Faculty Bibliography

PURPOSE/OBJECTIVE:To develop and evaluate a hybrid large language model (LLM)- and rule-based algorithm for tracking pancreatic cystic lesions (PCLs) across serial radiology reports and apply it to a single-center cohort to characterize cyst growth using first-to-last and consecutive comparisons. METHODS:This retrospective study included all abdominal imaging reports interpreted by abdominal radiologists between 2005 and 2024. A validated LLM identified reports describing PCLs. A hybrid algorithm combining LLM-extracted cyst features (size, location) with rule-based logic matched dominant cysts across serial reports. Two blinded radiologists independently annotated cyst matches in a subset of reports. Agreement between algorithm and radiologists was assessed using percent agreement and Cohen's κ. Discrepancies were adjudicated by a third radiologist for error analysis. Absolute size-based growth was assessed according to American College of Radiology (ACR) criteria, whereas cyst growth rate as a worrisome feature was assessed per Kyoto criterion, using both first-to-last and consecutive studies. Predictors of meeting the Kyoto cyst growth rate criterion were analyzed using multivariable Cox regression. RESULTS:In 58 patients with 418 longitudinal reports, agreement with the adjudicated reference standard was 96%. Cohen's κ was 0.81 (95% CI: 0.66-0.91). The overall cohort included 8,176 patients (61.8% female; mean age 67.6 ± 11.7 years) with 8,389 cysts across 28,489 reports over 40.6 ± 28.5 months (annual growth rate = 0.35 mm/year). ACR absolute growth criteria classified a higher proportion of cysts than the Kyoto cyst growth rate criterion using first-to-last examinations (16.3% vs. 7.4%, p < 0.001), whereas Kyoto cyst growth rate criterion identified a higher proportion using consecutive examinations (21.4% vs. 14%, p < 0.001). Larger baseline cyst size predicted meeting the Kyoto cyst growth rate criterion (HR 1.9-4.0; highest HR 4.0, 95% CI 3.08-5.21; p < 0.001). CONCLUSION/CONCLUSIONS:A hybrid LLM-rule-based algorithm enables reliable automated longitudinal tracking of PCLs across serial radiology reports. When applied at scale, cyst growth classification varied according to the guideline framework and interval comparison method used, and baseline cyst size was the strongest predictor of meeting Kyoto growth rate threshold.

More than 6 million persons living with dementia (PLWD) in the United States rely on the emergency department (ED) for unscheduled care, with up to half discharged home after treatment. The ED-to-home transition poses significant challenges for PLWD and their care partners (referred to as "dyads"), contributing to high rates of ED revisits and adverse outcomes. The Community Paramedic-led Transitions Intervention (CPTI) was developed to address these challenges by adapting the validated Care Transitions Intervention for the ED setting. Delivered by trained community paramedics, CPTI is a short-term 30-day program that includes one home visit and up to three follow-up phone calls. Using a coaching model, paramedic coaches work with members of the dyad to strengthen their knowledge, skills, and confidence to manage their health and successfully navigate the health care system. CPTI is being implemented as part of Emergency Departments LEading the Transformation of Alzheimer's and Dementia Care (ED-LEAD), a cluster-randomized pragmatic trial testing 3 interventions designed to improve outcomes for PLWD discharged home from the ED across 14 health systems and 79 EDs nationwide. This paper describes the CPTI model as implemented within ED-LEAD, detailing its theoretical foundation, structure, training curriculum, workflow integration, and implementation monitoring. This framework can provide a model for health systems, provider groups, and emergency medical service agencies interested in adopting this innovative approach and implementing the CPTI. Insights from its implementation within ED-LEAD will guide future efforts to improve post-ED outcomes and continuity of care for PLWD and their care partners.

