tbuckley/cabot-search huggingface dataset:
Abstract 4141123: Utility of Comprehensive Profiling of Blood Amino Acid in the Identification and Clinical Characterization of High-Risk Populations for Developing Future Adverse Events in Patients with Cardiovascular Disease
Authors: Kohei Moribayashi, Yunosuke Matsuura, Kinuko Yamamoto, Hiroki Tanaka, Soichi Komaki, Masashi Yamaguchi, Takeshi Ideguchi, Toshihiro Tsuruda, Koichi Kaikita
Journal: Circulation (2024)

Background: The associations of specific blood amino acid (AA) metabolite levels with frailty and heart failure have been reported. However, the utility of comprehensive AA profiling in cardiovascular disease (CVD) patients remains unknown. Aims: This study aimed to determine whether plasma AA profiling through hierarchical clustering analysis (HCA) can identify and clinically define a high-risk population prone to future adverse events. Methods: We enrolled 267 patients (mean age 74 years, 60% male) with CVD (118 with ischemic heart disease, 85 with valvular heart disease, 33 with cardiomyopathy, and 31 with other CVD). In fasting plasma samples, 39 AA metabolite levels were measured using liquid chromatography-mass spectrometry. Hierarchical clustering was used for data analysis. Major adverse cardiovascular events (MACE) were defined as a composite of all-cause mortality, nonfatal myocardial infarction, ischemic stroke, and rehospitalization for worsening heart failure. During a one-year follow-up, MACE incidence was compared across HCA-based patient clusters using Kaplan-Meier (KM) curve analysis. The cluster with the worst prognosis was characterized clinically compared to other clusters. Results: HCA enabled patients to be categorized into four clusters (Figure 1A). KM curves showed that Cluster 2 had a significantly worse prognosis than other clusters (log-rank test; p=0.0018) (Figure 1B). AA metabolism in Cluster 2 was characterized by the lowest values of total AA, non-essential AA (NEAA), essential AA (EAA), branched-chain AA (BCAA), BCAA/total AA ratio, and NEAA/EAA ratio. Compared to non-Cluster 2 patients, those in Cluster 2 were older (p=0.004), had lower body weight (p=0.02), a higher prevalence of chronic kidney disease (p&lt;0.0001), higher levels of brain natriuretic peptide (p&lt;0.0001) despite similar left ventricular ejection fraction, lower albumin levels (p=0.001), and more frailty indicators, such as muscle weakness (p=0.002), slower walking speed (p=0.0003), and lower scores on the Short Physical Performance Battery (p=0.002). Conclusion: Comprehensive blood AA profiling can effectively identify high-risk CVD patient groups and provide relevant clinical characterization for prognosis.
Abstract 4140669: Leveraging Large Language Models (LLMs) For Randomized Clinical Trial Summarization
Authors: Anjali Mangla, Phyllis Thangaraj, Rohan Khera
Journal: Circulation (2024)

Background: With widespread scientific misinformation, access to primary literature, such as randomized clinical trials (RCTs), can empower patients in their decision-making about their health. However, scientific publications for RCTs – the bedrock of evidence-based cardiovascular care – are not written in accessible language for patients. We hypothesized that large language models (LLMs) could appropriately summarize RCTs into understandable language based on evaluation objective tools, enhancing patient-provider communication and informed consent. Methods: From the 3 major medical journals, we extracted 60 RCTs published between January and December 2023. Of these RCTs, 28% were cardiovascular. Each study’s abstract was the used as the reference text or the publicly available summary. Using the chat interface of GPT4, (1) we prompted it to summarize the complete articles to maximize patient understandability (Prompt 1), and (2) prompted it to score 100% on the Patient Education Materials Assessment Tool (PEMAT), a scoring system for evaluating health literacy developed by the AHRQ (Prompt 2). Two evaluators scored original article abstracts, Prompt 1 and Prompt 2. The 8 relevant PEMAT Understandability Scale Questions scored 0 (not present) or 1 (present), with a mean of 0.7 representing the accepted threshold for understandability [A]. Results: The abstracts scored a 0.5 (IQR 0.4, 0.6) on PEMAT, with 8.3% scoring above 0.7, with significant differences across the 3 journals [B]. Prompt 1 scored a 0.9 (IQR 0.8, 1.0), with 83.3% scoring above 0.7, and Prompt 2 scored a 1.0 (0.9, 1.0) and higher than Prompt 1 (p&lt;.001), with 100% scoring above 0.7 [B]. Both Prompts scored higher than the respective abstracts (p&lt;.001). These patterns were consistent across cardiovascular and non-cardiovascular RCTs. The domains where there were most substantial improvements from abstracts to Prompts 1 and 2 included the degree of distracting information, use of everyday language, explanation of medical terms, and of numbers, and without the need to do calculations. Conclusion: LLMs that are primed to align summaries with levels of health literacy, and especially with objective scores, can enable patients to have accessible and reliable information by summarizing primary clinical literature in language understandable to patients.
Abstract 4140745: Efficacy and Safety of Impella, Venoarterial Extracorporeal Membrane Oxygenation, and Intra-aortic Balloon Pump in Acute Myocardial Infarction- related Cardiogenic Shock: A Systematic Review and Network Meta-Analysis
Authors: Hussam Al Hennawi, Muhammad Sabri, Muhammad Khuzzaim Khan, Angad Bedi, Mazzoni Clifford Jennifer
Journal: Circulation (2024)

