Faculty Bibliography

OBJECTIVES/OBJECTIVE:Multicenter research of geriatric emergency department (GED) care remains limited. Our objectives were to: 1. Prospectively collect data prioritized by the Geriatric Emergency care Applied Research (GEAR) network, a transdisciplinary taskforce for GED care, and create a multicenter GED research repository of prospective and electronic health record (EHR) data, 2. Assess concordance between prospective and EHR data. METHODS:The GEAR Standardization Study (GEARSS) is a multicenter, prospective study of older emergency department (ED) patients (65+) focusing on the 4Ms of age-friendly care (mobility, medication safety, mentation, what matters) and elder mistreatment. Demographic and clinical data were collected via interviews by trained research assistants (RA) on Days 0, 4, 30, and 90 and linked to EHR. Prevalence of chronic comorbidities and incident delirium were measured and reported using descriptive statistics. Prospective and EHR data concordance was assessed with Cohen's Kappa. RESULTS:999 participants were recruited from 5 EDs (3/25/2021-6/30/2022) across 3 institutions: Grady Health System, Northwestern Memorial Hospital, and Yale New Haven Health. The cohort was 57.0% female, 55.2% White, 39.1% Black, and 3.4% Hispanic, and the mean age was 75.1 years. For rheumatologic disease, peptic ulcer disease, diabetes, renal disease, and cancer, prevalence differed between prospective and EHR data by > 10%. About two-thirds of participants were at risk for falls. Concordance between prospective and EHR data was good for ethnicity (K = 0.73); excellent for sex (K = 1.00), age (K = 1.00), and race (K = 0.98); fair for disposition (K = 0.53); slight for ED observation status (K = 0.33) and dementia diagnosis (K = 0.24); poor for delirium presence (K = 0.07). CONCLUSION/CONCLUSIONS:In GEARSS, demographic variables aligned strongly between prospective and EHR data, while diagnosis, disposition, and mentation factors did not. This multicenter data source provides preliminary findings for common geriatric syndromes and conditions. Choice of measures using these data should be driven by GED research questions.

INTRODUCTION/BACKGROUND:The study aimed to develop and validate the Emergency Department Dementia Algorithm (EDDA) to detect dementia among older adults (65+) and support clinical decision-making in the emergency department (ED). METHODS:In a multisite retrospective study of 759,665 ED visits, electronic health record data from Yale New Haven Health (2014-2022) were used to train three supervised and semi-unsupervised positive-unlabeled machine learning models (XGBoost, Random Forest, LASSO). A separate test set of 400 ED encounters underwent adjudicated chart review for validation. RESULTS:EDDA achieved an area under the receiver-operating characteristic curve (AUROC) of 0.85 in the test set and 0.93 in the validation set. Positive-unlabeled learning improved performance. Agreement between EDDA and clinician-adjudicated dementia diagnoses was moderate (kappa = 0.50), with 17% of EDDA-positive patients having undiagnosed probable dementia. DISCUSSION/CONCLUSIONS:EDDA enhances dementia detection in the ED, with potential for real-time implementation to improve patient outcomes and care transitions. HIGHLIGHTS/CONCLUSIONS:Developed a machine learning algorithm using electronic health record data to detect dementia in the emergency department (ED). Algorithm designed to balance detection accuracy with ease of ED implementation. Parsimonious model with limited but predictive variables selected for rapid ED use. Focused on real-time application, optimizing ED workflows, and clinician support. Aims to enhance ED dementia detection, patient safety, and care coordination.

