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• Alzheimer's Disease (AD) is a major cause of dementia in the United States. • Non-traditional risk factors can help identify areas of higher AD Burden. • Machine learning techniques can help unravel this complex relationship. Geographical disparities in mortality among Alzheimer's disease (AD) patients have been reported and complex sociodemographic and environmental determinants of health (SEDH) may be contributing to this variation. Therefore, we aimed to explore high-risk SEDH factors possibly associated with all-cause mortality in AD across US counties using machine learning (ML) methods. We performed a cross-sectional analysis of individuals ≥65 years with any underlying cause of death but with AD in the multiple causes of death certificate (ICD-10,G30) between 2016 and 2020. Outcomes were defined as age-adjusted all-cause mortality rates (per 100,000 people). We analyzed 50 county-level SEDH and Classification and Regression Trees (CART) was used to identify specific county-level clusters. Random Forest, another ML technique, evaluated variable importance. CART's performance was validated using a "hold-out" set of counties. Overall, 714,568 individuals with AD died due to any cause across 2,409 counties during 2016–2020. CART identified 9 county clusters associated with an 80.1% relative increase of mortality across the spectrum. Furthermore, 7 SEDH variables were identified by CART to drive the categorization of clusters, including High School Completion (%), annual Particulate Matter 2.5 Level in Air, live births with Low Birthweight (%), Population under 18 years (%), annual Median Household Income in US dollars ($), population with Food Insecurity (%), and houses with Severe Housing Cost Burden (%). ML can aid in the assimilation of intricate SEDH exposures associated with mortality among older population with AD, providing opportunities for optimized interventions and resource allocation to reduce mortality among this population. [ABSTRACT FROM AUTHOR]

We used a collective impact model to form a statewide diabetes quality improvement collaborative to improve diabetes outcomes and advance diabetes health equity. Between 2020 and 2022, in collaboration with the Ohio Department of Medicaid, Medicaid Managed Care Plans, and Ohio's seven medical schools, we recruited 20 primary care practices across the state. The percentage of patients with hemoglobin A1c greater than 9% improved from 25% to 20% over two years. Applying our model more broadly could accelerate improvement in diabetes outcomes. ( Am J Public Health. 2023;113(12):1254-1257. https://doi.org/10.2105/AJPH.2023.307410).

Background: Accurate assessment of atherosclerotic cardiovascular disease (ASCVD) risk across heterogeneous populations is needed for effective primary prevention. Little is known about the performance of standard cardiovascular risk factors in older adults., Objective: To evaluate the performance of the American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) risk model, as well as the underlying cardiovascular risk factors, among adults older than 65 years., Design and Setting: Retrospective cohort derived from a regional referral system's electronic medical records., Participants: A total of 25 349 patients who were 65 years or older at study baseline (date of the first outpatient lipid panel taken between 2007 and 2010)., Measurements: Exposures of interest were traditional cardiovascular risk factors, as defined by inclusion in the PCE model. The primary outcome was major ASCVD events, defined as a composite of myocardial infarctions, stroke, and cardiovascular death., Results: The PCE and internally estimated models produced similar risk distributions for white men aged 65 to 74 years. For all other groups, PCE predictions were generally lower than those of the internal models, particularly for African Americans. Discrimination of the PCE was poor for all age groups, with concordance index (95% confidence interval) estimates of 0.62 (0.60-0.64), 0.56 (0.54-0.57), and 0.52 (0.49-0.54) among patients aged 65 to 74, 75 to 84, and 85 years and older, respectively. Reestimating relationships within these age groups resulted in better calibration but negligible improvements in discrimination. Blood pressure, total cholesterol, and diabetes either were not associated at all or had inverse associations in the older age groups., Conclusion: Traditional clinical risk factors for cardiovascular disease failed to accurately characterize risk in a contemporary population of Medicare-aged patients. Among those aged 85 years and older, some traditional risk factors were not associated with ASCVD events. Better risk models are needed to appropriately inform treatment decision making for the growing population of older adults. J Am Geriatr Soc 68:754-761, 2020., (© 2020 The American Geriatrics Society.)

Importance: Immune dysregulation can increase the risk of infection, malignant neoplasms, and cardiovascular disease, but improved methods are needed to identify and quantify immunologic hazard in the general population., Objective: To determine whether lymphopenia is associated with reduced survival in outpatients., Design, Setting, and Participants: This retrospective cohort study of the National Health and Nutrition Examination Survey (NHANES) included participants enrolled from January 1, 1999, to December 31, 2010, a large outpatient sample representative of the US adult population. Associations were evaluated between lymphopenia and other immunohematologic (IH) markers, clinical features, and survival during 12 years of follow-up, completed on December 31, 2011. Spearman correlations, Cox proportional hazards regression models, and Kaplan-Meier curves were used in univariable and multivariable models, allowing for nonlinear associations with bivariate cubic polynomials. Data were analyzed from September 1, 2018, through July 24, 2019., Exposures: Absolute lymphocyte counts (ALC), red blood cell distribution width (RDW), and C-reactive protein (CRP) level., Main Outcomes and Measures: All-cause survival., Results: Among the 31 178 participants, the median (interquartile range) age at baseline was 45 (30-63) years, 16 093 (51.6%) were women, 16 260 (52.2%) were nonwhite, and overall 12-year rate of survival was 82.8%. Relative lymphopenia (≤1500/μL) and severe lymphopenia (≤1000/μL) were observed in 20.1% and 3.0%, respectively, of this general population and were associated with increased risk of mortality (age- and sex-adjusted hazard ratios [HRs], 1.3 [95% CI, 1.2-1.4] and 1.8 [95% CI, 1.6-2.1], respectively) due to cardiovascular and noncardiovascular causes. Lymphopenia was also associated with worse survival in multivariable models, including traditional clinical risk factors, and this risk intensified when accompanied by bone marrow dysregulation (elevated RDW) and/or inflammation (elevated CRP level). Ten-year mortality ranged from 3.8% to 62.1% based on lymphopenia status, tertile of CRP level, and tertile of RDW. A high-risk IH profile was nearly twice as common as type 2 diabetes (19.3% and 10.0% of participants, respectively) and associated with a 3-fold risk of mortality (HR, 3.2; 95% CI, 2.6-4.0). Individuals aged 70 to 79 years with low IH risk had a better 10-year survival (74.1%) than those who were a decade younger with a high-risk IH profile (68.9%)., Conclusions and Relevance: These findings suggest that lymphopenia is associated with reduced survival independently of and additive to traditional risk factors, especially when accompanied by altered erythropoiesis and/or heightened inflammation. Immune risk may be analyzed as a multidimensional entity derived from routine tests, facilitating precision medicine and population health interventions.

