Outcomes with guideline-directed medical therapy and cardiac implantable electronic device therapies for patients with heart failure with reduced ejection fraction.

Background: Limited real-world evidence exists for outcomes with contemporary guideline-directed medical therapy (GDMT) or GDMT with implantable cardioverter-defibrillator (ICD)/cardiac resynchronization therapy defibrillator (CRT-D) therapy for patients with heart failure with reduced ejection fraction (HFrEF) and left ventricular ejection fraction (LVEF) ≤35%. Objective: The present study aimed to assess survival associated with GDMT or GDMT with ICD/CRT-D therapy. Methods: This retrospective observational study included real-world de-identified data from January 1, 2016, to December 19, 2023, from 24 U.S. institutions per participating institutional agreements (egnite Database; egnite, Inc.). Patients with a diagnosis of HFrEF and an echocardiographic study documenting LVEF ≤35% were included for analysis. Results: Of 43,591 patients with eligible index event of LVEF ≤35%, prescription history through ≥1 year preindex, and no ICD/CRT-D therapy preindex, mean ± standard deviation age at index was 71.2 ± 13.2 years; 14,805 (34.0%) patients were female. At 24 months, an estimated 99.1% (95% confidence interval [CI] 99.0%-99.2%), 89.9% (95% CI 89.7%-90.1%), 54.8% (95% CI 54.4%-55.2%), and 17.2% (95% CI 16.9%-17.5%), had ≥1, 2, 3, or all 4 GDMT classes prescribed, respectively; an estimated 15.7% (95% CI 15.3%-16.1%) had device placement. Of those without a device, by 24 months, an estimated 45.1% (95% CI 44.4%-45.7%) had a documented LVEF >35%. Counts of GDMT classes prescribed as well as ICD/CRT-D device therapy were associated with lower mortality risk in this population, even after adjustment for patient age, sex, and comorbidities. Conclusion: Both GDMT classes prescribed and device therapy were independently associated with lower mortality risk, even in the presence of more GDMT options for this more contemporary population.

Almanac - Retrieval-Augmented Language Models for Clinical Medicine.

BACKGROUND: Large language models (LLMs) have recently shown impressive zero-shot capabilities, whereby they can use auxiliary data, without the availability of task-specific training examples, to complete a variety of natural language tasks, such as summarization, dialogue generation, and question answering. However, despite many promising applications of LLMs in clinical medicine, adoption of these models has been limited by their tendency to generate incorrect and sometimes even harmful statements. METHODS: We tasked a panel of eight board-certified clinicians and two health care practitioners with evaluating Almanac, an LLM framework augmented with retrieval capabilities from curated medical resources for medical guideline and treatment recommendations. The panel compared responses from Almanac and standard LLMs (ChatGPT-4, Bing, and Bard) versus a novel data set of 314 clinical questions spanning nine medical specialties. RESULTS: Almanac showed a significant improvement in performance compared with the standard LLMs across axes of factuality, completeness, user preference, and adversarial safety. CONCLUSIONS: Our results show the potential for LLMs with access to domain-specific corpora to be effective in clinical decision-making. The findings also underscore the importance of carefully testing LLMs before deployment to mitigate their shortcomings. (Funded by the National Institutes of Health, National Heart, Lung, and Blood Institute.).

Almanac: Retrieval-Augmented Language Models for Clinical Medicine.

Large-language models have recently demonstrated impressive zero-shot capabilities in a variety of natural language tasks such as summarization, dialogue generation, and question-answering. Despite many promising applications in clinical medicine, adoption of these models in real-world settings has been largely limited by their tendency to generate incorrect and sometimes even toxic statements. In this study, we develop Almanac, a large language model framework augmented with retrieval capabilities for medical guideline and treatment recommendations. Performance on a novel dataset of clinical scenarios (n= 130) evaluated by a panel of 5 board-certified and resident physicians demonstrates significant increases in factuality (mean of 18% at p-value < 0.05) across all specialties, with improvements in completeness and safety. Our results demonstrate the potential for large language models to be effective tools in the clinical decision-making process, while also emphasizing the importance of careful testing and deployment to mitigate their shortcomings.

