Faculty Bibliography

OBJECTIVE:This study aimed to explore the prognostic impact of cognitive impairment on the long-term risk of major adverse cardiovascular events (MACEs) in older patients with non-ST-elevation acute coronary syndrome (NSTEACS) undergoing invasive treatment. METHODS:Patients aged ≥75 years with NSTEACS undergoing an invasive strategy were included in the multicentre prospective study (NCT01933581). Montreal Cognitive Assessment was used to evaluate cognitive status at baseline (scores ≥26 classified as normal, <26 as cognitive impairment). Long-term follow-up data were obtained from electronic patient care records. The primary endpoint was MACE as a composite of all-cause deaths, reinfarction, stroke/transient ischaemic attack, urgent revascularisation and significant bleeding. RESULTS:239 patients with baseline cognitive assessment completed long-term follow-up. Median age was 80.9 years (IQR 78.2-83.9 years) and 62.3% were male. On 5-year follow-up, there was no significant difference in the occurrence of MACE between the cognitively impaired group and the normal cognition group (p=0.155). Cognition status was not associated with MACE (HR 1.37 (95% CI 0.96 to 1.95); p=0.082). However, there was significantly more deaths (p=0.005) in those with cognitive impairment. Kaplan-Meier survival analysis (log-rank p=0.003) and Cox regression analysis (aHR 1.85 (95% CI 1.11 to 3.08); p=0.018) revealed increased risk of all-cause mortality, even after adjusting for frailty and GRACE (Global Registry of Acute Coronary Events) score. CONCLUSION/CONCLUSIONS:Cognitive impairment in older patients with NSTEACS undergoing an invasive strategy was associated with long-term all-cause mortality. Routine cognitive screening may aid risk stratification and further studies are needed to identify how this should influence management strategies and individual decision-making in this patient group. TRIAL REGISTRATION NUMBER/BACKGROUND:NCT01933581.

BACKGROUND/UNASSIGNED:Frailty is associated with adverse cardiovascular outcomes independent of age and comorbidities, yet the independent influence of frailty progression remains uncertain. METHODS/UNASSIGNED:Medicare Fee-for-service beneficiaries ≥ 65 years at cohort inception with continuous enrollment from 2003-2015 were included. Frailty trajectory was measured by annualized change in a validated claims-based frailty index (CFI) over a 5-year period. Linear mixed effects models, adjusting for baseline frailty, were used to estimate CFI change over a 5-year period. Survival analysis was used to evaluate associations of frailty progression and future health outcomes (major adverse cardiovascular and cerebrovascular events [MACCE], all-cause death, heart failure, myocardial infarction, ischemic stroke, and days alive at home [DAH] within the following calendar year). RESULTS/UNASSIGNED:26.4 million unique beneficiaries were included (mean age 75.4 ± 7.0 years, 57% female, 13% non-White). In total, 20% had frailty progression, 66% had no change in frailty, and 14% frailty regression over median follow-up of 2.4 years. Compared to those without a change in CFI, when adjusting for baseline frailty, those with frailty progression had significantly greater risk of incident MACCE (hazard ratio [HR] 2.30, 95% confidence interval [CI] 2.30-2.31), all-cause mortality (HR 1.59, 95% CI 1.58-1.59), acute myocardial infarction (HR 1.78, 95% CI 1.77-1.79), heart failure (HR 2.78, 95% CI 2.77-2.79), and stroke (HR 1.78, 95% CI 1.77-1.79). There was also a graded increase in risk of each outcome with more rapid progression and significantly fewer DAH with the most rapid vs. the slowest progression group (270.4 ± 112.3 vs. 308.6 ± 93.0 days, rate ratio 0.88, 95% CI 0.87-0.88, p < 0.001). CONCLUSIONS/UNASSIGNED:In this large, nationwide sample of Medicare beneficiaries, frailty progression, independent of baseline frailty, was associated with fewer DAH and a graded risk of MACCE, all-cause mortality, myocardial infarction, heart failure, and stroke compared to those without progression.

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.

PURPOSE/OBJECTIVE:Clinic-based or community-based interventions can improve adherence to guideline-directed medication therapies (GDMTs) among patients with heart failure (HF). However, opportunities for such interventions are frequently missed, as providers may be unable to recognise risk patterns for medication non-adherence. Machine learning algorithms can help in identifying patients with high likelihood of non-adherence. While a number of multilevel factors influence adherence, prior models predicting non-adherence have been limited by data availability. We have established an electronic health record (EHR)-based cohort with comprehensive data elements from multiple sources to improve on existing models. We linked EHR data with pharmacy refill data for real-time incorporation of prescription fills and with social determinants data to incorporate neighbourhood factors. PARTICIPANTS/METHODS:Patients seen at a large health system in New York City (NYC), who were >18 years old with diagnosis of HF or reduced ejection fraction (<40%) since 2017, had at least one clinical encounter between 1 April 2021 and 31 October 2022 and active prescriptions for any of the four GDMTs (beta-blocker, ACEi/angiotensin receptor blocker (ARB)/angiotensin receptor neprilysin inhibitor (ARNI), mineralocorticoid receptor antagonist (MRA) and sodium-glucose cotransporter 2 inhibitor (SGLT2i)) during the study period. Patients with non-geocodable address or outside the continental USA were excluded. FINDINGS TO DATE/RESULTS:Among 39 963 patients in the cohort, the average age was 73±14 years old, 44% were female and 48% were current/former smokers. The common comorbid conditions were hypertension (77%), cardiac arrhythmias (56%), obesity (33%) and valvular disease (33%). During the study period, 33 606 (84%) patients had an active prescription of beta blocker, 32 626 (82%) had ACEi/ARB/ARNI, 11 611 (29%) MRA and 7472 (19%) SGLT2i. Ninety-nine per cent were from urban metropolitan areas. FUTURE PLANS/UNASSIGNED:We will use the established cohort to develop a machine learning model to predict medication adherence, and to support ancillary studies assessing associates of adherence. For external validation, we will include data from an additional hospital system in NYC.