Introduction: Venoarterial extracorporeal membrane oxygenation (VA-ECMO) is being increasingly utilized for cardiogenic shock (CS). We compare the outcomes of using isolated mechanical circulatory support (MCS) versus Impella or intra-aortic baloon pump (IABP) for left ventricular unloading (LVU) in the context of VA-ECMO. Methods: We searched for Impella, VA-ECMO, and IABP utilization in acute myocardial infarction (MI) related cardiogenic shock. Primary outcomes included 30-day and 12-month mortality rates, major bleeding, and limb ischemia. Secondary outcomes were occurrence of major adverse cardiovascular events (MACE) and stroke. Data analysis utilized frequentist network meta-analysis with random-effects models, calculating odds ratios (OR) and 95% confidence intervals (CI). Results: We identified 22 studies, including 4 randomized controlled trials (RCTs) and 18 observational studies, involving a total of 79,149 participants. The average follow-up duration for these studies was 11 months, and the mean age of the included patients was 63 years. Regarding the 30-day mortality rate, IABP alone demonstrated a significant reduction compared to Impella and VA-ECMO [OR 0.54, 95% CI 0.40 to 0.72]. On the other hand, Impella alone exhibited the lowest 12-month mortality rate [OR 0.66, 95% CI 0.51 to 0.85]. Regarding complications, IABP showed a significantly lower risk of major bleeding [OR 0.29, 95% CI 0.14 to 0.61] and limb ischemia [OR 0.14, 95% CI 0.04 to 0.47] when compared to VA-ECMO and Impella. However, no significant difference was observed in the occurrence of stroke and MACE between Impella and IABP. Furthermore, there was no significant difference in the 30-day or 12-month mortality rate when VA-ECMO was combined with IABP or Impella. Conclusion: Impella offers significant long-term survival benefits, while IABP excels in short-term survival outcomes and reduces bleeding and thrombotic events with no significant difference in stroke and MACE risk.
Abstract 4141335: Modification Effect of Flu-like Illness on the Genetic Association of Dilated Cardiomyopathy
Authors: Hanyu Ni, Jinwen Cao, Daniel Kinnamon, Elizabeth Jordan, Ray Hershberger
Journal: Circulation (2024)

Background and Aims: Previous studies have speculated that a viral infection may act as a trigger in the development of idiopathic dilated cardiomyopathy (DCM) among people genetically at risk. This study aimed to describe the frequency of DCM patients who experienced a flu-like illness prior to the diagnosis and examine if this experience modifies the association of DCM with carrying DCM-relevant genetic variants. Methods: We analyzed data from the DCM Precision Medicine Study conducted between June 2016 and April 2021. Medical history including flu-like illness prior to DCM diagnosis was obtained from patient interview and medical record review. Exome sequencing identified DCM-related rare variants [pathogenic (P), likely pathogenic (LP), or uncertain significance (VUS)] and common variants via GWAS. Logistic mixed models with a case-only design were used to examine if flu-like illness modified the association between DCM and genetic risk. After imputation using the TOPMed Imputation Server, Firth logistic regression was used to examine if flu-like illness modified the association of DCM with each of 13,443,192 common autosomal variants (minor allele frequency &gt;=1%). Results: Of 1,164 patients with DCM, 351 (30.2%) reported episodes of flu-like illness proximal to their DCM diagnosis. The percent with a history of flu-like illness was higher among those aged &lt;45 than those aged &gt; 45 (35.2% vs. 27.4%, P=0.004) and among ever smokers than non-smokers (32.4% vs. 28.2%, P=0.04), but did not differ by other demographics, clinical comorbidities, or seasons. The percent with a history of flu-like illness by variant classification was 29.9% for LP/P, 29.6% for VUS only, and 30.1% for no LP/P/VUS. The odds ratio for an interaction between a history of flu-like illness and presence of any P, LP or VUS variants was 1.0 (95% CI: 0.7-1.3). A genome-wide significant association between rs2102158 and flu-like illness (p=1.1*10^-8) was identified at chromosome 3q24. Conclusions: We did not find evidence that a flu-like illness modified the association of DCM with DCM-relevant rare variants; however, our GWAS analysis suggested that flu-like illness may modify the effect of a common variant on the odds of DCM.
Abstract 4140786: The Outcomes of Takotsubo Cardiomyopathy Patients with Psychiatric Disorders: A Global Retrospective Analysis using TriNetX
Authors: Sahana Devakumar, Anderson Anuforo, Nikita Gupta, Rohan Kumar Ochani, Muhammad Hanif, Kan Liu, Cynthia Taub
Journal: Circulation (2024)