Implications of Extra-cardiac Disease in Patient Selection for Heart Transplantation: Considerations in Cardiac Amyloidosis.

Disease-modifying therapies in both light chain and transthyretin amyloidosis have improved patient functional status and survival. Conceivably, as heart failure may progress despite amyloid therapies, more patients may be considered for heart transplantation. In earlier eras, extra-cardiac amyloid deposits significantly reduced post-heart transplant patient survival and functional status compared to the non-amyloid population. In the modern era, transplant centres have reported improved outcomes in amyloidosis as patient selection has grown more stringent. Importantly, systematic candidate evaluation should assess the degree of extra-cardiac involvement, the effectiveness of disease-modifying therapies and downstream effects on patients' nutrition and frailty. This review outlines such an overall approach while also considering that organ-specific selection criteria may vary between individual transplant centres. A methodical approach to patient evaluation will promote better understanding of the prevalence and severity of extra-cardiac disease in amyloidosis patients referred for heart transplantation and of any disparities in decision outcomes in this population.

Nurturing Diverse Generations of the Medical Workforce for Success With Authenticity: An Association of Black Cardiologists' Roundtable.

The COVID-19 pandemic exposed the consequences of systemic racism in the United States with Black, Hispanic, and other racial and ethnic diverse populations dying at disproportionately higher rates than White Americans. Addressing the social and health disparities amplified by COVID-19 requires in part restructuring of the healthcare system, particularly the diversity of the healthcare workforce to better reflect that of the US population. In January 2021, the Association of Black Cardiologists hosted a virtual roundtable designed to discuss key issues pertaining to medical workforce diversity and to identify strategies aimed at improving racial and ethnic diversity in medical school, graduate medical education, faculty, and leadership positions. The Nurturing Diverse Generations of the Medical Workforce for Success with Authenticity roundtable brought together diverse stakeholders and champions of diversity and inclusion to discuss innovative ideas, solutions, and opportunities to address workforce diversification.

Development of low-cost edible coatings based on polysaccharides with active lactic acid bacteria for the protection of fresh produce modeled using fresh cut apples.

The loss of fresh produce along the supply chain represents a significant contributor to environmental and economic burden. Although technological advances in distribution and storage have provided a means to reduce the loss of fresh produce, in resource-limited settings, these technologies may not be available. One attractive approach to help address this limitation is to use edible coatings to protect fresh produce from biotic and abiotic factors that cause food deterioration. Here, we developed edible coatings from materials that are cheap and easy to prepare: maize starch, κ-carrageenan, and agar as the matrix; glycerol as the plasticizer; and Lactobacillus plantarum TPB21.12 as the active ingredient. Using fresh cut apples as a model substrate, we found that maize starch coating retained color, agar coating delayed browning, and κ-carrageenan coating decreased mass shrinkage of the fresh cut apples. L. plantarum TPB21.12 remained viable in the edible coating suspensions during storage and was active against Escherichia coli TPB21.8, a model bacterium for biotic factor that causes food spoilage. The simplicity of the edible coating formulation and preparation method offers an attractive approach for applications to help protect fresh produce from deterioration and reduce food loss and waste generation.

Effects of Body Mass Index on Presentation and Outcomes of COVID-19 among Heart Transplant and Left Ventricular Assist Device Patients: A Multi-Institutional Study.

