Faculty Bibliography

BACKGROUND/UNASSIGNED:The burden of Alzheimer's disease and related dementias (AD/ADRD) in Costa Rica is expected to become one of the highest in the region. Early detection will help optimize resources and improve primary care interventions. The Montreal Cognitive Assessment (MoCA) has shown good sensitivity for detecting mild cognitive impairment (MCI), but specificity varies depending on the population. This motivated the analysis of different cutoffs to minimize false-positive classifications in a Costa Rican sample for its use in clinical settings. METHODS/UNASSIGNED:Data was analyzed from 516 memory clinic outpatients (148 cognitively normal, 260 MCI, 108 mild AD/ADRD; mean age 66.3 ± 10.8 years) who underwent complete neurological and neuropsychological assessment and were diagnosed by consensus. Optimal MoCA cutoff scores were identified using a multiple cutoff approach. RESULTS/UNASSIGNED:Overall, a cutoff score of ≥ 23 showed better accuracy to distinguish between normal cognition (NC) and MCI (sensitivity 73%, specificity 83%). When analyzed by educational levels, a cutoff score of ≥ 21 showed better accuracy for ≤ 6 years (sensitivity 80%, specificity 76%), ≥23 for 7-12 years (sensitivity 86%, specificity 76%) and ≥ 24 for > 12 years (sensitivity 70%, specificity 85%). For distinguishing MCI from mild AD/ADRD, the optimal overall cutoff score was ≥ 15 (sensitivity 66%, specificity 85%). When stratified by years of education, cutoff scores of ≥ 14 showed better accuracy for ≤ 6 years (sensitivity 70%, specificity 88%), ≥15 for 7-12 years (sensitivity 46%, specificity 95%) and ≥ 17 for > 12 years (sensitivity 67%, specificity 93%). CONCLUSIONS/UNASSIGNED:A MoCA cutoff score of ≥ 23 in the Costa Rican population showed better diagnostic accuracy for detecting MCI and may reduce the false positive rate. Our findings may be helpful for primary care clinical settings and further referral criteria.

Alzheimer's disease (AD) is a devastating, age-associated neurodegenerative disorder and the most common cause of dementia. The clinical continuum of AD spans from preclinical disease to subjective cognitive decline, mild cognitive impairment, and dementia stages (mild, moderate, and severe). Neuropathologically, AD is defined by the accumulation of amyloid β (Aβ) into extracellular plaques in the brain parenchyma and in the cerebral vasculature, and by abnormally phosphorylated tau that accumulates intraneuronally forming neurofibrillary tangles (NFTs). Development of treatment approaches that prevent or even reduce the cognitive decline because of AD has been slow compared to other major causes of death. Recently, the United States Food and Drug Administration gave full approval to 2 different Aβ-targeting monoclonal antibodies. However, this breakthrough disease modifying approach only applies to a limited subset of patients in the AD continuum and there are stringent eligibility criteria. Furthermore, these approaches do not prevent progression of disease, because other AD-related pathologies, such as NFTs, are not directly targeted. A non-mutually exclusive alternative is to address lifestyle interventions that can help reduce the risk of AD and AD-related dementias (ADRD). It is estimated that addressing such modifiable risk factors could potentially delay up to 40% of AD/ADRD cases. In this review, we discuss some of the many modifiable risk factors that may be associated with prevention of AD/ADRD and/or increasing brain resilience, as well as other factors that may interact with these modifiable risk factors to influence AD/ADRD progression. ANN NEUROL 2024.

BACKGROUND:Subjective cognitive decline (SCD), considered a preclinical dementia stage, is less understood in Hispanics, a high-risk group for dementia. We investigated SCD to mild cognitive impairment (MCI) progression risk, as well as baseline and longitudinal features of depressive symptoms, SCD complaints, and objective cognitive performance among Hispanics compared to non-Hispanic Whites (NHW). METHODS:Hispanic (n = 23) and NHW (n = 165) SCD participants were evaluated at baseline and 2-year follow-up. Evaluations assessed function, depressive symptoms, SCD, and objective cognitive performance. RESULTS:Hispanic ethnicity associated with a significantly increased risk of 2-year progression of SCD to MCI compared to NHW. This increased risk associated with increased depressive symptoms, distinctive SCD features, and elevated amnestic and non-amnestic objective cognitive decline. This supports further research to refine the assessment of preclinical dementia in this high-risk group.

Magnetization transfer MRI is sensitive to semi-solid macromolecules, including amyloid beta, and has previously been used to discriminate Alzheimer's disease (AD) patients from controls. Here, we fit an unconstrained 2-pool quantitative MT (qMT) model, i.e., without constraints on the longitudinal relaxation rate

