Design and pilot implementation for the BETTER CARE-HF trial: A pragmatic cluster-randomized controlled trial comparing two targeted approaches to ambulatory clinical decision support for cardiologists.

BACKGROUND: Beart failure with reduced ejection fraction (HFrEF) is a leading cause of morbidity and mortality. However, shortfalls in prescribing of proven therapies, particularly mineralocorticoid receptor antagonist (MRA) therapy, account for several thousand preventable deaths per year nationwide. Electronic clinical decision support (CDS) is a potential low-cost and scalable solution to improve prescribing of therapies. However, the optimal timing and format of CDS tools is unknown. METHODS AND RESULTS: We developed two targeted CDS tools to inform cardiologists of gaps in MRA therapy for patients with HFrEF and without contraindication to MRA therapy: (1) an alert that notifies cardiologists at the time of patient visit, and (2) an automated electronic message that allows for review between visits. We designed these tools using an established CDS framework and findings from semistructured interviews with cardiologists. We then pilot tested both CDS tools (n = 596 patients) and further enhanced them based on additional semistructured interviews (n = 11 cardiologists). The message was modified to reduce the number of patients listed, include future visits, and list date of next visit. The alert was modified to improve noticeability, reduce extraneous information on guidelines, and include key information on contraindications. CONCLUSIONS: The BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce CArdiovascular REcommendations for Heart Failure) trial aims to compare the effectiveness of the alert vs. the automated message vs. usual care on the primary outcome of MRA prescribing. To our knowledge, no study has directly compared the efficacy of these two different types of electronic CDS interventions. If effective, our findings can be rapidly disseminated to improve morbidity and mortality for patients with HFrEF, and can also inform the development of future CDS interventions for other disease states. (Trial registration: Clinicaltrials.gov NCT05275920).

Missed opportunities in medical therapy for patients with heart failure in an electronically-identified cohort.

BACKGROUND: National registries reveal significant gaps in medical therapy for patients with heart failure and reduced ejection fraction (HFrEF), but may not accurately (or fully) characterize the population eligible for therapy. OBJECTIVE: We developed an automated, electronic health record-based algorithm to identify HFrEF patients eligible for evidence-based therapy, and extracted treatment data to assess gaps in therapy in a large, diverse health system. METHODS: In this cross-sectional study of all NYU Langone Health outpatients with EF ≤ 40% on echocardiogram and an outpatient visit from 3/1/2019 to 2/29/2020, we assessed prescription of the following therapies: beta-blocker (BB), angiotensin converting enzyme inhibitor (ACE-I)/angiotensin receptor blocker (ARB)/angiotensin receptor neprilysin inhibitor (ARNI), and mineralocorticoid receptor antagonist (MRA). Our algorithm accounted for contraindications such as medication allergy, bradycardia, hypotension, renal dysfunction, and hyperkalemia. RESULTS: We electronically identified 2732 patients meeting inclusion criteria. Among those eligible for each medication class, 84.8% and 79.7% were appropriately prescribed BB and ACE-I/ARB/ARNI, respectively, while only 23.9% and 22.7% were appropriately prescribed MRA and ARNI, respectively. In adjusted models, younger age, cardiology visit and lower EF were associated with increased prescribing of medications. Private insurance and Medicaid were associated with increased prescribing of ARNI (OR = 1.40, 95% CI = 1.02-2.00; and OR = 1.70, 95% CI = 1.07-2.67). CONCLUSIONS: We observed substantial shortfalls in prescribing of MRA and ARNI therapy to ambulatory HFrEF patients. Subspecialty care setting, and Medicaid insurance were associated with higher rates of ARNI prescribing. Further studies are warranted to prospectively evaluate provider- and policy-level interventions to improve prescribing of these evidence-based therapies.

Multimodality imaging: Bird's eye view from the 2019 American College of Cardiology Scientific Sessions.

The 2019 American College of Cardiology Scientific Sessions displayed innovation in many areas for the evaluation and management of cardiovascular disease from preventive evaluation and care to advanced interventions. Imaging played a central role in these developments with a highlight of the conference being the imaging research presented. This review will summarize key imaging studies which were presented at this scientific meeting which will lead to innovation in the evaluation and management of cardiovascular disease. Experts in nuclear imaging (DW/MA), echocardiography (MS), cardiac magnetic resonance (SL), and cardiac computed tomography (RB) selected abstracts which they found to be of particular interest to the multimodality imaging audience and were integrated into this review (LP).

Value of gated-SPECT MPI for ischemia-guided PCI of non-culprit vessels in STEMI patients with multivessel disease after primary PCI.

There remains a clinical question of which patients benefit from revascularization of non-culprit coronary artery stenosis in the setting of acute ST-segment elevation myocardial infraction (STEMI). This is a large population of patients with prior studies showing 40 to 70% of patients with STEMI having non-culprit stenosis. This article reviews the current state of the literature evaluating outcomes of those previously randomized to revascularization of non-culprit stenosis around the time of the STEMI. We propose a new study design to utilize gated-SPECT in the decision process by using an ischemic burden of > 5% as a cut-off for revascularization vs. complete revascularization without ischemia assessment.

Myocardial perfusion imaging in women for the evaluation of stable ischemic heart disease-state-of-the-evidence and clinical recommendations.

