tbuckley/cabot-search huggingface dataset:
Abstract 4142449: The Impact of a Closed Unit Model on Cardiac Intensive Care Unit Outcomes: A Before-After Study
Authors: Colin Hinkamp, Matthew Nardi, Mourad Senussi
Journal: Circulation (2024)

Background: The ‘closed unit model’ is increasingly being adopted as a model for providing critical care to cardiac patients in contemporary intensive care units (ICU), where patients are under the direct care of an intensivist-led primary team. Many data demonstrates improved outcomes in various other intensive care settings, but few data exist in the context of cardiology intensive care. We aim to assess the clinical implications of adopting a closed unit model in our cardiac intensive care unit (CICU) across a variety of parameters. Hypothesis: Adoption of a closed unit model will result in improvement in mortality rate, ICU length of stay (LOS), and spontaneous awakening trial (SAT) and spontaneous breathing trial (SBT) compliance. Methods: We performed a before—after retrospective comparison of patients admitted to the CICU at our tertiary care hospital after adoption of a closed unit model on 1 January. The study period was the first 3 months after adoption of the closed model, with the 3-months preceding adoption of the closed model serving as the comparison group. Mortality, SAT and SBT rates were compared using the Chi-squared test and median CICU LOS was compared using the Wilcoxon rank-sum test. Results: 751 individual patients were admitted to the CICU and analyzed (380 before vs 371 after adoption). The mortality rate significantly improved (10% vs 6.7%; p=&lt;0.01; Figure 1). Despite this, there was no significant change in median LOS (2.7 days [IQR 1.11-5.73] vs 2.5, [IQR 1.16-6.14]; p=0.54). There was also a significant improvement in SAT (66.8% vs. 73.6%; p=&lt;0.01) and SBT rates (90.3% vs. 94.6%; p=&lt;0.01; Figure 1). Conclusions: Adoption of a closed unit model resulted in a statistically significant improvement in CICU mortality and daily SAT and SBT compliance, although surprisingly there was no improvement in LOS. These findings suggest that our transition to a closed unit model enhanced our patient's outcomes likely through promoting improved adherence to evidence-based critical care principles. Further study is needed to explore the factors contributing to the unchanged LOS and to better evaluate the long-term impact of a closed unit model on outcomes and resource utilization in cardiac ICUs.
Abstract 4142250: Circulating Progenitor Cells are Associated with Cognitive Impairment and Structural Brain Changes
Authors: Edward Woods, Matthew Gold, Alireza Rahbar, Mohammad Hossain, Ihab Hajjar, Edmund Waller, Arshed Quyyumi
Journal: Circulation (2024)

Introduction: Circulating progenitor cells (CPC’s) are mononuclear stem cells which originate in the bone marrow, and circulate in the blood, playing a role in promoting vascular regeneration and healing. Previous studies have shown associations between lower levels of CPC’s and increased all-cause mortality, MACE, and atherosclerosis. Additionally, those with cognitive disorders such as Alzheimer’s disease have been shown to have reduced levels of CPC’s, and some association between CPC’s and cognitive decline has been shown. Clinical surrogates for cognitive decline include a lower Montreal Cognitive Assessment (MoCA) score, and an increase in white matter hyperintensities (WMH) on MRI. We hypothesize that reduced circulating EPCs are associated with a lower MoCA score and an increased number of white matter hyperintensities (WMH) on MRI. Methods: In 181 participants (40.3% male, 41.4% Black) with and without mild cognitive impairment, CPCs were enumerated by flow cytometry as CD45 med mononuclear cells expressing CD34 and co-expression with either CD133, chemokine CXC motif receptor 4 (CXCR4), or vascular endothelial growth factor receptor-2 (VEGF2R). Participants were followed for four years and underwent neuropsychiatric testing and MRI imaging. MoCA testing was used to evaluate multiple domain cognitive function. Diffusion weighted MRI was used to evaluate for WMH indicating microvascular damage. Linear regression modeling was used to determine the cross-sectional association between CPC’s and both the MoCA score and burden of WMH after adjusting for age, gender, race, body mass index, history of heart failure, and history of chronic kidney disease. Results: Lower levels of CD34/VEGF2R were associated with lower MoCA scores (β=1.31, p=0.025) and more WMH (β= -2109.1, p=0.011) when comparing first and fourth quartile of CPC concentration. Additionally, decreased CD34/133 and CD34/CXCR4 were associated with an increased burden of WMH (β= - 3491.1, p=0.029 and β= -2419.8, p=0.012) when first and fourth quartiles were compared. Conclusions: Lower CPC counts of CD34 subsets were associated with worse performance on MoCA and more white matter hyperintensities on MRI, demonstrating that lower endothelial regenerative capacity may lead to decreased cognition and cognitive decline.
Abstract 4142993: Myocardial Performance Score: A Novel Marker of Cardiac Power and Efficiency for Prognostication of Advanced Heart Failure
Authors: Michael Randazzo, Anthony Kanelidis, Sara Kalantari, Bryan Smith, Ann Nguyen, Bow Chung, Stanley Swat, Nitasha Sarswat, Christopher Salerno, Valluvan Jeevanandam, Gene Kim, Mark Belkin, Jonathan Grinstein
Journal: Circulation (2024)