Early identification of Alzheimer's disease (AD) and AD-related dementias (ADRD) has high clinical significance, both because of the potential to slow decline through initiating FDA-approved therapies and managing modifiable risk factors, and to help persons living with dementia and their families to plan before cognitive loss makes doing so challenging. However, substantial racial and ethnic disparities in early diagnosis currently lead to additional inequities in care, urging accurate and inclusive risk assessment programs. In this study, we trained an artificial intelligence foundation model to represent the electronic health records (EHR) data with a vast cohort of 1.2 million patients within a large health system. Building upon this foundation EHR model, we developed a predictive Transformer model, named TRADE, capable of identifying risks for AD/ADRD and mild cognitive impairment (MCI), by analyzing the past sequential visit records. Amongst individuals 65 and older, our model was able to generate risk predictions for various future timeframes. On the held-out validation set, our model achieved an area under the receiver operating characteristic (AUROC) of 0.772 (95% CI: 0.770, 0.773) for identifying the AD/ADRD/MCI risks in 1 year, and AUROC of 0.735 (95% CI: 0.734, 0.736) in 5 years. The positive predictive values (PPV) in 5 years among individuals with top 1% and 5% highest estimated risks were 39.2% and 27.8%, respectively. These results demonstrate significant improvements upon the current EHR-based AD/ADRD/MCI risk assessment models, paving the way for better prognosis and management of AD/ADRD/MCI at scale.

BACKGROUND:We examined drivers of self and study partner reports of memory loss in mild cognitive impairment (MCI) from Alzheimer (AD-MCI) and vascular disease (Va-MCI). METHODS:We performed retrospective cross-sectional analyses of participants with AD-MCI (n=2874) and Va-MCI (n=376) from the National Alzheimer's Coordinating Center data set. Statistical analysis utilized 2-sided t test or the Fisher exact test. RESULTS:Compared with AD-MCI, Va-MCI subjects (24.5% vs. 19.7%, P=0.031) and study partners (31.4% vs. 21.6%, P<0.0001) were more likely to deny memory loss. Black/African Americans were disproportionately represented in the group denying memory loss in AD-MCI (20.0% vs. 13.2%, P<0.0001) and Va-MCI (33.7% vs. 18.0%, P=0.0022). Study partners of participants with these features also disproportionately denied memory loss: female (AD-MCI: 60.1% vs. 51.7%, P=0.0002; Va-MCI: 70.3% vs. 52.3%, P=0.0011), Black/African American (AD-MCI: 23.5% vs. 11.98%, P<0.0001; Va-MCI: 48.8% vs. 26.5%, P=0.0002), and <16 years of education (AD-MCI only: 33.9% vs. 16.3%, P=0.0262). In AD-MCI and Va-MCI, participants with anxiety were disproportionately represented in the group endorsing memory loss (AD: 28.2% vs. 17.4%, P<0.0001; Va: 31.5% vs. 16.1%, P=0.0071), with analogous results with depression. CONCLUSION/CONCLUSIONS:The findings would suggest extra vigilance in interview-based MCI detection of persons at-risk for self-based or informant-based misreport.

IMPORTANCE/UNASSIGNED:Large language models (LLMs) are crucial for medical tasks. Ensuring their reliability is vital to avoid false results. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR. OBJECTIVE/UNASSIGNED:Evaluate ChatGPT and LlaMA-2 performance in extracting MMSE and CDR scores, including their associated dates. METHODS/UNASSIGNED:Our data consisted of 135,307 clinical notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or MoCA. After applying inclusion criteria 34,465 notes remained, of which 765 underwent ChatGPT (GPT-4) and LlaMA-2, and 22 experts reviewed the responses. ChatGPT successfully extracted MMSE and CDR instances with dates from 742 notes. We used 20 notes for fine-tuning and training the reviewers. The remaining 722 were assigned to reviewers, with 309 each assigned to two reviewers simultaneously. Inter-rater-agreement (Fleiss' Kappa), precision, recall, true/false negative rates, and accuracy were calculated. Our study follows TRIPOD reporting guidelines for model validation. RESULTS/UNASSIGNED:For MMSE information extraction, ChatGPT (vs. LlaMA-2) achieved accuracy of 83% (vs. 66.4%), sensitivity of 89.7% (vs. 69.9%), true-negative rates of 96% (vs 60.0%), and precision of 82.7% (vs 62.2%). For CDR the results were lower overall, with accuracy of 87.1% (vs. 74.5%), sensitivity of 84.3% (vs. 39.7%), true-negative rates of 99.8% (98.4%), and precision of 48.3% (vs. 16.1%). We qualitatively evaluated the MMSE errors of ChatGPT and LlaMA-2 on double-reviewed notes. LlaMA-2 errors included 27 cases of total hallucination, 19 cases of reporting other scores instead of MMSE, 25 missed scores, and 23 cases of reporting only the wrong date. In comparison, ChatGPT's errors included only 3 cases of total hallucination, 17 cases of wrong test reported instead of MMSE, and 19 cases of reporting a wrong date. CONCLUSIONS/UNASSIGNED:In this diagnostic/prognostic study of ChatGPT and LlaMA-2 for extracting cognitive exam dates and scores from clinical notes, ChatGPT exhibited high accuracy, with better performance compared to LlaMA-2. The use of LLMs could benefit dementia research and clinical care, by identifying eligible patients for treatments initialization or clinical trial enrollments. Rigorous evaluation of LLMs is crucial to understanding their capabilities and limitations.

INTRODUCTION/UNASSIGNED:Alzheimer's Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent. METHODS/UNASSIGNED: = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus. RESULTS/UNASSIGNED:SCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD. DISCUSSION/UNASSIGNED:The diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.