This study examined (a) the extent of heterogeneity in the patterns of developmental trajectories of language development and academic functioning in children who have experienced maltreatment, (b) how maltreatment type (i.e., neglect or physical abuse) and timing of abuse explained variation in developmental trajectories, and (c) the extent to which individual protective factors (i.e., preschool attendance, prosocial skills), relationship protective factors (i.e., parental warmth, absence of past-year depressive episode, cognitive/verbal responsiveness) and community protective factors (i.e., neighborhood safety) promoted the development of resilient language/academic functioning trajectories. Longitudinal data analyses were conducted using cohort sequential Growth Mixture Model (CS-GMM) with a United States national representative sample of children reported to Child Protective Services (n=1,776). Five distinct developmental trajectories from birth to age 10 were identified including two resilient groups. Children who were neglected during infancy/toddlerhood or physically abused during preschool age were more likely to be in the poorer language/academic functioning groups (decreasing/recovery/decreasing and high decreasing) than the resilient high stable group. Child prosocial skills, caregiver warmth, and caregiver cognitive stimulation significantly predicted membership in the two resilient academic functioning groups (low increasing and high stable), after controlling for demographics and child physical abuse and neglect. Results suggest that it is possible for a maltreated child to successfully achieve competent academic functioning, despite the early adversity, and identifies three possible avenues of intervention points. This study also makes a significant contribution to the field of child development research through the novel use of CS-GMM, which has implications for future longitudinal data collection methodology., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Objective: Epilepsy is a chronic neurological condition that significantly increases risk of injury and premature death. Rates of mental illness are also disproportionately high in those with epilepsy, which can be attributed in part to the stress and stigma associated with epilepsy. Psychiatric conditions generally complicate the management of epilepsy, and understanding how psychiatric comorbidity affects use of crisis-based health resources could inform care approaches that help improve epilepsy care. To better understand effects of psychiatric comorbidity on epilepsy burden, we conducted a 5-year retrospective analysis of data from a large safety-net healthcare network and compared the occurrence of negative health events (NHEs), defined as emergency department (ED) visits and hospitalizations, among individuals with epilepsy and mental illness (E-MI) vs. those with epilepsy alone (E)., Methods: Electronic health record (EHR) data from a large Midwestern U.S. safety-net healthcare system were queried to identify a study population of adults ≥18years with a diagnosis of epilepsy, with or without mental illness. We assessed demographic and clinical characteristics for each of the 5years and compared NHEs between subgroups with E-MI vs. E. An additional analysis focused on those individuals who remained in the healthcare system over the entire 5-year study time frame (January, 2010 to December, 2014). Annual and cumulative NHE counts and hospital length of stay for individuals with E-MI and E were assessed, as were hospital discharge diagnoses., Results: The number (approximately 2000) and demographic characteristics of individuals with epilepsy who received care each year of the study period was relatively consistent. In 2014, mean age of individuals with epilepsy was 48 (range: 18-95), 48.2% were women, 51.5% were White, 37.9% were African-American, and 8.6% were Hispanic. In 2014, there were 1616 (78.6%) individuals in the subgroup with E and 439 (21.4%) in the subgroup with E-MI. Most clinical and demographic variables between the subgroups with E-MI and E were similar, except that individuals with E-MI were less likely to be employed or commercially insured. Overall, NHEs were common, with over 1/4 (27.5%) of all individuals with epilepsy having an ED visit during the year, 13.7% having hospitalization, and 34.2% having either an ED visit or hospitalization. Individuals with E-MI had significantly more NHEs compared to individuals with epilepsy only, as evidenced by higher rates of any NHE (p<.001), ED visits (p<.001), and hospitalizations (p<.001). The cumulative differential in ED and hospital use between subgroups with E-MI and E was substantial over a 5-year time period. While most NHEs were directly related to seizures for the overall group, substance-use complications appeared as a top reason for hospitalization only in the group with E-MI., Conclusions: Individuals with E-MI made up just over 20% of all people with epilepsy in a safety-net system and had higher rates of NHEs than those without mental illness. Better and earlier identification of individuals with E-MI, assistance with self-management including helping individuals to optimize ambulatory care settings as opposed to the ED, and treatment for substance use disorders could eventually reduce NHEs in this vulnerable subgroup of individuals with epilepsy., (Copyright © 2015 Elsevier Inc. All rights reserved.)