Faculty Bibliography

INTRODUCTION:This study aimed to characterize the association of cognitive decline starting in midlife with brain pathology in late life in the absence of dementia. METHODS:Nondemented Atherosclerosis Risk in Communities participants with brain imaging, all cognitive factor scores (CFSs), and nonmissing covariates were included. CFSs were collected at three visits across 21 years (1990-2013) (short-term cognitive change [1990-1996], long-term cognitive change [1990-2013]), and brain magnetic resonance imaging and florbetapir positron emission tomography (PET) imaging were collected in 2011-13 (PET subset n = 327). Outcomes of interest were total and regional brain volumes (cm3), log2 (white matter hyperintensity volume), white matter integrity (fractional anisotropy, mean diffusivity), ≥1 lacunar infarct (3-20 mm), and elevated brain β-amyloid (SUVR >1.2). Multivariable linear/logistic regression related outcomes to CFS slopes after adjusting for demographics and total intracranial volume. RESULTS:At baseline, the 1,734 participants had a mean (SD) age of 55 (5.2) years, and were 60% female and 26% Black. After adjustment, a 1-SD larger long-term decline in CFS was associated with a smaller relative total brain volume by 1.2% (95% CI: 1.0, 1.5), a smaller relative temporal lobe meta region volume by 1.9% (1.5, 2.3), a 13% (9, 17) larger volume of white matter hyperintensities, a 1.3-fold (1.2, 1.4) higher odds of having ≥1 lacune, and 1.7-fold (1.3, 2.2) higher odds of elevated brain β-amyloid deposition and worse white matter integrity. Some long-term associations were also found for midlife short-term declines in CFS. CONCLUSIONS:This study provides evidence that starting in midlife, short-term and long-term declines in cognition are associated with multiple deleterious late-life differences in nondemented brains.

Eighty-one percent of persons living with cancer have an emergency department (ED) visit within the last 6 months of life. Many cancer patients in the ED are at an advanced stage with high symptom burden and complex needs, and over half is admitted to an inpatient setting. Innovative models of care have been developed to provide high quality, ambulatory, and home-based care to persons living with serious, life-limiting illness, such as advanced cancer. New care models can be divided into a number of categories based on either prognosis (e.g., greater than or less than 6 months), or level of care (e.g., lower versus higher intensity needs, such as intravenous pain/nausea medication or frequent monitoring), and goals of care (e.g., cancer-directed treatment versus symptom-focused care only). We performed a narrative review to (1) compare models of care for seriously ill cancer patients in the ED and (2) examine factors that may hasten or impede wider dissemination of these models.

INTRODUCTION/UNASSIGNED:In order to obtain FDA Marketing Authorization for aid in the diagnosis of concussion, an eye tracking study in an intended use population was conducted. METHODS/UNASSIGNED:Potentially concussed subjects recruited in emergency department and concussion clinic settings prospectively underwent eye tracking and a subset of the Sport Concussion Assessment Tool 3 at 6 sites. The results of an eye tracking-based classifier model were then validated against a pre-specified algorithm with a cutoff for concussed vs. non-concussed. The sensitivity and specificity of eye tracking were calculated after plotting of the receiver operating characteristic curve and calculation of the AUC (area under curve). RESULTS/UNASSIGNED:= 282) was 31.6%. CONCLUSION/UNASSIGNED:A pre-specified algorithm and cutoff for diagnosis of concussion vs. non-concussion has a sensitivity and specificity that is useful as a baseline-free aid in diagnosis of concussion. Eye tracking has potential to serve as an objective "gold-standard" for detection of neurophysiologic disruption due to brain injury.

Background: We recently implemented the Age-Friendly Health System's 4Ms (What Matters, Medication, Mentation, and Mobility) framework in New York City Health + Hospitals/Bellevue Hospital Center's Geriatrics clinic to improve care of older adults.
Method(s): We examined the impact of 4Ms assessment on patient care and changes in care processes through specific interventions triggered after assessment. We conducted chart reviews of patient visits during March 2021, the first month of 4Ms implementation and identified interventions made during these visits. To assess "What Matters" providers asked "What Matters the most to you;" potentially inappropriate Medications (PIM) were identified using the Beers list; Mentation was evaluated using the Mini-Cog; and Mobility was determined using timed up and go (TUG) test. We used descriptive statistics to characterize findings.
Result(s): Among the 121 patients who had 4Ms assessment in March 2021, 85% (n=103) were asked "What Matters;" providers reviewed Medications for almost all (n=118; 98%) and conducted a Mini-Cog for 64% (n=78). Most not cognitively assessed were either previously screened (n=11; 9%) or had dementia (n=12; 10%). Providers used the TUG test for 87% (n=105). What Mattered to patients most commonly was "getting better" (n=24; 23%). There were 39 (33%) patients with potentially inappropriate Medications (including proton pump inhibitors, gabapentinoids, and NSAIDS) of which 10 (26%) Medications were either discontinued or reduced. Other interventions included further cognitive evaluation (n=2) and home care referrals (n=2) among 14 (18%) with an abnormal Mini- Cog. Among the 51 (42%) patients with an abnormal TUG, providers intervened for 19 (37%) with devices, referrals or home services.
Conclusion(s): The adoption of 4Ms assessment during routine visits identified issues with Medications, Mentation and Mobility, triggering several interventions for common geriatric conditions. 4Ms assessment is a helpful strategy to organize geriatric care, routinely assess patients for common geriatric syndromes, and improve care. Future directions include prioritizing interventions integrated with "What Matters" to maintain patient-centered care

