Racial, ethnic and neighborhood socioeconomic differences in incidence of dementia: A regional retrospective cohort study.

BACKGROUND: Evidence on the effects of neighborhood socioeconomic disadvantage on dementia risk in racially and ethically diverse populations is limited. Our objective was to evaluate the relative extent to which neighborhood disadvantage accounts for racial/ethnic variation in dementia incidence rates. Secondarily, we evaluated the spatial relationship between neighborhood disadvantage and dementia risk. METHODS: In this retrospective study using electronic health records (EHR) at two regional health systems in Northeast Ohio, participants included 253,421 patients aged >60 years who had an outpatient primary care visit between January 1, 2005 and December 31, 2015. The date of the first qualifying visit served as the study baseline. Cumulative incidence of composite dementia outcome, defined as EHR-documented dementia diagnosis or dementia-related death, stratified by neighborhood socioeconomic deprivation (as measured by Area Deprivation Index) was determined by competing-risk regression analysis, with non-dementia-related death as the competing risk. Fine-Gray sub-distribution hazard ratios were determined for neighborhood socioeconomic deprivation, race/ethnicity, and clinical risk factors. The degree to which neighborhood socioeconomic position accounted for racial/ethnic disparities in the incidence of composite dementia outcome was evaluated via mediation analysis with Poisson rate models. RESULTS: Increasing neighborhood disadvantage was associated with increased risk of EHR-documented dementia diagnosis or dementia-related death (most vs. least disadvantaged ADI quintile HR = 1.76, 95% confidence interval = 1.69-1.84) after adjusting for age and sex. The effect of neighborhood disadvantage on this composite dementia outcome remained after accounting for known medical risk factors of dementia. Mediation analysis indicated that neighborhood disadvantage accounted for 34% and 29% of the elevated risk for composite dementia outcome in Hispanic and Black patients compared to White patients, respectively. CONCLUSION: Neighborhood disadvantage is related to the risk of EHR-documented dementia diagnosis or dementia-related death and accounts for a portion of racial/ethnic differences in dementia burden, even after adjustment for clinically important confounders.

Miscalibration of lung allocation models leads to inaccurate waitlist mortality predictions.

The importance of waitlist (WL) mortality risk estimates will increase with the adoption of the US Composite Allocation Score (CAS) system. Calibration is rarely assessed in clinical prediction models, yet it is a key factor in determining access to lung transplant. We assessed the calibration of the WL-lung allocation score (LAS)/CAS models and developed alternative models to minimize miscalibration. Scientific Registry of Transplant Recipients data from 2015 to 2020 were used to assess the calibration of the WL model and for subgroups (age, sex, diagnosis, and race/ethnicity). Three recalibrated models were developed and compared: (1) simple recalibration model (SRM), (2) weighted recalibration model 1 (WRM1), and (3) weighted recalibration model 2 (WRM2). The current WL-LAS/CAS model underestimated risk for 78% of individuals (predicted mortality risk, <42%) and overpredicted risk for 22% of individuals (predicted mortality risk, ≥42%), with divergent results among subgroups. Error measures improved in SRM, WRM1, and WRM2. SRM generally preserved candidate rankings, whereas WRM1 and WRM2 led to changes in ranking by age and diagnosis. Differential miscalibration occurred in the WL-LAS/CAS model, which improved with recalibration measures. Further inquiry is needed to develop mortality models in which risk predictions approximate observed data to ensure accurate ranking and timely access to transplant. IMPACT: With changes to the lung transplant allocation system planned in 2023, evaluation of the accuracy and precision of survival models used to rank candidates for lung transplant is important. The waitlist model underpredicts risk for 78% of US transplant candidates with an unequal distribution of miscalibration across subgroups leading to inaccurate ranking of transplant candidates. This work will serve to inform future efforts to improve modeling efforts in the US lung transplant allocation system.

Refining the Lung Allocation Score Models Fails to Improve Discrimination Performance.

