Faculty Bibliography

INTRODUCTION:The aim of this study was to assess the association of peripheral neuropathy (PN) as defined by monofilament insensitivity with mild cognitive impairment (MCI) and dementia in older adults with and without diabetes. METHODS:We conducted a cross-sectional analysis of 3,362 Black and White participants in the Atherosclerosis Risk in Communities Neurocognitive Study (ARIC-NCS) who underwent monofilament testing at visit 6 (2016-2017, age 71-94 years). Participants' cognitive status was classified by an adjudication committee as cognitively normal, MCI, or dementia after completing a comprehensive battery of neurocognitive assessments. We used logistic regression to evaluate the association of PN with MCI or dementia overall and stratified by diabetes status after adjusting for traditional dementia risk factors. We also compared age-adjusted brain MRI measures among a subset (N = 1,095) of participants with versus without PN. RESULTS:Overall, the prevalence of MCI (21.9% vs. 16.7%) and dementia (7.8% vs. 3.9%) were higher among participants with versus without PN (both p < 0.05). After adjustment, PN was positively associated with MCI or dementia in the overall study population (OR 1.45, 95% CI 1.23, 1.73). Results were similar by diabetes status (diabetes: OR 1.38, 95% CI 1.03-1.87; no diabetes: OR 1.48, 95% CI 1.20-1.83; p-for-interaction = 0.46). Age-adjusted total and lobar brain volumes were significantly lower in participants with versus without PN (both, p < 0.05). DISCUSSION/CONCLUSIONS:PN as defined by monofilament insensitivity was associated with cognitive status independent of vascular risk factors and regardless of diabetes status. Our findings support a connection between PN and cognitive impairment, even in the absence of diabetes.

The COVID-19 pandemic drove a rapid transition to virtual care experiences for graduate medical trainees. Core training competencies have expanded to incorporate virtual contexts, however there is limited knowledge of the optimal design of virtual care training tools for learners. In this study, we describe the application of a Design Thinking approach to the identification and co-design of novel training tools to support residents and precepting attending physicians in virtual ambulatory care practice. We applied the model of "Empathize, Define, Ideate, Prototype, and Test" via a mixed methods approach to (1) explore the needs, preferences, and concerns of Internal Medicine residents and outpatient precepting attendings regarding virtual ambulatory care training environments, and (2) evaluate, prototype, and test potential training tools. Eleven residents and eight attending physicians participated. Identified learner needs and problem areas included: improving virtual visit technical skills; acquiring virtual communication skills; adapting to the loss of shared in-person learning space and optimizing virtual learning environments; remediating non-virtual procedural competencies; and educating on new documentation requirements. Key solution areas included: virtual precepting support tools; digital information and education dissemination tools; and strategies for management of technical issues. Several prototypes were proposed, with a single tool (a virtual preceptor tip sheet) deployed in clinical practice. Residents found the workshop program improved their understanding of Design Thinking and its relevance to healthcare. Ultimately, Design Thinking can be deployed to engage medical trainees and precepting attendings in the effective development of novel educational tools for the virtual care learning environment.

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