Introduction: Assessment of invasive hemodynamics is a critical aspect of heart failure (HF) management influencing treatment decisions. However, standard metrics including intracardiac filling pressures and cardiac output do not consistently predict clinical outcomes. The myocardial performance score (MPS) is a novel hemodynamic parameter that combines myocardial power and efficiency into a single variable. We aimed to evaluate the prognostic significance of MPS and assess whether it can improve risk stratification compared to traditional measures. Methods: All patients who underwent isolated right heart catheterization for chronic, or acute on chronic HF between 2013-2019 at our institution were retrospectively analyzed. MPS is calculated as [aortic pulsatility index (API) x cardiac power output (CPO)]/2. The primary outcome was a composite endpoint of death or need for left ventricular assist device or heart transplant over a two-year period. MPS thresholds of 0.5 and 1.0 were selected from prior analyses showing declining efficiency less than 0.5 in addition to balanced power and efficiency greater than 1.0. Kaplan-Meier curves were calculated with statistical significance determined by log-rank tests. Results: A total of 709 patients (60±14 years; 54% male) were included, of which 102 (14%) had an MPS&lt;0.5, 169 (24%) had an MPS between 0.5-1.0, and 438 (62%) had an MPS≥1.0. Of the 607 patients with an MPS≥0.5, 379 (62%) demonstrated freedom from the composite endpoint compared to 37 (36%) patients with an MPS&lt;0.5 (p&lt;0.0001). An intermediate MPS (0.5≤MPS&lt;1.0) conveyed significantly greater freedom compared to patients with a low MPS&lt;0.5 (57% vs 36%; p&lt;0.001), yet lower freedom compared to those with a high MPS≥1.0 (57% vs. 66%, p&lt;0.05). An MPS&lt;0.5 demonstrated superior risk stratification with an odds ratio for the composite endpoint at two years of 3.1 compared to 1.8 for pulmonary capillary wedge pressure&gt;15 mmHg and cardiac index&lt;2.0 L/min/m 2 estimated by Fick equation or thermodilution (Figure). Conclusions: MPS is a novel, advanced hemodynamic measurement that outperforms current invasive hemodynamic parameters in accurately predicting long-term clinical outcomes in all patients with heart failure.
Abstract 4142868: AI-enhanced Electrocardiographic Evaluation of Left Ventricular Ejection Fraction and Outflow Tract Gradient in Hypertrophic Cardiomyopathy
Authors: Veer Sangha, Arya Aminorroaya, Lovedeep Dhingra, Aline Pedroso Camargos, Evangelos Oikonomou, Rohan Khera
Journal: Circulation (2024)