The coronavirus disease 2019 (COVID-19) pandemic continues to pose a significant threat to patients receiving advanced heart failure therapies. The current study was undertaken to better understand the relationship between obesity and outcomes of SARS-CoV-2 infection in patients with a left ventricular assist device (LVAD) or heart transplant. We performed a retrospective review of patients with a heart transplant or LVAD who presented to one of the participating 11 institutions between April 1 and November 30, 2020. Patients were grouped by body mass index (BMI) into obese (BMI ≥ 30 k/m2) and nonobese cohorts (BMI < 30 kg/m2). Multivariable logistic regression models were used to estimate effects of obesity on outcomes of interest. Across all centers, 162 heart transplant and 81 LVAD patients were identified; 54 (33%) and 38 (47%) were obese, respectively. Obese patients tended to have more symptoms at presentation. No differences in rates of hospitalization or ICU admission were noted. Obese patients with LVADs were more likely to require mechanical ventilation (39% vs. 8%, p < 0.05). No differences in renal failure or secondary infection were noted. Mortality was similar among heart transplant patients (11% [obese] vs. 16% [nonobese], p = 0.628) and LVAD patients (12% vs. 15%, p = 1.0). BMI was not associated with increased adjusted odds of mortality, ICU admission, or mechanical ventilation (all p > 0.10). In summary, acute presentations of SARS-CoV-2 among heart transplant and LVAD recipients carry a significantly higher mortality than the general population, although BMI does not appear to impact this. Further studies on the longer-term effects of COVID-19 on this population are warranted.

Prevalence, mutational spectrum and clinical implications of clonal hematopoiesis of indeterminate potential in plasma cell dyscrasias.

Clonal hematopoiesis of indeterminate potential (CHIP) is common both in healthy individuals and patients with hematological cancers. Recent studies have showed worse prognosis for patients with multiple myeloma (MM) and non-Hodgkin lymphoma undergoing stem cell transplant, that have concomitant presence of CHIP. Data regarding the clinical and biological role of CHIP in plasma cell dyscrasias (PCDs) is rapidly increasing. However, the prevalence and prognostic implication of CHIP in patients with MM outside of the transplant setting, and in those with other more indolent PCDs remains elusive. Here we explored the prevalence and clinical implications of CHIP detected through next-generation sequencing in 209 patients with PCDs including MM, light chain (AL) amyloidosis (ALA), monoclonal gammopathy of undetermined significance (MGUS), and smoldering multiple myeloma (SMM). To avoid attributing the mutations to the plasma cell clone, CHIP was defined as the presence of DNMT3A, TET2, or ASXL1 mutations in the peripheral blood or bone marrow (DTA-CH). The prevalence of DTA-CH was 19% in patients with PCDs, with no difference between each PCD. TET2 (23%) and DNMT3A (22%), were the most frequently mutated genes. DTA-CH correlated with older age in MM (P = .001) and MGUS/SMM (P = 0.0007), as well as with coronary artery disease or congestive heart failure in MM (P = .03). DTA-CH did not predict worse OS or PFS in either MM or ALA, nor it predict higher risk of progression to MM in patients with MGUS/SMM. Our results overall further elucidate the prevalence and mutational spectrum of CHIP in PCDs, providing more information regarding the clinical relevance of CHIP in this patient population.

High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning.