IntroductionOlder adults with IBD are at higher risk for postoperative complications as compared to their younger counterparts, however factors contributing to this are unknown. We assessed risk factors associated with adverse IBD-related surgical outcomes, evaluated trends in emergency surgery, and explored differential risks by age.MethodsUsing the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database, we identified adults ≥18 years of age who underwent an IBD-related intestinal resection from 2005-2019. Our primary outcome included a 30-day composite of mortality, readmission, reoperation, and/or major postoperative complication.ResultsOverall, 49,746 intestinal resections were performed with 9,390 (18.8%) occurring among older adults with IBD. Nearly 37% of older adults experienced an adverse outcome as compared to 28.1% among younger adults with IBD (p<0.01). Among all adults with IBD, the presence of preoperative sepsis (aOR, 2.08; 95%CI 1.94-2.24), malnutrition (aOR, 1.22; 95%CI 1.14-1.31), dependent functional status (aOR, 6.92; 95%CI 4.36-11.57), and requiring emergency surgery (aOR, 1.50; 95%CI 1.38-1.64) increased the odds of an adverse postoperative outcome, with similar results observed when stratifying by age. Further, 8.8% of surgeries among older adults were emergent, with no change observed over time (p=0.16).DiscussionPreoperative factors contributing to the risk of an adverse surgical outcome are similar between younger and older individuals with IBD, and include elements such as malnutrition and functional status. Incorporating these measures into surgical decision-making can reduce surgical delays in older individuals at low-risk and help target interventions in those at high risk, transforming care for thousands of older adults with IBD.

IMPORTANCE/UNASSIGNED:Medication nonadherence is common among patients with heart failure with reduced ejection fraction (HFrEF) and can lead to increased hospitalization and mortality. Patients living in socioeconomically disadvantaged areas may be at greater risk for medication nonadherence due to barriers such as lower access to transportation or pharmacies. OBJECTIVE/UNASSIGNED:To examine the association between neighborhood-level socioeconomic status (nSES) and medication nonadherence among patients with HFrEF and to assess the mediating roles of access to transportation, walkability, and pharmacy density. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This retrospective cohort study was conducted between June 30, 2020, and December 31, 2021, at a large health system based primarily in New York City and surrounding areas. Adult patients with a diagnosis of HF, reduced EF on echocardiogram, and a prescription of at least 1 guideline-directed medical therapy (GDMT) for HFrEF were included. EXPOSURE/UNASSIGNED:Patient addresses were geocoded, and nSES was calculated using the Agency for Healthcare Research and Quality SES index, which combines census-tract level measures of poverty, rent burden, unemployment, crowding, home value, and education, with higher values indicating higher nSES. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Medication nonadherence was obtained through linkage of health record prescription data with pharmacy fill data and was defined as proportion of days covered (PDC) of less than 80% over 6 months, averaged across GDMT medications. RESULTS/UNASSIGNED:Among 6247 patients, the mean (SD) age was 73 (14) years, and majority were male (4340 [69.5%]). There were 1011 (16.2%) Black participants, 735 (11.8%) Hispanic/Latinx participants, and 3929 (62.9%) White participants. Patients in lower nSES areas had higher rates of nonadherence, ranging from 51.7% in the lowest quartile (731 of 1086 participants) to 40.0% in the highest quartile (563 of 1086 participants) (P < .001). In adjusted analysis, patients living in the lower 2 nSES quartiles had significantly higher odds of nonadherence when compared with patients living in the highest nSES quartile (quartile 1: odds ratio [OR], 1.57 [95% CI, 1.35-1.83]; quartile 2: OR, 1.35 [95% CI, 1.16-1.56]). No mediation by access to transportation and pharmacy density was found, but a small amount of mediation by neighborhood walkability was observed. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this retrospective cohort study of patients with HFrEF, living in a lower nSES area was associated with higher rates of GDMT nonadherence. These findings highlight the importance of considering neighborhood-level disparities when developing approaches to improve medication adherence.

