after acute myocardial infarction has improved substantially, older adults remain at heightened risk for hospital readmissions and death. Evidence for the role of cognitive impairment in older myocardial infarction survivors' risk for these outcomes is limited. METHODS:3041 patients aged ≥75 years hospitalized with acute myocardial infarction (mean age 82 ± 5 years, 56% male) recruited from 94 US hospitals. Cognition was assessed using the Telephone Interview for Cognitive Status; scores of <27 and <22 indicated mild and moderate/severe impairment, respectively. Readmissions and death at 6 months post-discharge were ascertained via participant report and medical record review. Associations between cognition and outcomes were evaluated with multivariable-adjusted logistic regression. RESULTS:Mild and moderate/severe cognitive impairment were present in 11% and 6% of the cohort, respectively. Readmission and death at 6 months occurred in 41% and 9% of participants, respectively. Mild and moderate/severe cognitive impairment were associated with increased risk of readmission (odds ratio [OR] 1.36; 95% confidence interval [CI], 1.08-1.72 and OR 1.58; 95% CI, 1.18-2.12, respectively) and death (OR 2.19; 95% CI, 1.54-3.11 and OR 3.82; 95% CI, 2.63-5.56, respectively) in unadjusted analyses. Significant associations between moderate/severe cognitive impairment and death (OR 1.69; 95% CI, 1.10-2.59) persisted after adjustment for demographics, myocardial infarction characteristics, comorbidity burden, functional status, and depression, but not for readmissions. CONCLUSIONS:Moderate-to-severe cognitive impairment is associated with heightened risk of death in older acute myocardial infarction patients in the months after hospitalization, but not with readmission. Routine cognitive screening may identify older myocardial infarction survivors at risk for poor outcomes who may benefit from closer oversight and support in the post-discharge period.

Income, education, and cumulative-risk indices likely obscure meaningful heterogeneity in the mechanisms through which poverty impacts child outcomes. This study draws from contemporary theory to specify multiple dimensions of poverty-related adversity and resources, with the aim of better capturing these nuances. Using data from the Family Life Project (N = 1,292), we leveraged moderated nonlinear factor analysis (Bauer, 2017) to establish group- and longitudinally invariant environmental measures from infancy to early adolescence. Results indicated three latent factors-material deprivation, psychosocial threat, and sociocognitive resources-were distinct from each other and from family income. Each was largely invariant across site, racial group, and development and showed convergent and discriminant relations with age-twelve criterion measures. Implications for ensuring socioculturally valid measurements of poverty are discussed.

This study examines whether changes in classroom quality predict within-child changes in achievement and behavioral problems in elementary school (ages spanning approximately 6-11 years old). Drawing on data from a longitudinal study of children in predominantly low-income, nonurban communities (n = 1,078), we relied on child fixed effects modeling, which controlled for stable factors that could bias the effects of classroom quality. In general, we found that changes in classroom quality had small and statistically nonsignificant effects on achievement and behavior. However, we found that moving into a high-quality classroom, particularly those rated as high in Classroom Organization, had positive effects on achievement and behavior for children with significant exposure to poverty in early life.

Left censoring in salivary bioscience data occurs when salivary analyte determinations fall below the lower limit of an assay's measurement range. Conventional statistical approaches for addressing censored values (i.e., recoding as missing, substituting or extrapolating values) may introduce systematic bias. While specialized censored data statistical approaches (i.e., Maximum Likelihood Estimation, Regression on Ordered Statistics, Kaplan-Meier, and general Tobit regression) are available, these methods are rarely implemented in biobehavioral studies that examine salivary biomeasures, and their application to salivary data analysis may be hindered by their sensitivity to skewed data distributions, outliers, and sample size. This study compares descriptive statistics, correlation coefficients, and regression parameter estimates generated via conventional and specialized censored data approaches using salivary C-reactive protein data. We assess differences in statistical estimates across approach and across two levels of censoring (9% and 15%) and examine the sensitivity of our results to sample size. Overall, findings were similar across conventional and censored data approaches, but the implementation of specialized censored data approaches was more efficient (i.e., required little manipulations to the raw analyte data) and appropriate. Based on our review of the findings, we outline preliminary recommendations to enable investigators to more efficiently and effectively reduce statistical bias when working with left-censored salivary biomeasure data.

Time-to-event data are often subject to left-truncation. Lack of consideration of the sampling condition will introduce bias and loss in efficiency of the estimation. While auxiliary information from the same or similar cohorts may be available, challenges arise due to the practical issue of accessibility of individual-level data and taking account of various sampling conditions for different cohorts. In this paper, we introduce a likelihood-based method to incorporate information from auxiliary data to eliminate the left-truncation problem and improve efficiency. A one-step Monte-Carlo Expectation-Maximization algorithm is developed to calculate an augmented likelihood through creating pseudo-data sets which extend the form and conditions of the observed sample. The method is illustrated by both a real dataset and simulation studies.