IMPORTANCE: Early detection and characterization of increased left ventricular (LV) wall thickness can markedly impact patient care but is limited by under-recognition of hypertrophy, measurement error and variability, and difficulty differentiating causes of increased wall thickness, such as hypertrophy, cardiomyopathy, and cardiac amyloidosis. OBJECTIVE: To assess the accuracy of a deep learning workflow in quantifying ventricular hypertrophy and predicting the cause of increased LV wall thickness. DESIGN, SETTINGS, AND PARTICIPANTS: This cohort study included physician-curated cohorts from the Stanford Amyloid Center and Cedars-Sinai Medical Center (CSMC) Advanced Heart Disease Clinic for cardiac amyloidosis and the Stanford Center for Inherited Cardiovascular Disease and the CSMC Hypertrophic Cardiomyopathy Clinic for hypertrophic cardiomyopathy from January 1, 2008, to December 31, 2020. The deep learning algorithm was trained and tested on retrospectively obtained independent echocardiogram videos from Stanford Healthcare, CSMC, and the Unity Imaging Collaborative. MAIN OUTCOMES AND MEASURES: The main outcome was the accuracy of the deep learning algorithm in measuring left ventricular dimensions and identifying patients with increased LV wall thickness diagnosed with hypertrophic cardiomyopathy and cardiac amyloidosis. RESULTS: The study included 23 745 patients: 12 001 from Stanford Health Care (6509 [54.2%] female; mean [SD] age, 61.6 [17.4] years) and 1309 from CSMC (808 [61.7%] female; mean [SD] age, 62.8 [17.2] years) with parasternal long-axis videos and 8084 from Stanford Health Care (4201 [54.0%] female; mean [SD] age, 69.1 [16.8] years) and 2351 from CSMS (6509 [54.2%] female; mean [SD] age, 69.6 [14.7] years) with apical 4-chamber videos. The deep learning algorithm accurately measured intraventricular wall thickness (mean absolute error [MAE], 1.2 mm; 95% CI, 1.1-1.3 mm), LV diameter (MAE, 2.4 mm; 95% CI, 2.2-2.6 mm), and posterior wall thickness (MAE, 1.4 mm; 95% CI, 1.2-1.5 mm) and classified cardiac amyloidosis (area under the curve [AUC], 0.83) and hypertrophic cardiomyopathy (AUC, 0.98) separately from other causes of LV hypertrophy. In external data sets from independent domestic and international health care systems, the deep learning algorithm accurately quantified ventricular parameters (domestic: R2, 0.96; international: R2, 0.90). For the domestic data set, the MAE was 1.7 mm (95% CI, 1.6-1.8 mm) for intraventricular septum thickness, 3.8 mm (95% CI, 3.5-4.0 mm) for LV internal dimension, and 1.8 mm (95% CI, 1.7-2.0 mm) for LV posterior wall thickness. For the international data set, the MAE was 1.7 mm (95% CI, 1.5-2.0 mm) for intraventricular septum thickness, 2.9 mm (95% CI, 2.4-3.3 mm) for LV internal dimension, and 2.3 mm (95% CI, 1.9-2.7 mm) for LV posterior wall thickness. The deep learning algorithm accurately detected cardiac amyloidosis (AUC, 0.79) and hypertrophic cardiomyopathy (AUC, 0.89) in the domestic external validation site. CONCLUSIONS AND RELEVANCE: In this cohort study, the deep learning model accurately identified subtle changes in LV wall geometric measurements and the causes of hypertrophy. Unlike with human experts, the deep learning workflow is fully automated, allowing for reproducible, precise measurements, and may provide a foundation for precision diagnosis of cardiac hypertrophy.

Challenges and the innovations in the care of advanced heart failure patients during COVID-19.

The COVID-19 pandemic underscored our healthcare system's unpreparedness to manage an unprecedented pandemic. Heart failure (HF) physicians from 14 different academic and private practice centers share their systems' challenges and innovations to care for patients with HF, heart transplantation, and patients on LVAD support during the COVID-19 pandemic. We discuss measures implemented to alleviate the fear in seeking care, ensure continued optimization of guideline directed medical therapy (GDMT), manage the heart transplant waiting list, continue essential outpatient monitoring of anticoagulation in LVAD patients and surveillance testing post-heart transplant, and prevent physician burnout. This collaborative work can build a foundation for better preparation in the face of future challenges.

A phylogenomic perspective on the evolutionary history of the stonefly genus Suwallia (Plecoptera: Chloroperlidae) revealed by ultraconserved genomic elements.