Background: Neighborhood disadvantage influences health outcomes regardless of personal economic status, illustrating the importance of neighborhood context on health. The Area Deprivation index (ADI) establishes a ranking system of U.S. neighborhoods on state and national levels based on 17 neighborhood factors. Using data from an ongoing study of patients with dual diagnoses of diabetes and dementia, we investigated the relationship between ADI and diabetic outcomes, including glycemic control, blood pressure, and dementia severity.
Method(s): We conducted descriptive and bivariate statistics using 3 years of health record data from patients of NYU Langone Health. We included patients >=65 years, with ADRD and DM, and on DM medication. In addition to demographic measures and NY home addresses, we collected hemoglobin A1c, blood pressure, and assessed dementia severity, surveying proxies with the dementia severity rating scale (DSRS). We used ArcGIS and ADI data to link patient addresses to an ADI score. We stratified the sample into two groups: a low deprivation group with ADI scores 1-5, and a high deprivation group with ADI scores 6-10.
Result(s): Of those meeting inclusion criteria (n=996), most were over 75 years (73.5%), female (60.1%), white (71.2%), and not Hispanic or Latino (72.4%). Mean patient age was 81.3; standard deviation (SD): 7.6. More than 50% of patients had an NY state ADI score of 1, 2 or 3 out of 10, indicating that the majority of the population lived in neighborhoods of less disadvantage. 83.4% (n=831) of the population fell into the low deprivation group. There were no differences in hemoglobin A1c (7.09 vs. 7.01) or dementia severity (25.5 +/- 0.8 vs. 22.4 +/- 2.0) between low and high deprivation groups, respectively. However, systolic blood pressure was greater in high deprivation individuals (132.4 +/- 19.3 mm Hg vs. 128.6 +/- 18.2; p=0.02).
Conclusion(s): The ADI in this study was associated with blood pressure but not diabetic control or dementia severity. Less heterogeneity in disadvantage limited our ability to detect this potential social determinant of health. In a city, where neighborhood disadvantage changes from block to block, the influence of environment on health may be more difficult to detect

Background: Clinical trials are important to improve evidencebased care for persons living with dementia (PLWD) and for their care partners (dyads). Barriers to research recruitment are numerous, including care partners concerns' of ill health, cognitive impairment (CI) severity, and denial of need. The aim of this study is to determine whether a performance- or informant-based screening test for CI is associated with trial enrollment and whether mode of administration influences one's decision to participate.
Method(s): We used cross-sectional data from patients and caregivers who visited the EDs of New York University (NYU) and Indianapolis University (IU) during screening for the Program of Intensive Support in Emergency Departments (ED) for Care Partners of Cognitively Impaired Patients (POISED), which is testing a care management intervention. We offered CI screening to patients >75 years using the Mini-Cog and if unable to do this, we offered their care partners the Short Portable Informant Questionnaire of Cognitive Decline (IQ-CODE). We used chi-square tests and logistic regression to determine whether likelihood of enrollment differed between screening tests and mode of administration: in-person versus telephone.
Result(s): We screened 8860 patients or care partners (dyads) between 3/3/2018-4/1/2021, of which n=2840 at NYU and n=660 at IU had positive screens. Of these 3500 dyads, 2142 had a positive Mini-Cog (<2) and 1358 had a positive IQ-CODE (>3.40). We enrolled 13.9% (n=297) of positive Mini-Cogs and 14.5% (n=309) of positive in-person IQ-CODEs. During the pandemic we conducted all IQCODEs by phone and enrolled 34% (n=196) of those who screened positive. Adjusting for age, sex, and gender, compared to Mini-Cog screening, only those having positive IQCODES by phone were more likely to enroll (adjusted odds ratio (AOR): 3.75 (95% CI: 2.76, 5.11).
Conclusion(s): Higher enrollment using informant-based telephone screening after discharge suggests that care partner recognition of a problem and perhaps having less distraction from the ED visit may increase trial enrollment. Whether the pandemic was the predomant factor encouraging enrollment is unknown