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used automated, machine-learning, high-dimensional data pruning, and validated identified biomarkers. The parent cohort consisted of male, never-smoking firefighters with WTC-LI (FEV1, %Pred< lower limit of normal (LLN); n = 100) and controls (n = 127) and had their biomarkers assessed. Cases and controls (n = 15/group) underwent untargeted metabolomics, then feature selection performed on metabolites, cytokines, chemokines, and clinical data. Cytokines, chemokines, and clinical biomarkers were validated in the non-overlapping parent-cohort via binary logistic regression with 5-fold cross validation. Random forests of metabolites (n = 580), clinical biomarkers (n = 5), and previously assayed cytokines, chemokines (n = 106) identified that the top 5% of biomarkers important to class separation included pigment epithelium-derived factor (PEDF), macrophage derived chemokine (MDC), systolic blood pressure, macrophage inflammatory protein-4 (MIP-4), growth-regulated oncogene protein (GRO), monocyte chemoattractant protein-1 (MCP-1), apolipoprotein-AII (Apo-AII), cell membrane metabolites (sphingolipids, phospholipids), and branched-chain amino acids. Validated models via confounder-adjusted (age on 9/11, BMI, exposure, and pre-9/11 FEV1, %Pred) binary logistic regression had AUCROC [0.90(0.84-0.96)]. Decreased PEDF and MIP-4, and increased Apo-AII were associated with increased odds of WTC-LI. Increased GRO, MCP-1, and simultaneously decreased MDC were associated with decreased odds of WTC-LI. In conclusion, automated data pruning identified novel WTC-LI biomarkers; performance was validated in an independent cohort. One biomarker-PEDF, an antiangiogenic agent-is a novel, predictive biomarker of particulate-matter-related lung disease. Other biomarkers-GRO, MCP-1, MDC, MIP-4-reveal immune cell involvement in WTC-LI pathogenesis. Findings of our automated biomarker identification warrant further investigation into these potential pharmacotherapy targets.

Restrictive immigration policies are important social determinants of health, but less is known about the health implications and health-related content of protective immigration policies, which may also represent critical determinants of health. We conducted a content analysis of types, themes, and health-related language in 328 "sanctuary" policies enacted between 2009 and 2017 in the United States. Sanctuary policies were introduced in thirty-two states and Washington, D.C., most frequently in 2014 and 2017. More than two-thirds of policies (67.6 percent) contained language related to health, including direct references to access to services. Health-related themes commonly co-occurred with language related to supporting immigrants in communities, including themes of antidiscrimination, inclusion, trust, and privacy. Our work provides foundational, nuanced data about the scope and nature of sanctuary policies that can inform future research exploring the impacts of these policies on health and health care.

The needs of persons living with Alzheimer's disease and Alzheimer's disease-related dementia (AD/ADRD) are challenged by tremendous complexity impacting both care delivery and financing. Most persons living with dementia (PLWD) also suffer from other chronic medical or mental health conditions, which further burden quality of life and function. In addition to difficult treatment choices, optimal dementia care models likely involve people and services that are not typical pieces of the health care delivery system but are all critical partners-care partners, social workers, and community services, to name a few. More than 200 models of dementia care have demonstrated some efficacy. However, these successful interventions that might address much of the care needed by PLWD are uninsured in the United States, where insurance coverage has focused on acute care needs. This poses great difficulties for both care provision and care financing. In this article, we review these 3 key challenges: dementia care for those with chronic comorbid disease; care models that require people who are not typical providers in traditional care delivery systems; and the mandate to provide high-quality care that is currently not funded by usual health care insurance. We propose promising next steps that could substantially improve the lives of PLWD and the lives of their care partners, and highlight some of the many research questions that remain.

RATIONALE & OBJECTIVE:Immune activation is fundamental to the pathogenesis of many kidney diseases. Innate immune molecules such as soluble urokinase-type plasminogen activator receptor (suPAR) have been linked to the incidence and progression of chronic kidney disease (CKD). Whether other biomarkers of immune activation are associated with incident kidney failure with replacement therapy (KFRT) in African Americans with nondiabetic kidney disease is unclear. STUDY DESIGN:Prospective cohort. SETTING & PARTICIPANTS:African American Study of Kidney Disease and Hypertension (AASK) participants with available baseline serum samples for biomarker measurement. PREDICTORS:Baseline serum levels of soluble tumor necrosis factor receptor 1 (sTNFR1), sTNFR2, tumor necrosis factor α (TNF-α), and interferon γ (IFN-γ). OUTCOMES:Incident KFRT, all-cause mortality. ANALYTICAL APPROACH:Cox proportional hazards models. RESULTS:, and median urinary protein-creatinine ratio was 0.09g/g at baseline. Over a median follow up of 9.6 years, there were 161 (32%) KFRT and 113 (23%) death events. In models adjusted for demographic and clinical factors and baseline kidney function, each 2-fold higher baseline level of sTNFR1, sTNFR2, and TNF-α was associated with 3.66-fold (95% CI, 2.31-5.80), 2.29-fold (95% CI, 1.60-3.29), and 1.35-fold (95% CI, 1.07-1.71) greater risks of KFRT, respectively; in comparison, each doubling of baseline suPAR concentration was associated with 1.39-fold (95% CI, 1.04-1.86) greater risk of KFRT. sTNFR1, sTNFR2, and TNF-α were also significantly associated with death (up to 2.2-fold higher risks per 2-fold higher baseline levels; P≤0.01). IFN-γ was not associated with either outcome. None of the biomarkers modified the association of APOL1 high-risk status (genetic risk factors for kidney disease among individuals of African ancestry) with KFRT (P>0.05 for interaction). LIMITATIONS:Limited generalizability to other ethnic groups or causes of CKD. CONCLUSIONS:Among African Americans with CKD attributed to hypertension, baseline levels of sTNFR1, sTNFR2, and TNF-α but not IFN-γ were associated with KFRT and mortality.