Evolutionary biologists have long sought to disentangle phylogenetic relationships among taxa spanning the tree of life, an increasingly important task as anthropogenic influences accelerate population declines and species extinctions, particularly in insects. Phylogenetic analyses are commonly used to identify unique evolutionary lineages, to clarify taxonomic designations of the focal taxa, and to inform conservation decisions. Advances in DNA sequencing techniques have increasingly facilitated the ability of researchers to apply genomic methods to phylogenetic analyses, even for non-model organisms. Stoneflies are non-model insects that are important bioindicators of the quality of freshwater habitats and landscape disturbance as they spend the immature stages of their life cycles in fresh water, and the adult stages in terrestrial environments. Phylogenetic relationships within the stonefly genus Suwallia (Insecta: Plecoptera: Chloroperlidae) are poorly understood, and have never been assessed using molecular data. We used DNA sequence data from genome-wide ultraconserved element loci to generate the first molecular phylogeny for the group and assess its monophyly. We found that Palearctic and Nearctic Suwallia do not form reciprocally monophyletic clades, and that a biogeographic history including dispersal, vicariance, and founder event speciation via jump dispersal best explains the geographic distribution of this group. Our results also strongly suggest that Neaviperla forcipata (Neave, 1929) is nested within Suwallia, and the concept of the genus Suwallia should be revised to include it. Thus, we formally propose a new taxonomic combination wherein Neaviperla forcipata (Neave, 1929) is reclassified as Suwallia forcipata (Neave, 1929). Moreover, some Suwallia species (e.g., S. amoenacolens, S. kerzhneri, S. marginata, S. pallidula, and S. starki) exhibit pronounced cryptic diversity that is worthy of further investigation. These findings provide a first glimpse into the evolutionary history of Suwallia, improve our understanding of stonefly diversity in the tribe Suwallini, and highlight areas where additional research is needed.

Electrocardiogram Characteristics and Prognostic Value in Light-Chain Amyloidosis: A Comparison With Cardiac Magnetic Resonance Imaging.

Background: An electrocardiogram (ECG) is a simple and cheap non-invasive tool that shows various abnormalities and has prognostic value for patients with light-chain amyloidosis (AL). The present study aimed to explore the association between ECG characteristics and cardiac magnetic resonance (CMR)-detected amyloid burden and to investigate the prognostic value of ECG in AL amyloidosis. Methods: We prospectively enrolled 99 patients with AL amyloidosis (56 male patients; median age, 58 y). Detailed clinical information, 12-lead ECG, and CMR data were collected. All patients were followed up longitudinally, and the endpoint was all-cause mortality. ECG characteristics were analyzed and correlated with the degree of late gadolinium enhancement (LGE) and extracellular volume (ECV) by T1 mapping on CMR. The prognostic value of ECG characteristics was analyzed using Kaplan-Meier survival analysis and multivariate Cox regression. Results: During a median follow-up period of 33 months, 69 of the 99 patients died. Fragmented Q wave-R wave-S wave (QRS), pathological Q waves, the Sokolow index, QRS duration, and voltages were significantly associated with the extent of LGE, native T1, and ECV by CMR (p < 0.05). Fragmented QRS and Sokolow index showed independent prognostic value in AL amyloidosis (p = 0.001; p = 0.026, respectively). Fragmented QRS remained independent after adjusting for clinical values (hazard ratio: 2.034; 95% confidence interval: 1.148-3.603; p = 0.015). However, no ECG characteristics were independent predictors for prognosis in AL amyloidosis when LGE and ECV were included in the multivariate analysis. Conclusion: ECG abnormalities showed significant association with CMR indicators of amyloid burden. Fragmented QRS has an independent prognostic value in AL amyloidosis and could be used as an alternative marker when CMR is not available.

Future Perspectives of Cardiovascular Biomarker Utilization in Cancer Survivors: A Scientific Statement From the American Heart Association.

Improving cancer survival represents the most significant effect of precision medicine and personalized molecular and immunologic therapeutics. Cardiovascular health becomes henceforth a key determinant for the direction of overall outcomes after cancer. Comprehensive tissue diagnostic studies undoubtedly have been and continue to be at the core of the fight against cancer. Will a systemic approach integrating circulating blood-derived biomarkers, multimodality imaging technologies, strategic panomics, and real-time streams of digitized physiological data overcome the elusive cardiovascular tissue diagnosis in cardio-oncology? How can such a systemic approach be personalized for application in day-to-day clinical work, with diverse patient populations, cancer diagnoses, and therapies? To address such questions, this scientific statement approaches a broad definition of the biomarker concept. It summarizes the current literature on the utilization of a multitude of established cardiovascular biomarkers at the intersection with cancer. It identifies limitations and gaps of knowledge in the application of biomarkers to stratify the cardiovascular risk before cancer treatment, monitor cardiovascular health during cancer therapy, and detect latent cardiovascular damage in cancer survivors. Last, it highlights areas in biomarker discovery, validation, and clinical application for concerted efforts from funding agencies, scientists, and clinicians at the cardio-oncology nexus.