Background: Longitudinal assessments of left ventricular ejection fraction (LVEF) and left ventricular outflow tract (LVOT) gradient have become critical in the management of HCM with the emergence of cardiac myosin inhibitors (CMI) but rely on repeated echocardiography. We developed AI-enhanced tools to evaluate these echocardiographic parameters using images/photos of 12-lead ECGs and 1-lead ECG signals captured by portable devices. Methods: Using ECGs and paired echocardiograms recorded within 30 days at Yale during 2015-2022, we developed convolutional neural networks to predict continuous LVEF and LVOT gradients from 12-lead ECG images and lead I ECGs. We plotted 12-lead ECGs in varying layouts to ensure the image model was agnostic of real-world variations and augmented ECG signals with random Gaussian noises to improve the 1-lead model’s resilience to noisy acquisition. We leveraged resampling and weighted loss functions to optimize our regression models. We tested our models for detecting EF&lt;50%, and LVOT≥30 and ≥20 mmHg – clinically important thresholds for treatment with CMI – on ECGs from a subset of patients with cardiac-MRI confirmed HCM. Results: Models for LVEF and LVOT were developed in 98,778 and 11,135 unique patients, respectively. The LVEF models were tested on ECGs from 489 unique patients with HCM (age 61 [IQR:53-68] years, 182 [37.2%] women, 46 [9.4%] EF&lt;50%) who were not in the development cohort. The image and 1-lead LVEF models had AUROCs of 0.865 and 0.803, sensitivities of 91.3% and 89.1%, and specificities of 63.7% and 44.0%, respectively. We tested the LVOT models in 426 patients with HCM (61[53-69] years, 163 [38.3%] women, 19 [4.5%] LVOT≥30, 28 [6.6%] LVOT≥20). The image and 1-lead LVOT models had AUROCs of 0.833 and 0.817, sensitivities of 89.5% and 90.0%, and specificities of 58.5% and 52.7%, respectively, for detecting LVOT≥30, and AUROCs of 0.784 and 0.722, sensitivities of 92.9% and 89.3%, and specificities of 58.5% and 35.5%, respectively for LVOT≥20. Conclusion: AI applied to accessible modalities such as ECG images and 1-lead ECGs from portable devices may mitigate the burden of therapeutic monitoring for CMI in HCM, but further development and refinement are needed to fully validate their clinical utility as an efficient alternative to echocardiography.
Abstract 4142984: Sex Differences in Atrial Fibrillation: Insights from Metabolomics and Transcriptomics
Authors: Ningjing Qian, Junyan Jin, Ying Gao, Yaping Wang
Journal: Circulation (2024)

Background: Patients with atrial fibrillation (AF) show different prevalence, complications and prognosis between sexes, which increases the difficulties of risk stratification and therapy strategy management. However, the underlying reasons remain unclear. Hypothesis: Plasma metabolites might contribute to sex differences in AF. Methods: Plasma samples of male and female patients with AF were collected and performed with metabolomics analysis. Transcriptomics data of atrial tissue from GEO database was analyzed based on a sex stratification. Metabolomics and transcriptomics data were further integratedly analyzed to explore the association among metabolites, atrial remodeling and AF. The related different expressed genes were validated by qPCR. Results: Metabolomics analysis showed 155 higher-level metabolites and 408 lower-level metabolites in female patients with AF compared to male patients. And a total of 41 annotated metabolites were further identified. Especially, plasma level of phenylalanine was significantly lower in female patients with AF compared with male patients (FC 0.79, p &lt;0.05) while plasma levels of phenylalanine derived-metabolites, including 3,4-dihydroxyphenylacetic acid and 4-hydroxybenzoic acid were significantly higher in female patients with AF compared with male patients (FC 1.71, p &lt;0.05; FC 2.29, p &lt;0.05). KEGG pathway analysis also showed differential metabolites were enriched in phenylalanine, tyrosine and tryptophan biosynthesis and phenylalanine metabolism pathways. Transcriptomics analysis of left atrium suggested that atrial remodeling in males with AF was prone to be enriched in metabolic pathways while that in females was strongly enriched in inflammation related pathways. Moreover, related genes responded to phenylalanine and phenylalanine derived-metabolites such as NRF2, GPX4 were both significantly unregulated in left atrium of AF patients compared to those of sinus rhythm (SR) patients in males (FC 3.96, p &lt;0.01; FC 2.20, p &lt;0.05) while were not significantly altered between AF and SR patients in females (both p &gt;0.05). Conclusion: This study highlights sex differences of plasma metabolites in patients with AF and their association with differential transcriptomic signature of left atrium. The findings provide new insights into understanding sex differences in AF and identify several specific metabolites, which underscores the importance of taking sex differences into consideration during decision making in clinical practice.
Abstract 4143034: High-Intensity Statins in Veterans with Peripheral Artery Disease
Authors: Saket Girotra, Qiang Li, Mary Vaughan Sarrazin, Rohit Nathani, Paul Chan, Cathy Nguyen, Richard Hoffman, Nicole Minniefield-Young, Shirling Tsai, Glenn Gobbel, MOHAMMED AL-GARADI, Kim Smolderen, Shipra Arya, Joshua Beckman, Brian Lund
Journal: Circulation (2024)