Individuals of African ancestry carrying APOL1 (apolipoprotein L1) high-risk genotypes face a markedly increased risk of kidney failure, yet tools to identify those individuals likely to progress to chronic kidney disease are lacking. Here we profiled plasma proteomes of 851 Penn Medicine BioBank participants of African ancestry (285 males and 566 females) with APOL1 high-risk genotypes and preserved estimated glomerular filtration rate (eGFR) (≥60 ml min^-1 1.73 m^-2). Using elastic net Cox regression adjusted for age, sex, eGFR and albuminuria, we derived a nine-protein APOL1 Proteomic Risk Score (APRS) that predicts a composite outcome of ≥40% eGFR decline, kidney failure or death. APRS achieved a time-dependent area under the receiver operating characteristic curve (tAUC) of 86.5%, outperforming the Kidney Failure Risk Equation (66.1%) and polygenic risk scores, with 10-year event rates of 62.5% versus 3.3% across risk quintiles. External validation in Atherosclerosis Risk in Communities and UK Biobank cohorts confirmed robust accuracy (tAUC 82-85%) and consistent performance across demographic and clinical subgroups. Plasma levels of APRS component proteins correlated with kidney tissue fibrosis and tubular injury pathways, indicating strong biological plausibility. By enabling early and accurate prediction of disease progression in APOL1 high-risk individuals, APRS bridges the gap between genetic susceptibility and clinical translation. This scalable and biologically informed approach provides a precision medicine framework for early intervention and may accelerate development of APOL1-targeted therapies to reduce kidney disease disparities.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Plasma biomarkers such as phospho-tau species are increasingly used in clinical practice for the diagnosis of Alzheimer disease (AD). Phosphorylated-tau at threonine 181 (p-tau181) values also provide prognostic information about incident dementia. Cognitive status similarly conveys prognostic information, but the relationship between plasma biomarkers for AD and cognitive status requires clarification. METHODS:Participants from the Atherosclerosis Risk in Communities (ARIC) study who were adjudicated as free of dementia in 2011-2013 had plasma samples analyzed for p-tau181 and other biomarkers. Participants were surveilled for incident dementia through December 31, 2022. Cumulative incidence curves, Cox models, and Fine-Gray models were used to evaluate the independent and combined discriminatory accuracy of cognitive status and plasma biomarkers for incident dementia. RESULTS:The sample comprised 1,577 ARIC participants (age 76.5 years, 60% women, 73% White, 27% Black). The risk of incident dementia was higher in persons with a baseline status of mild cognitive impairment (covariate-adjusted hazard ratio [HR] 2.94, 95% CI 2.61-3.33) compared with those who were cognitively unimpaired independent of biomarker status. The risk of dementia was also higher in persons with more abnormal concentrations of p-tau181 and other biomarkers independent of cognitive status. When age, cognitive status, and p-tau181 were included in the same models, the risk was attenuated relative to models where only cognitive status or plasma biomarkers were included. For continuous p-tau181 concentrations, the covariate-adjusted HR without cognitive status was 1.45 (95% CI 1.36-1.54), but when cognitive status was included, the HR decreased to 1.37 (95% CI 1.29-1.46). Models showed that when combined with age, p-tau181 alone, cognitive status alone, or the combination of p-tau181 and cognitive status had similar discriminatory accuracy. DISCUSSION/CONCLUSIONS:Cognitive status and plasma biomarker concentrations convey independent but overlapping information about the risk of incident dementia. Although cognitive status and plasma p-tau181 have similar discriminatory accuracies, the far lower incidence rate of dementia in persons who are initially cognitively unimpaired highlights the importance of an accurate clinical diagnosis.

BACKGROUND:The current generation of 1.3 billion adolescents (10-19-year-olds), most of whom live in low- and middle-income countries, face large and growing mental health problems. Collective action that could lead to significant improvement in adolescent mental health and well-being (AMH) remains limited. We analyse the factors shaping the global prioritization of AMH for funding and action and reflect on a way forward. METHODS:We triangulate data from interviews with key informants knowledgeable in AMH; focus group discussions with youth representatives who are mental health advocates, some with lived experience of mental ill-health; and document review. We collected the qualitative data from 2021 to 2023, followed by thematic analysis and stakeholder consultations. RESULTS:We identify four themes which shape the global prioritization of AMH. First, prevailing interpersonal and institutional stigma and discrimination directed against adolescents with mental health problems hamper attention to AMH. Second, limited data on the burden of mental health problems and evidence of what works have led to the perception among decision-makers that AMH is an intractable problem. Third, diverse ways of framing AMH are often viewed as a sign of weak alignment rather than as opportunities for coalition-building. Fourth, a wide variety and increasing number of stakeholders are involved in AMH, while the stakeholder landscape remains fragmented, inhibiting coalition-building for AMH. CONCLUSIONS:To overcome the barriers that currently impede the prioritization of AMH, we recommend that (1) stakeholders conduct an adolescent-led consultative process to develop an "umbrella framing", supported by common metrics, (2) advocates use existing global platforms to shape the political priority for AMH, (3) decision-makers, funders and research partners invest in meaningful engagement of adolescents (with lived experience), researchers and implementing partners (4) identify a leadership, governance and accountability structure for a global coalition that could transform AMH and (5) conduct context-specific analyses to inform coalition-building nationally.