Alzheimer's disease is the neurodegenerative disorder responsible for approximately 60% to 70% of all cases of dementia and is expected to affect 152 million by 2050. Recently, anti-amyloid therapies have been developed and approved by the Food and Drug Administration as disease-modifying treatments given as infusions every 2 to 5 weeks for Alzheimer's disease. Although this is an important milestone in mitigating Alzheimer's disease progression, it is critical for emergency medicine clinicians to understand what anti-amyloid therapies are and how they work to recognize, treat, and mitigate their adverse effects. Anti-amyloid therapies may be underrecognized contributors to emergency department visits because they carry the risk of adverse effects, namely amyloid-related imaging abnormalities. Amyloid-related imaging abnormalities are observed as abnormalities on magnetic resonance imaging as computed tomography is not sensitive enough to detect the microvasculature abnormalities causing vasogenic edema (amyloid-related imaging abnormalities-E) microhemorrhages and hemosiderin deposits (amyloid-related imaging abnormalities-H). Patients presenting with amyloid-related imaging abnormalities may have nonspecific neurologic symptoms, including headache, lethargy, confusion, and seizures. Anti-amyloid therapies may increase risk of hemorrhagic conversion of ischemic stroke patients receiving thrombolytics and complicate the initiation of anticoagulation. Given the novelty of anti-amyloid therapies and limited real-world data pertaining to amyloid-related imaging abnormalities, it is important for emergency medicine clinicians to be aware of these agents.

A core tenant of the Geriatric Emergency care Applied Research Network 2.0-Advancing Dementia Care (GEAR 2.0-ADC) is the inclusion of community members during all stages of clinical research. As such, we deliberately integrated and supported patient and public involvement in the evaluation and selection of GEAR 2.0-ADC Pilot Research Grants by developing and adapting traditional grant application review structures, with input from community members, to create the GEAR 2.0-ADC Community Review Committee approach. Community members, including persons living with dementia, effectively participated in all three rounds of research grant application review and selection, complementing the traditional scientific review process. The structure and flexibility of the GEAR 2.0-ADC Community Review Committee approach serve as a model for patient and public grant application review involvement with strong potential for applications across grant reviews in other medical specialties.

BACKGROUND:Existing risk scores assessing geriatric vulnerability in the emergency department (ED) have shown limited predictive power, especially in diverse populations. We investigated the relationship of a quick and easy-to-administer geriatric vulnerability scoring system with functional decline and mortality in older patients admitted to multiple hospitals through the ED in the United States (US) and Brazil (BR). METHOD/METHODS:Federated, international, multicenter observational study of hospitalized ED patients aged ≥ 65 from US and BR. The six criteria from the PRO-AGE score (Physical impairment, Recent hospitalization, Older age [≥ 90], Acute mental alteration, Getting thinner, and Exhaustion; 0-8; higher scores = greater vulnerability) were assessed on admission. We used proportional hazards models to investigate the relationships between PRO-AGE score groups and 90-day mortality and functional decline, defined as new dependence in activities of daily living (ADL) and instrumental ADL (IADL), after adjusting for age, sex, race and ethnicity, education, Charlson comorbidity score, and study site. Death was considered a competing event for the functional decline outcome. RESULTS:A total of 1390 patients were included (US = 560; Brazil = 830). The 90-day risk of death was higher for the upper compared with the lower (reference) PRO-AGE group in both cohorts (US: HR = 11.76; 95% confidence interval [CI] = 2.56-54.04; BR: HR = 12.29; 95% CI = 3.54-42.59), whereas the risk of new 90-day ADL disability was higher for upper (HR = 2.08; 95% CI = 1.21-3.56) and middle groups (HR = 2.10; 95% CI = 1.35-3.27) in the US but only the upper group in BR (HR = 1.70; 95% CI = 1.02-2.85). CONCLUSION/CONCLUSIONS:A higher PRO-AGE score was associated with mortality and functional decline in older ED patients admitted to hospitals in the US and BR, demonstrating its generalizability as a geriatric vulnerability risk score.