Background: Current guidelines recommend high-intensity statins in patients with peripheral artery disease (PAD) to reduce the risk of cardiovascular and limb events. The extent to which these recommendations have been adopted in a large integrated health system remains uncertain. Methods: Using a novel natural language processing system that we previously developed and validated for identifying PAD, we created a registry of patients with a new diagnosis of PAD during 2015-2020 in the Veterans Health Administration (VHA). We used VHA pharmacy data to determine rates of active statin use at index date (date of PAD diagnosis), new initiation, persistence, and adherence (definitions in Table 1). High-intensity statin was based on statin type and dose. Analyses were also stratified by presence of pre-existing atherosclerotic cardiovascular disease (ASCVD), which was defined as a prior history of coronary or cerebrovascular disease. Results: Among 103,748 patients, 64,159 (61.8%) were on statins at index date (baseline) and 30,968 (29.8%) were on high-intensity statins (Table 1). An additional 14,219 patients (13.7%) initiated statins within 1 year of PAD diagnosis, of whom 6,384 (6.2%) initiated high-intensity statins. Rates of active baseline use, or new initiation in 1 year were much lower in patients who did not have pre-existing ASCVD, compared to those with ASCVD (Table 1). Persistence with therapy among total active users was 78.0% for any statin and 78.6% for high-intensity statins. Mean adherence among persistent users was &gt;80% for any statin and high intensity statin. Persistence and adherence did not differ in subgroups stratified by ASCVD. Conclusion: Although more than 75% PAD patients were already on, or initiated a statin within 1 year of PAD diagnosis, only 36% were on high-intensity statins. Baseline use and new initiation of any statin and high-intensity statin was lower in PAD patients who did not have co-existing ASCVD. Overall, persistence among active users, and adherence among persistent users was high, and did not differ by statin intensity or pre-existing ASCVD. Given the strong evidence supporting high-intensity statins in PAD, interventions targeting intensifying statin therapy in PAD, especially in those without pre-existing ASCVD are warranted.
Abstract 4142897: The Burden of Adult Congenital Heart Disease in the United States
Authors: Vasupradha Suresh Kumar, Craig Sable, Dorothy Nakiwala, Nicholas Kassebaum
Journal: Circulation (2024)

Introduction: The Global Burden of Disease (GBD) study provides a unique opportunity to better understand fatal and nonfatal outcomes and their socioeconomic drivers in adults with congenital heart disease (ACHD). The aim of this study is to better understand trends in ACHD in the US and to analyze socioeconomic factors that may be correlated to geographic differences in patient outcomes. Methods: State specific data on mortality, prevalence, and disability adjusted life years (DALY) were acquired from GBD Database from 1990 to 2021 for ACHD patients aged 20 years and older in the USA. We subsequently correlated this data with median household income and percent uninsured in each state by using the US census bureau poverty and income data. Results: There are 292,625 (95% CI 258,956 – 342,906) adults &gt; 20 years in the USA living with CHD in 2021 (compared to 212,366 in 1990). In 2021, ACHD was responsible for 1074 (CI 964 -1331) deaths and 62,244 (CI 51,820 – 76,301) DALYs ( FIGURE 1 ). Between 1990 and 2021 there was a decrease in rates of mortality (0.79 to 0.43/100,000) and DALYs (44 to 25/100,000). There is considerable variation by state. The state with the highest mortality and DALYs (West Virginia) also has one of the lowest median household incomes ($51,122). States with lower ACHD mortality have higher median household incomes (r 2 =0.612, p&lt;0.001) ( FIGURE 2 ). The percent uninsured in each state also has a positive correlation with mortality (r 2 =0.142, p=0.006). Conclusion: The GBD study provides unique insight into ACHD mortality, prevalence, and disability and should be considered the gold standard for prevalence, disablity and mortality in the US. While mortality and disability rates have decreased from 1990 to 2021, ACHD patients living in states with lower median household income and higher percent uninsured have higher rates of mortality and disability. Investment into more equitable access to care is warranted for this population.
Abstract 4143004: A Stepwise Approach to Identifying and Assessing the Content Validity of Patient-Reported Outcome (PRO) Measures for Use with Adults with Acute Heart Failure
Authors: Meaghan OConnor, Anita Loughlin, Laura Waldman, Sloan Rucker, Shailja Vaghela, Namhee Kwon, Vanja Sikirica
Journal: Circulation (2024)