This document from the American Society of Nuclear Cardiology represents an updated consensus statement on the evidence base of stress myocardial perfusion imaging (MPI), emphasizing new developments in single-photon emission tomography (SPECT) and positron emission tomography (PET) in the clinical evaluation of women presenting with symptoms of stable ischemic heart disease (SIHD). The clinical evaluation of symptomatic women is challenging due to their varying clinical presentation, clinical risk factor burden, high degree of comorbidity, and increased risk of major ischemic heart disease events. Evidence is substantial that both SPECT and PET MPI effectively risk stratify women with SIHD. The addition of coronary flow reserve (CFR) with PET improves risk detection, including for women with nonobstructive coronary artery disease and coronary microvascular dysfunction. With the advent of PET with computed tomography (CT), multiparametric imaging approaches may enable integration of MPI and CFR with CT visualization of anatomical atherosclerotic plaque to uniquely identify at-risk women. Radiation dose-reduction strategies, including the use of ultra-low-dose protocols involving stress-only imaging, solid-state detector SPECT, and PET, should be uniformly applied whenever possible to all women undergoing MPI. Appropriate candidate selection for stress MPI and for post-MPI indications for guideline-directed medical therapy and/or invasive coronary angiography are discussed in this statement. The critical need for randomized and comparative trial data in female patients is also emphasized.

The elusive role of myocardial perfusion imaging in stable ischemic heart disease: Is ISCHEMIA the answer?

The assessment of ischemia through myocardial perfusion imaging (MPI) is widely accepted as an index step in the diagnostic evaluation of stable ischemic heart disease (SIHD). Numerous observational studies have characterized the prognostic significance of ischemia extent and severity. However, the role of ischemia in directing downstream SIHD care including coronary revascularization has remained elusive as reductions in ischemic burden have not translated to improved clinical outcomes in randomized trials. Importantly, selection bias leading to the inclusion of many low risk patients with minimal ischemia have narrowed the generalizability of prior studies along with other limitations. Accordingly, an ongoing randomized controlled trial entitled ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) will compare an invasive coronary revascularization strategy vs a conservative medical therapy approach among stable patients with moderate to severe ischemia. The results of ISCHEMIA may have a substantial impact on the management of SIHD and better define the role of MPI in current SIHD pathways of care.

Evaluating AI Proficiency in Nuclear Cardiology: Large Language Models take on the Board Preparation Exam.

Background: Previous studies evaluated the ability of large language models (LLMs) in medical disciplines; however, few have focused on image analysis, and none specifically on cardiovascular imaging or nuclear cardiology. Objectives: This study assesses four LLMs - GPT-4, GPT-4 Turbo, GPT-4omni (GPT-4o) (Open AI), and Gemini (Google Inc.) - in responding to questions from the 2023 American Society of Nuclear Cardiology Board Preparation Exam, reflecting the scope of the Certification Board of Nuclear Cardiology (CBNC) examination. Methods: We used 168 questions: 141 text-only and 27 image-based, categorized into four sections mirroring the CBNC exam. Each LLM was presented with the same standardized prompt and applied to each section 30 times to account for stochasticity. Performance over six weeks was assessed for all models except GPT-4o. McNemar's test compared correct response proportions. Results: GPT-4, Gemini, GPT4-Turbo, and GPT-4o correctly answered median percentiles of 56.8% (95% confidence interval 55.4% - 58.0%), 40.5% (39.9% - 42.9%), 60.7% (59.9% - 61.3%) and 63.1% (62.5 - 64.3%) of questions, respectively. GPT4o significantly outperformed other models (p=0.007 vs. GPT-4Turbo, p<0.001 vs. GPT-4 and Gemini). GPT-4o excelled on text-only questions compared to GPT-4, Gemini, and GPT-4 Turbo (p<0.001, p<0.001, and p=0.001), while Gemini performed worse on image-based questions (p<0.001 for all). Conclusion: GPT-4o demonstrated superior performance among the four LLMs, achieving scores likely within or just outside the range required to pass a test akin to the CBNC examination. Although improvements in medical image interpretation are needed, GPT-4o shows potential to support physicians in answering text-based clinical questions.

Impact of Visit Volume on the Effectiveness of Electronic Tools to Improve Heart Failure Care.

BACKGROUND: Electronic health record (EHR) tools can improve prescribing of guideline-recommended therapies for heart failure with reduced ejection fraction (HFrEF), but their effectiveness may vary by physician workload. OBJECTIVES: This paper aims to assess whether physician workload modifies the effectiveness of EHR tools for HFrEF. METHODS: This was a prespecified subgroup analysis of the BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure) cluster-randomized trial, which compared effectiveness of an alert vs message vs usual care on prescribing of mineralocorticoid antagonists (MRAs). The trial included adults with HFrEF seen in cardiology offices who were eligible for and not prescribed MRAs. Visit volume was defined at the cardiologist-level as number of visits per 6-month study period (high = upper tertile vs non-high = remaining). Analysis at the patient-level used likelihood ratio test for interaction with log-binomial models. RESULTS: Among 2,211 patients seen by 174 cardiologists, 932 (42.2%) were seen by high-volume cardiologists (median: 1,853; Q1-Q3: 1,637-2,225 visits/6 mo; and median: 10; Q1-Q3: 9-12 visits/half-day). MRA was prescribed to 5.5% in the high-volume vs 14.8% in the non-high-volume groups in the usual care arm, 10.3% vs 19.6% in the message arm, and 31.2% vs 28.2% in the alert arm, respectively. Visit volume modified treatment effect (P for interaction = 0.02) such that the alert was more effective in the high-volume group (relative risk: 5.16; 95% CI: 2.57-10.4) than the non-high-volume group (relative risk: 1.93; 95% CI: 1.29-2.90). CONCLUSIONS: An EHR-embedded alert increased prescribing by >5-fold among patients seen by high-volume cardiologists. Our findings support use of EHR alerts, especially in busy practice settings. (Building Electronic Tools to Enhance and Reinforce Cardiovascular Recommendations for Heart Failure [BETTER CARE-HF]; NCT05275920).