Consumer wearable devices are commonly used by patients and consumers for several reasons with increasing application as new technologies are developed. Use of these devices is an emerging issue in Neurology because of increased adoption and the additional data reported to providers by patients. Understanding of possible functions, limitations, and effect on patients of non-US Food and Drug Administration (FDA)-cleared wearable technology to inform neurologic care is needed. A common theme in people with neurologic conditions regarding consumer wearables and associated tracking applications is that there is significant promise in these tools, but adherence (days per use/per week), continued engagement (attrition), and unintended consequences such as heightened anxiety remain important issues. Further understanding and validation of these devices is needed within the field of Neurology before full use and confidence can be achieved. Below, we provide examples of non-FDA-cleared wearable devices used in Neurology in the areas of epilepsy, headache, cardiac monitoring, and sleep.

BACKGROUND:The role of maternal and fetal characteristics in determining kidney size in early childhood remains largely unexplored. This study aims to evaluate the association between birth weight and kidney size in children aged one to six years and explore other children and maternal determinants in a United States cohort. METHODS:We analyzed data from 892 mother-child pairs enrolled in the New York University Children's Health and Environment Study (CHES). Renal sonographic measurements were taken from one to six years of age. Kidney size outcomes included average kidney length, width, depth, total kidney volume (TKV), adjusted kidney length (kidney length/body length), and adjusted TKV (TKV/body surface area). Maternal determinants include age, demographic characteristics, pre-pregnancy BMI, lifestyle, pregnancy complications, and diet during pregnancy. Fetal determinants included sex, birth weight for gestational age z-score, and gestational age at delivery. Anthropometric z change and breastfeeding duration were also considered. Associations were examined using crude and covariate-adjusted linear mixed models. RESULTS:Birth weight z-score and anthropometric z change were observed positively associated with all measures except adjusted kidney length. Female children had smaller average kidney length and TKV, and breastfeeding duration was negatively associated with average kidney depth and TKV. Children of non-Hispanic Black mothers and parous mothers had smaller kidney measures. CONCLUSION/CONCLUSIONS:In NYU CHES, we found that early childhood kidney size measures were consistently influenced by birth weight z-scores and changes in postnatal weight gain z-scores. Additionally, we observed racial differences and the influence of breastfeeding duration on kidney size. TRIAL REGISTRATION/BACKGROUND:Not applicable.

One in four US adults age ≥ 65 have two or more chronic conditions, many of which can be prevented or managed through nutritional interventions. Despite known benefits, nutrition is not prioritized in undergraduate or graduate medical education. We reviewed agendas of three major geriatrics-related continuing medical education (CME) conferences from 2018 to 2025 to understand the extent to which deficits in nutrition training could be addressed via CME. We searched 19 conference agendas for the terms: "nutrition," "diet," "lifestyle," "food," "fat," "carbohydrates," "protein," "vitamin," "mineral," "weight," and "nutrients." Our results showed that nutrition topics were inconsistently offered at geriatrics-related CME conferences, with some conferences offering no nutrition-related talks, and some offering as little as 8 minutes of nutrition-related talks. Few sessions addressed malnutrition or food security. This is the first known review of nutrition education at geriatrics-focused CME conferences. We found insufficient practical nutrition education for providers at CME events to overcome training gaps in medical education. Improved interdisciplinary participation at CME events could increase availability of nutrition education for physicians.

Reliable structural brain measurements are essential for studying neurodegeneration and for designing adequately powered aging and Alzheimer's disease (AD) research. We evaluated the test-retest reliability of FreeSurfer 7.1 morphometric measures in 100 older adults (mean age 73.5 years) ranging from cognitively unimpaired to dementia. Each participant underwent two T1-weighted 3T MRI scans on the same scanner within a short interval (mean 5.5 weeks), minimizing biological change. Segmentation was performed in both standard cross-sectional and longitudinal FreeSurfer modes, focusing on AD-relevant volumes of entorhinal cortex, hippocampus, lateral ventricles, choroid plexus, and the AD cortical thickness signature. Reliability was quantified using absolute and root-mean-square test-retest differences, standard deviation of differences, and intraclass correlation coefficients. Longitudinal processing improved precision by 15-50% across most measures compared with cross-sectional processing, with the largest gain observed for entorhinal thickness. Larger, anatomically well-defined regions (e.g., hippocampus, AD signature) demonstrated higher reliability than small structures or those with complex geometry (e.g., entorhinal cortex, choroid plexus). Image quality, indexed by the Euler characteristic, was the only factor significantly associated with measurement variability; reliability was unrelated to age, sex, cognitive status, inter-scan interval, or amyloid/tau PET burden. Power analyses indicated that detecting a 1% within-individual change requires sample sizes ranging from 36 (AD signature) to >300 (entorhinal cortex). We observed low reliability of choroid plexus volumetry by FreeSurfer 7. These results provide practical benchmarks for expected FreeSurfer measurement variability in older adults. They highlight the advantages of longitudinal processing and rigorous quality control for research on brain aging and AD.