Different patient-reported outcome (PRO) measures have been used and validated in studies of patients with heart failure (HF), including disease-specific measures like the 23-item Kansas City Cardiomyopathy Questionnaire (KCCQ). However, there is limited research available regarding the content validity (i.e., comprehensiveness, relevance, and comprehensibility) of those measures specifically as it relates to patients with acute HF (AHF). This study used a stepwise approach to identify PRO measures used in AHF studies and evaluate their content validity through a landscape analysis, concept mapping, and cognitive debriefing (CD) interviews with US-based patients. A landscape analysis was performed to identify PRO measures used in AHF studies. To assess concept coverage, items in each PRO measure were mapped to concepts (i.e., signs/symptoms and impacts on daily life) from the AHF conceptual model developed by Moshkovich et al. (2020). PRO measures with the most comprehensive and/or appropriate concept coverage were further evaluated through CD interviews with US adults who had been hospitalized for AHF within the last six months. The landscape analysis resulted in the identification of 15 PRO measures for use in AHF; nine were deemed appropriate for concept mapping. Following mapping, four measures were selected for further research based on their comprehensive concept coverage (KCCQ, PROMIS®+HF-27), effectiveness at measuring health utility (EQ-5D-5L), and suitability for measuring shortness of breath (a dyspnea numeric rating scale [NRS]). The KCCQ, in particular, showed good concept coverage, addressing more than half (n=12) of the key concepts in the Moshkovich et al. (2020) model. Twenty adults with AHF, representing NYHA classes I (n=4), II (n=8), and III (n=8), a mean age of 64 years (range: 39-81), and an average of 110 days since hospitalization (range: 26-183), participated in CD interviews. Participants found each measure easy to understand and answer, with items relevant to their experience of AHF. Participants found the recall periods, ranging from 24-hours to 2-weeks, appropriate and easy to use. This study’s stepwise approach allowed for the systematic identification and evaluation of the content validity of four PRO measures—the KCCQ, dyspnea NRS, EQ-5D-5L, and PROMIS®+HF-27—for use with adults with AHF. This research fills a gap in the current published literature regarding measures appropriate for use with adults with AHF.
Abstract 4142999: How many and which leads in ECG do you need to estimate a patient’s ejection fraction? A Deep Learning Approach.
Authors: Tienhsiung Ku, Hao-Chun Chang, Chih-Wei Chiu, Dann-Pyng Shih, Tzong-shiun Li, Ming-Tse Tsai
Journal: Circulation (2024)

Patients with heart failure (HF) can range from being asymptomatic to experiencing various combinations of symptoms. Left ventricular ejection fraction (EF), measured via echocardiography, is the primary tool to differentiate between different HF types and guide therapies. However, the availability of echocardiography varies geographically. In contrast, electrocardiograms (ECGs) are more common and easily accessible. In this study, we use a deep learning approach to correlate ECG readings with their corresponding EF. Low EF is defined as ≤ 35%. Patients with the International Classification of Diseases codes for HF were screened retrospectively at Changhua Christian Hospital, Taiwan, from 2016 to 2022 with IRB approval. Only data comprising sex, age, a 10-second ECG record with a sampling rate of 500 Hz, and an echocardiography report obtained within 7 days after ECG acquisition were included. There were 3,508 samples (low EF: normal EF = 1,430:2,078) from 1,240 patients in the dataset. We reserved 10% of the samples as the final testing set (n=351) and split the remaining 90% randomly into the training and validation sets (n=2,525 and n=632) in a ratio of 8:2. A convolutional neural network was trained to classify input ECG lead(s) as either low or normal EF. For simplicity, the model with the lowest validation loss was selected and further evaluated on the final testing set. There were 721 males and 519 females with a mean age of 70.47 (±14.59). We experimented with various combinations of limb and chest leads as input ECG data and used the validation set to assess their performance, as shown in Table 1. The model trained with leads V2, I, and II had the lowest validation loss and achieved 71.3% sensitivity, 88.6% specificity, and an AUC of 87.6% on the testing set. With more information from multiple leads, a patient’s EF could be better predicted; however, the incremental benefits tapered off quickly. In our investigation, the best model was found by combining information from three leads: I, II, and V2. Our study discovered a pathway to ECG-based artificial intelligence applications and provided innovative insights into medical device design, which could benefit patients in under-resourced areas.