BACKGROUND: As broader geographic sharing is implemented in lung transplant allocation through the Composite Allocation Score (CAS) system, models predicting waitlist and posttransplant (PT) survival will become more important in determining access to organs. RESEARCH QUESTION: How well do CAS survival models perform, and can discrimination performance be improved with alternative statistical models or machine learning approaches? STUDY DESIGN AND METHODS: Scientific Registry for Transplant Recipients (SRTR) data from 2015-2020 were used to build seven waitlist (WL) and data from 2010-2020 to build similar PT models. These included the (I) current lung allocation score (LAS)/CAS model; (II) re-estimated WL-LAS/CAS model; (III) model II incorporating nonlinear relationships; (IV) random survival forests model; (V) logistic model; (VI) linear discriminant analysis; and (VII) gradient-boosted tree model. Discrimination performance was evaluated at 1, 3, and 6 months on the waiting list and 1, 3, and 5 years PT. Area under the curve (AUC) values were estimated across subgroups. RESULTS: WL model performance was similar across models with the greatest discrimination in the baseline cohort (AUC 0.93) and declined to 0.87-0.89 for 3-month and 0.84-0.85 for 6-month predictions and further diminished for residual cohorts. Discrimination performance for PT models ranged from AUC 0.58-0.61 and remained stable with increasing forecasting times but was slightly worse for residual cohorts. WL and PT variability in AUC was greatest for individuals with Medicaid insurance. INTERPRETATION: Use of alternative modeling strategies and contemporary cohorts did not improve performance of models determining access to lung transplant.

Evaluating and Modeling Neighborhood Diversity and Health Using Electronic Health Records.

BACKGROUND: Electronic health records (EHRs) provide researchers with abundant sample sizes, detailed clinical data, and other advantages for performing high-quality observational health research on diverse populations. We review and demonstrate strategies for the design and analysis of cohort studies on neighborhood diversity and health, including evaluation of the effects of race, ethnicity, and neighborhood socioeconomic position on disease prevalence and health outcomes, using localized EHR data. METHODS: Design strategies include integrating and harmonizing EHR data across multiple local health systems and defining the population(s) of interest and cohort extraction procedures for a given analysis based on the goal(s) of the study. Analysis strategies address inferential goals, including the mechanistic study of social risks, statistical adjustment for differences in distributions of social and neighborhood-level characteristics between available EHR data and the underlying local population, and inference on individual neighborhoods. We provide analyses of local variation in mortality rates within Cuyahoga County, Ohio. RESULTS: When the goal of the analysis is to adjust EHR samples to be more representative of local populations, sampling and weighting are effective. Causal mediation analysis can inform effects of racism (through racial residential segregation) on health outcomes. Spatial analysis is appealing for large-scale EHR data as a means for studying heterogeneity among neighborhoods even at a given level of overall neighborhood disadvantage. CONCLUSIONS: The methods described are a starting point for robust EHR-derived cohort analysis of diverse populations. The methods offer opportunities for researchers to pursue detailed analyses of current and historical underlying circumstances of social policy and inequality. Investigators can employ combinations of these methods to achieve greater robustness of results. HIGHLIGHTS: EHR data are an abundant resource for studying neighborhood diversity and health.When using EHR data for these studies, careful consideration of the goals of the study should be considered in determining cohort specifications and analytic approaches.Causal mediation analysis, stratification, and spatial analysis are effective methods for characterizing social mechanisms and heterogeneity across localized populations.

Multiple Sclerosis Performance Test: Technical Development and Usability.

INTRODUCTION: In the clinic, the assessment of patients with multiple sclerosis (MS) is typically qualitative and non-standardized. OBJECTIVES: To describe the MS Performance Test (MSPT), an iPad Air® 2 (Apple, Cupertino, CA, USA)-based neurological assessment platform allowing patients to input relevant information without the aid of a medical technician, creating a longitudinal, clinically meaningful, digital medical record. To report results from human factor (HF) and usability studies, and the initial large-scale implementation in a practice setting. METHODS: The HF study examined use-error patterns in small groups of MS patients and healthy controls (n = 14), the usability study assessed the effectiveness of patient interaction with the tool by patients with a range of MS disability (n = 60) in a clinical setting, and the implementation study deployed the MSPT across a diverse population of patients (n = 1000) in a large MS center for routine clinical care. RESULTS: MSPT assessments were completed by all users in the HF study; minor changes to design were recommended. In the usability study, 73% of patients with MS completed the MSPT, with an average administration time of 32 min; 85% described their experience with the tool as satisfactory. In the initial implementation for routine care, 84% of patients with MS completed the MSPT, with an average administration time of 28 min. CONCLUSION: Patients with MS with varying disability levels completed the MSPT with minimal or no supervision, resulting in comprehensive, efficient, standardized, quantitative, clinically meaningful data collection as part of routine medical care, thus allowing for large-scale, real-world evidence generation. FUNDING: Biogen. TRIAL REGISTRATION: NCT02664324.

Utility of Montreal Cognitive Assessment in Differentiating Dementia With Lewy Bodies From Alzheimer's Dementia.

Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) are the 2 most common neurodegenerative dementias. Identification of patients with DLB is necessary to guide appropriate clinical management and medication trials. Patients with DLB are reported to perform poorly on tasks of visuospatial and executive function, compared to patients with AD who perform poorly on memory tasks. Using the Montreal Cognitive Assessment, we found that patients with DLB (n = 73) had statistically significant lower performance in clock drawing (visuospatial and executive function) and higher performance in delayed recall (memory) subscores compared to patients with AD (n = 57). This score pattern should raise suspicion for a DLB diagnosis at initial evaluation of patients with dementia.

Processing speed test: Validation of a self-administered, iPad®-based tool for screening cognitive dysfunction in a clinic setting.

BACKGROUND: Cognitive dysfunction is common in multiple sclerosis (MS) patients and has important consequences for daily activities, yet, unlike motor function, is not routinely assessed in the clinic setting. We developed the Processing Speed Test (PST), a self-administered iPad®-based tool to measure MS-related deficits in processing speed. OBJECTIVE: To determine whether the PST is valid for screening cognitive dysfunction by comparing it to the paper-and-pencil Symbol Digit Modalities Test (SDMT). METHODS: We assessed PST test-retest reliability, sensitivity of PST and SDMT in discriminating MS patients from healthy controls (HC), convergent validity between PST and SDMT, correlations between T2 lesion load and PST and SDMT, and PST performance with and without technician present during administration. RESULTS: PST had excellent test-retest reliability, was highly correlated with SDMT, was slightly more sensitive than SDMT in discriminating MS from HC groups, and correlated better with cerebral T2 lesion load than did SDMT. Finally, PST performance was no different with or without a technician in the testing environment. CONCLUSION: PST has advantages over SDMT because of its efficient administration, scoring, and potential for medical record or research database integration. PST is a practical tool for routine screening of processing speed deficits in the MS clinic.

Cross-sectional and longitudinal multimodal structural imaging in prodromal Huntington's disease.

OBJECTIVES: Diffusivity in white-matter tracts is abnormal throughout the brain in cross-sectional studies of prodromal Huntington's disease. To date, longitudinal changes have not been observed. The present study investigated cross-sectional and longitudinal changes in white-matter diffusivity in relationship to the phase of prodromal Huntington's progression, and compared them with changes in brain volumes and clinical variables that track disease progression. METHODS: Diffusion MRI profiles were studied for 2 years in 37 gene-negative controls and 64 prodromal Huntington's disease participants in varied phases of disease progression. To estimate the relative importance of diffusivity metrics in the prodromal phase, group effects were rank ordered relative to those obtained from analyses of brain volumes, motor, cognitive, and sensory variables. RESULTS: First, at baseline diffusivity was abnormal throughout all tracts, especially as individuals approached a manifest Huntington's disease diagnosis. Baseline diffusivity metrics in 6 tracts and basal ganglia volumes best distinguished among the groups. Second, group differences in longitudinal change in diffusivity were localized to the superior fronto-occipital fasciculus, most prominently in individuals closer to a diagnosis. Group differences were also observed in longitudinal changes of most brain volumes, but not clinical variables. Last, increases in motor symptoms across time were associated with greater changes in the superior fronto-occipital fasciculus diffusivity and corpus callosum, cerebrospinal fluid, and lateral ventricle volumes. CONCLUSIONS: These novel findings provide new insights into changes within 2 years in different facets of brain structure and their clinical relevance to changes in symptomatology that is decisive for a manifest Huntington's diagnosis. © 2016 International Parkinson and Movement Disorder Society.

Network topology and functional connectivity disturbances precede the onset of Huntington's disease.

Cognitive, motor and psychiatric changes in prodromal Huntington's disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington's disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington's disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington's disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington's disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression.

Disruption of caudate working memory activation in chronic blast-related traumatic brain injury.