Prevalence and Outcomes of p.Val142Ile TTR Amyloidosis Cardiomyopathy: A Systematic Review.

BACKGROUND: The p.Val142Ile variant, predominantly found among people of African descent, is the most common cause of variant transthyretin amyloidosis and carriers predominantly develop a cardiomyopathy (variant transthyretin amyloidosis cardiomyopathy) phenotype. Yet, there are conflicting data on the prevalence and outcomes of p.Val142Ile variant carriers. METHODS: We performed a systematic review of the prevalence and outcomes of p.Val142Ile variant transthyretin amyloidosis cardiomyopathy among subjects of African descent. We found 62 relevant articles after searching the MEDLINE databases from 1980 to 2020 that reported data for ≈150 000 subjects. RESULTS: The reported worldwide prevalence of the p.Val142Ile variant is 0.3% to 1.6% in the general population. Among people of African descent, the reported prevalence from all studies ranges from 1.1% to 9.8%, but for studies with >1000 subjects, it is 3% to 3.5%. The prevalence of the p.Val142Ile variant in a region is dependent on the reported percentage of subjects who are of African descent in that region. p.Val142Ile variant transthyretin amyloidosis cardiomyopathy typically presents in the seventh to eighth decade of life and the majority of cases reported were male, with 25% to 38% diagnosed with atrial fibrillation. It was associated with a longitudinally worse quality of life and a lower adjusted survival compared with other types of transthyretin amyloidosis cardiomyopathy. CONCLUSIONS: The p.Val142Ile variant is the most common variant of the transthyretin gene with most carriers being of African descent. The true penetrance is unknown but the p.Val142Ile variant is associated with increased rates of incident heart failure and portends a lower overall survival. Increased awareness could lead to earlier diagnosis and improved heart failure outcomes among those of African descent, which is of increasing importance given the advent of novel therapeutics for this disease.

Coronavirus disease 2019 in heart transplant recipients: Risk factors, immunosuppression, and outcomes.

BACKGROUND: COVID-19 continues to inflict significant morbidity and mortality, particularly on patients with preexisting health conditions. The clinical course, outcomes, and significance of immunosuppression regimen in heart transplant recipients with COVID-19 remains unclear. METHODS: We included the first 99 heart transplant recipients at participating centers with COVID-19 and followed patients until resolution. We collected baseline information, symptoms, laboratory studies, vital signs, and outcomes for included patients. The association of immunosuppression regimens at baseline with severe disease were compared using logistic regression, adjusting for age and time since transplant. RESULTS: The median age was 60 years, 25% were female, and 44% were white. The median time post-transplant to infection was 5.6 years. Overall, 15% died, 64% required hospital admission, and 7% remained asymptomatic. During the course of illness, only 57% of patients had a fever, and gastrointestinal symptoms were common. Tachypnea, oxygen requirement, elevated creatinine and inflammatory markers were predictive of severe course. Age ≥ 60 was associated with higher risk of death and the use of the combination of calcineurin inhibitor, antimetabolite, and prednisone was associated with more severe disease compared to the combination of calcineurin inhibitor and antimetabolite alone (adjusted OR = 7.3, 95% CI 1.8-36.2). Among hospitalized patients, 30% were treated for secondary infection, acute kidney injury was common and 17% required new renal replacement therapy. CONCLUSIONS: We present the largest study to date of heart transplant patients with COVID-19 showing common atypical presentations and a high case fatality rate of 24% among hospitalized patients and 16% among symptomatic patients.