Enhancing access to care using telehealth is a priority for improving outcomes among older adults with heart failure, increasing quality of care, and decreasing costs. Telehealth has the potential to increase access to care for patients who live in underresourced geographic regions, have physical disabilities or poor access to transportation, and may not otherwise have access to cardiologists with expertise in heart failure. During the COVID-19 pandemic, access to telehealth expanded, and yet barriers to access, including broadband inequality, low digital literacy, and structural barriers, prevented many of the disadvantaged patients from getting equitable access. Using a health equity lens, this scientific statement reviews the literature on telehealth for older adults with heart failure; provides an overview of structural, organizational, and personal barriers to telehealth; and presents novel interventions that pair telemedicine with in-person services to mitigate existing barriers and structural inequities.

BACKGROUND:Although studies to date have broadly shown that cardiovascular disease (CVD) increases cognitive and physical impairment risk, there is still limited understanding of the magnitude of this risk among relevant CVD subtypes or age cohorts. METHODS:We analyzed longitudinal data from 16 679 U.S. Health and Retirement Study participants who were aged ≥65 years at study entry. Primary endpoints were physical impairment (activities of daily living impairment) or cognitive impairment (Langa-Weir Classification of dementia). We compared these endpoints among participants who developed incident CVD versus those who were CVD free, both in the short term (<2-year postdiagnosis) and long term (>5 years), controlling for sociodemographic and health characteristics. We then analyzed the effects by CVD subtype (atrial fibrillation, congestive heart failure, ischemic heart disease, and stroke) and age-at-diagnosis (65-74, 75-84, and ≥85). RESULTS:Over a median follow-up of 10 years, 8 750 participants (52%) developed incident CVD. Incident CVD was associated with significantly higher adjusted odds (aOR) of short-term and long-term physical and cognitive impairment. The oldest (≥85) age-at-diagnosis subgroup had the highest risk of short-term physical (aOR 3.01, 95% confidence interval [CI]: 2.40-3.77) and cognitive impairment (aOR 1.96, 95% CI: 1.55-2.48), as well as long-term impairment. All CVD subtypes were associated with higher odds of physical and cognitive impairment, with the highest risk for patients with incident stroke. CONCLUSIONS:Incident CVD was associated with an increased risk of physical and cognitive impairment across CVD subtypes. Impairment risk after CVD was highest among the oldest patients (≥85 years) who should therefore remain a target for prevention efforts.

BACKGROUND:Whether initial invasive management in older vs younger adults with chronic coronary disease and moderate or severe ischemia improves health status or clinical outcomes is unknown. OBJECTIVES/OBJECTIVE:The goal of this study was to examine the impact of age on health status and clinical outcomes with invasive vs conservative management in the ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) trial. METHODS:One-year angina-specific health status was assessed with the 7-item Seattle Angina Questionnaire (SAQ) (score range 0-100; higher scores indicate better health status). Cox proportional hazards models estimated the treatment effect of invasive vs conservative management as a function of age on the composite clinical outcome of cardiovascular death, myocardial infarction, or hospitalization for resuscitated cardiac arrest, unstable angina, or heart failure. RESULTS: = 0.29). CONCLUSIONS:Older patients with chronic coronary disease and moderate or severe ischemia had consistent improvement in angina frequency but less improvement in angina-related health status with invasive management compared with younger patients. Invasive management was not associated with improved clinical outcomes in older or younger patients. (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches [ISCHEMIA]; NCT01471522).

BACKGROUND:Health status is increasingly recognized as an important patient-centered outcome after acute myocardial infarction (AMI). Yet drivers of decline in health status after AMI remain largely unknown in older adults. We sought to develop and validate a predictive risk model for health status decline among older adult survivors of AMI. METHODS:Using data from a prospective cohort study conducted from 2013 to 2017 of 3041 patients age ≥75 years hospitalized with acute myocardial infarction at 94 U.S. hospitals, we examined a broad array of demographic, clinical, functional, and psychosocial variables for their association with health status decline, defined as a decrease of ≥5 points in the Short Form-12 (SF-12) physical component score from hospitalization to 6 months post-discharge. Model selection was performed in logistic regression models of 20 imputed datasets to yield a parsimonious risk prediction model. Model discrimination and calibration were evaluated using c-statistics and calibration plots, respectively. RESULTS:Of the 2571 participants included in the main analyses, 30% of patients experienced health status decline from hospitalization to 6 months post-discharge. The risk model contained 14 factors, 10 associated with higher risk of health status decline (age, pre-existing AMI, pre-existing cancer, pre-existing COPD, pre-existing diabetes, history of falls, presenting Killip class, acute kidney injury, baseline health status, and mobility impairment) and four associated with lower risk of health status decline (male sex, higher hemoglobin, receipt of revascularization, and arrhythmia during hospitalization). The model displayed good discrimination (c-statistic = 0.74 in validation cohort) and calibration (p > 0.05) in both development and validation cohorts. CONCLUSIONS:We used split sampling to develop and validate a risk model for health status decline in older adults after hospitalization for AMI and identified several risk factors that may be modifiable to mitigate the threat of this important patient-centered outcome. External validation of this risk model is warranted.