Mild to moderate traumatic brain injury (TBI) due to blast exposure is frequently diagnosed in veterans returning from the wars in Iraq and Afghanistan. However, it is unclear whether neural damage resulting from blast TBI differs from that found in TBI due to blunt-force trauma (e.g., falls and motor vehicle crashes). Little is also known about the effects of blast TBI on neural networks, particularly over the long term. Because impairment in working memory has been linked to blunt-force TBI, the present functional magnetic resonance imaging (fMRI) study sought to investigate whether brain activation in response to a working memory task would discriminate blunt-force from blast TBI. Twenty-five veterans (mean age = 29.8 years, standard deviation = 6.01 years, 1 female) who incurred TBI due to blast an average of 4.2 years prior to enrollment and 25 civilians (mean age = 27.4 years, standard deviation = 6.68 years, 4 females) with TBI due to blunt-force trauma performed the Sternberg Item Recognition Task while undergoing fMRI. The task involved encoding 1, 3, or 5 items in working memory. A group of 25 veterans (mean age = 29.9 years, standard deviation = 5.53 years, 0 females) and a group of 25 civilians (mean age = 27.3 years, standard deviation = 5.81 years, 0 females) without history of TBI underwent identical imaging procedures and served as controls. Results indicated that the civilian TBI group and both control groups demonstrated a monotonic relationship between working memory set size and activation in the right caudate during encoding, whereas the blast TBI group did not (p < 0.05, corrected for multiple comparisons using False Discovery Rate). Blast TBI was also associated with worse performance on the Sternberg Item Recognition Task relative to the other groups, although no other group differences were found on neuropsychological measures of episodic memory, inhibition, and general processing speed. These results could not be attributed to caudate atrophy or the presence of PTSD symptoms. Our results point to a specific vulnerability of the caudate to blast injury. Changes in activation during the Sternberg Item Recognition Task, and potentially other tasks that recruit the caudate, may serve as biomarkers for blast TBI.

Functional connectivity of primary motor cortex is dependent on genetic burden in prodromal Huntington disease.

Subtle changes in motor function have been observed in individuals with prodromal Huntington disease (prHD), but the underlying neural mechanisms are not well understood nor is the cumulative effect of the disease (disease burden) on functional connectivity. The present study examined the resting-state functional magnetic resonance imaging (rs-fMRI) connectivity of the primary motor cortex (M1) in 16 gene-negative (NEG) controls and 48 gene-positive prHD participants with various levels of disease burden. The results showed that the strength of the left M1 connectivity with the ipsilateral M1 and somatosensory areas decreased as disease burden increased and correlated with motor symptoms. Weakened M1 connectivity within the motor areas was also associated with abnormalities in long-range connections that evolved with disease burden. In this study, M1 connectivity was decreased with visual centers (bilateral cuneus), but increased with a hub of the default mode network (DMN; posterior cingulate cortex). Changes in connectivity measures were associated with worse performance on measures of cognitive-motor functioning. Short- and long-range functional connectivity disturbances were also associated with volume loss in the basal ganglia, suggesting that weakened M1 connectivity is partly a manifestation of striatal atrophy. Altogether, the results indicate that the prodromal phase of HD is associated with abnormal interhemispheric interactions among motor areas and disturbances in the connectivity of M1 with visual centers and the DMN. These changes may, respectively, contribute to increased motor symptoms, visuomotor integration problems, and deficits in the executive control of movement as individuals approach a manifest diagnosis.

Disruption of response inhibition circuits in prodromal Huntington disease.

Cognitive changes in the prodromal phase of Huntington disease (prHD) are found in multiple domains, yet their neural bases are not well understood. One component process that supports cognition is inhibitory control. In the present fMRI study, we examined brain circuits involved in response inhibition in 65 prHD participants and 36 gene-negative (NEG) controls using the stop signal task (SST). PrHD participants were subdivided into three groups (LOW, MEDIUM, HIGH) based on their CAG-Age Product (CAP) score, an index of genetic exposure and a proxy for expected time to diagnosis. Poorer response inhibition (stop signal duration) correlated with CAP scores. When response inhibition was successful, activation of the classic frontal inhibitory-network was normal in prHD, yet stepwise reductions in activation with proximity to diagnosis were found in the posterior ventral attention network (inferior parietal and temporal cortices). Failures in response inhibition in prHD were related to changes in inhibition centers (supplementary motor area (SMA)/anterior cingulate and inferior frontal cortex/insula) and ventral attention networks, where activation decreased with proximity to diagnosis. The LOW group showed evidence of early compensatory activation (hyperactivation) of right-hemisphere inhibition and attention reorienting centers, despite an absence of cortical atrophy or deficits on tests of executive functioning. Moreover, greater activation for failed than successful inhibitions in an ipsilateral motor-control network was found in the control group, whereas such differences were markedly attenuated in all prHD groups. The results were not related to changes in cortical volume and thickness, which did not differ among the groups. However, greater hypoactivation of classic right-hemisphere inhibition centers [inferior frontal gyrus (IFG)/insula, SMA/anterior cingulate cortex (ACC)] during inhibition failures correlated with greater globus pallidus atrophy. These results are the first to demonstrate that response inhibition in prHD is associated with altered functioning in brain networks that govern inhibition, attention, and motor control.