INTRODUCTION/BACKGROUND:The Geriatric Emergency Care Applied Research Network 2.0-Advancing Dementia Care (GEAR 2.0-ADC) aims to advance research efforts to improve the emergency care of persons living with dementia (PLWDs). OBJECTIVE:To support this objective, GEAR 2.0-ADC convened a virtual consensus conference to prioritize emergency care research opportunities for PLWDs inclusive of perspectives of PLWDs to ensure identification of research gaps in response to their experiences and priorities. Inclusion of PLWDs as research partners is increasingly recognized as a best practice, however, approaches to facilitating consensus participation are lacking. METHODS:Best practices for supporting the engagement of PLWDs in a consensus conference, applied across its three phases (pre-conference, during the conference, and post-conference), include: establishing a learning environment focused on research priorities before the event, presenting information in ways that align with participants' learning preferences while accommodating cognitive impairments, and providing multiple opportunities and methods for gathering post-conference feedback from PLWDs. RESULTS:These strategies were identified by PLWDs and care partners (CPs) through semi-structured interviews, who were involved in the convening process, aimed at exploring ways to enhance facilitation techniques for participants. CONCLUSION/CONCLUSIONS:Additionally, these summarized insights aim to encourage the use of community-engaged approaches in discussions and consensus-building around research priorities in emergency care, particularly for PLWDs and their CPs.

Persons Living with Dementia (PLWD), diagnosed or undiagnosed, have high Emergency Department (ED) use. Identification of such patients poses significant challenges for emergency clinicians with considerable downstream implications on patients, care partners, and healthcare systems. With the advent of Geriatric Emergency Departments (GEDs) there is an opportunity to understand and improve care of PLWDs in EDs with effective allocation of resources and the development of novel techniques to better support detecting those at risk, communicating findings, and coordinating care for such patients. Advances have been made leveraging Electronic Health Record (EHR) data to risk stratify patients for dementia in the hope that those at high-risk may benefit from further evaluation. The promise of multiple blood-base biomarkers (BBM) as a future modality to improve detection of those at risk of dementias, will also have the potential to advance the delivery of care of PLWD and their care partners in EDs. HIGHLIGHTS: EDs have an integral role in delivering care for Person Living with Dementia and their care partners. High acuity and fast paced ED environment and other barriers makes it difficult to identify Person Living with Dementia. EHR-based risk stratification algorithms can identify patients at risk for Dementia in ED and outpatient settings. Use of Blood-Based Biomarkers in the ED setting is novel and considerations of its use and implications need to be studied. EHR based risk stratification algorithm and Blood Based Biomarkers when used judiciously have the potential to overcome some of the known barriers to identify and improve care for Person Living with Dementia as they transition through EDs.

INTRODUCTION/BACKGROUND:Cognitive impairment (CI) is under-recognized by emergency department (ED) clinicians, and processes for cognitive screening and outpatient referrals are limited. METHODS:This pilot study tested the feasibility of ED clinicians referring older adult patients identified through CI screening and direct clinician referral for outpatient cognitive evaluation. Telephone interviews and chart reviews were conducted on 100 patients about their emergency care, cognitive function, and referral status. RESULTS:A total of 9359 ED patients were screened for memory and thinking problems, with 650 (6.9%) reporting such issues. A total of 100 patients were discharged and referred for outpatient cognitive evaluation, consisting of 37 referred from screening and 67 through direct clinician referral. Of these, 26 (26.0%) scheduled and 19 (19.0%) completed outpatient evaluations within 100 days. Fifteen (78.9%) were formally diagnosed with dementia, CI, or memory loss. DISCUSSION/CONCLUSIONS:ED clinicians are able to identify and appropriately refer older patients with CI for outpatient evaluation. Future studies can improve referral rates with solutions addressing detection and follow-up challenges. HIGHLIGHTS/CONCLUSIONS:Screening for cognitive impairment and outpatient referral for cognitive evaluation is feasible in the emergency department. Nearly 80% of patients who completed follow-up were diagnosed with cognitive impairment, including probable dementia and Alzheimer's disease. Significant gaps and barriers remain in maintaining outpatient follow-up from initial referral from the emergency department, with less than one in five patients completing outpatient evaluations.