Higher working memory predicts slower functional decline in autopsy-confirmed Alzheimer's disease.

BACKGROUND: There is heterogeneity in the pattern of early cognitive deficits in Alzheimer's disease (AD). However, whether the severity of initial cognitive deficits relates to different clinical trajectories of AD progression is unclear. OBJECTIVE: To determine if deficits in specific cognitive domains at the initial visit relate to the rate of progression in clinical trajectories of AD dementia. METHODS: 68 subjects from the National Alzheimer's Coordinating Center database who had autopsy-confirmed AD as the primary diagnosis and at least 3 serial assessments a year apart, with a Mini-Mental State Examination (MMSE) score >15 and a Clinical Dementia Rating Scale-Global (CDR-G) score ≤1 at the initial visit were included. A mixed regression model was used to examine the association between initial neuropsychological performance and rate of change on the MMSE and CDR Sum of Boxes. RESULTS: Preservation of working memory, but not episodic memory, in the mild cognitive impairment and early dementia stages of AD relates to slower rate of functional decline. DISCUSSION: These findings are relevant for estimating the rate of decline in AD clinical trials and in counseling patients and families. Improving working memory performance as a possible avenue to decrease the rate of functional decline in AD dementia warrants closer investigation.

Neural activation during response inhibition differentiates blast from mechanical causes of mild to moderate traumatic brain injury.

Military personnel involved in Operations Enduring Freedom and Iraqi Freedom (OEF/OIF) commonly experience blast-induced mild to moderate traumatic brain injury (TBI). In this study, we used task-activated functional MRI (fMRI) to determine if blast-related TBI has a differential impact on brain activation in comparison with TBI caused primarily by mechanical forces in civilian settings. Four groups participated: (1) blast-related military TBI (milTBI; n=21); (2) military controls (milCON; n=22); (3) non-blast civilian TBI (civTBI; n=21); and (4) civilian controls (civCON; n=23) with orthopedic injuries. Mild to moderate TBI (MTBI) occurred 1 to 6 years before enrollment. Participants completed the Stop Signal Task (SST), a measure of inhibitory control, while undergoing fMRI. Brain activation was evaluated with 2 (mil, civ)×2 (TBI, CON) analyses of variance, corrected for multiple comparisons. During correct inhibitions, fMRI activation was lower in the TBI than CON subjects in regions commonly associated with inhibitory control and the default mode network. In contrast, inhibitory failures showed significant interaction effects in the bilateral inferior temporal, left superior temporal, caudate, and cerebellar regions. Specifically, the milTBI group demonstrated more activation than the milCON group when failing to inhibit; in contrast, the civTBI group exhibited less activation than the civCON group. Covariance analyses controlling for the effects of education and self-reported psychological symptoms did not alter the brain activation findings. These results indicate that the chronic effects of TBI are associated with abnormal brain activation during successful response inhibition. During failed inhibition, the pattern of activation distinguished military from civilian TBI, suggesting that blast-related TBI has a unique effect on brain function that can be distinguished from TBI resulting from mechanical forces associated with sports or motor vehicle accidents. The implications of these findings for diagnosis and treatment of TBI are discussed.

Examining neural correlates of skill acquisition in a complex videogame training program.

Acquisition of complex skills is a universal feature of human behavior that has been conceptualized as a process that starts with intense resource dependency, requires effortful cognitive control, and ends in relative automaticity on the multi-faceted task. The present study examined the effects of different theoretically based training strategies on cortical recruitment during acquisition of complex video game skills. Seventy-five participants were recruited and assigned to one of three training groups: (1) Fixed Emphasis Training (FET), in which participants practiced the game, (2) Hybrid Variable-Priority Training (HVT), in which participants practiced using a combination of part-task training and variable priority training, or (3) a Control group that received limited game play. After 30 h of training, game data indicated a significant advantage for the two training groups relative to the control group. The HVT group demonstrated enhanced benefits of training, as indexed by an improvement in overall game score and a reduction in cortical recruitment post-training. Specifically, while both groups demonstrated a significant reduction of activation in attentional control areas, namely the right middle frontal gyrus, right superior frontal gyrus, and the ventral medial prefrontal cortex, participants in the control group continued to engage these areas post-training, suggesting a sustained reliance on attentional regions during challenging task demands. The HVT group showed a further reduction in neural resources post-training compared to the FET group in these cognitive control regions, along with reduced activation in the motor and sensory cortices and the posteromedial cortex. Findings suggest that training, specifically one that emphasizes cognitive flexibility can reduce the attentional demands of a complex cognitive task, along with reduced reliance on the motor network.