Background: High prevalence of psychiatric disorders (PD) is seen in Takotsubo cardiomyopathy (TC). Existing literature presents conflicting results but often identifies worse outcomes in patients with PD who develop TC. Primary limitations of those studies were relatively small sample sizes and insufficient matching for confounders. Therefore, we used a global database to determine differences in outcomes in TC patients with and without PD. Methods: We queried the TriNeTX Global collaborative network for adults diagnosed with TC between 2013 and 2023. We excluded patients with confounding diagnoses occurring 5 days before or after TC diagnosis and created two cohorts based on PD diagnosis. ICD-10 codes for PD included were: psychotic, mood and anxiety disorders. Propensity score matching (PSM) was conducted for over 50 covariates. After PSM, logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals. The primary endpoints were all-cause mortality, 4-point MACE and ICU admissions at 30 days, 90 days and 1 year. Acute appendicitis was used as a falsification endpoint. Result: The sample population had 10864 patients in the cohort with diagnosed TC and PD (Cohort 1) and 11,997 patients with TC without PD (Cohort 2). Before propensity score matching (PSM), Cohort 1 had significantly increased odds of ICU admissions (OR 1.32, 95%CI, 1.22-1.43) and 4-point MACE (OR 1.34, 95%CI, 1.26-1.44) but not all-cause mortality (OR 0.98, 95%CI, 0.88-1.09) at 30 days [Table 1]. After propensity score matching (PSM), both cohorts had 7,074 patients. Analysis post-PSM showed Cohort 1 had significantly lower odds of all primary outcomes compared to Cohort 2 at 30 days: All-cause mortality (OR 0.75; 95%CI, 0.66-0.86), 4 point MACE (OR 0.86; 95%CI, 0.79-0.94), and ICU admission (OR 0.88; 95%CI 0.80-0.97). These lower odds persisted at 90 days and 1 year. Conclusion: After extensive propensity score matching to eliminate confounders, there are reduced odds of 4-point MACE, all-cause mortality, cardiogenic shock and cardiac arrest in TC with PD cohort suggesting that patients with PD and TC have better cardiovascular outcomes if appropriately matched to a cohort with similar baseline characteristics.
Abstract 4141318: AI-Powered Smartphone Application for Detection of Left Ventricular Systolic Dysfunction using 12-Lead ECG
Authors: Anthony Demolder, Robert Herman, Boris Vavrik, Michal Martonak, Vladimir Boza, Martin Herman, Timotej Paluš, Viera Kresnakova, Jakub Bahyl, Andrej Iring, Jozef Bartunek, Marc Vanderheyden, Ward Heggermont, Martin Penicka
Journal: Circulation (2024)

Background: Though echocardiography is the cornerstone of cardiac function assessment in specialized practice, there is a lack of point-of-care tools for immediate evaluation of left ventricular ejection fraction (LVEF) in current practice facilitating the early identification of patients at risk for heart failure who may benefit from further echocardiographic evaluation. Aims: To develop and validate artificial intelligence (AI) models to identify reduced LVEF from a single 12-lead ECG using a smartphone application. Methods: We sourced all ECGs and transthoracic echocardiograms (TTEs) recorded between 2011 and 2021. ECGs were paired with TTEs conducted within a 24-hour window and were randomly divided into the model development dataset (50%) and validation dataset (50%). Two AI-ECG models were created: one to detect LVEF ≤40% and another for LVEF &lt;50%, following the AHA definition of heart failure. These models were coupled with smartphone-based ECG digitization technology. Performance metrics included area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1-score. Results: A total of 1,205,370 ECGs and 291,433 TTEs were collected and paired, resulting in 109,809 ECG-TTE pairs from 56,236 unique patients. The validation dataset consisted of 25,510 distinct TTE-ECG pairs (25,510 patients). Prevalence of LVEF≤40% and LVEF&lt;50% was 5.4% and 7.9% respectively. The LVEF≤40% model demonstrated an AUC of 0.963 (95% CI: 0.959-0.966), sensitivity 0.924 (95% CI: 0.91-0.937), specificity 0.887 (95% CI: 0.883-0.891), and F1-score of 0.474 (95% CI: 0.457-0.490). PPV and NPV were 0.318 (95% CI: 0.304-0.333) and 0.995 (95% CI: 0.994-0.996) respectively. Performance of the LVEF &lt;50% model shows an AUC of 0.952 (95% CI: 0.947-0.956), with a slightly lower sensitivity of 0.899 (95% CI: 0.886-0.912), specificity of 0.875 (95% CI: 0.871-0.879), PPV of 0.382 (95% CI: 0.368-0.395), NPV of 0.99 (95% CI: 0.989-0.992), and F1-score of 0.536 (0.521-0.55). Conclusion: The smartphone-integrated AI model can reliably detect reduced LVEF from standard 12-lead ECGs. Our findings suggest these single 12 lead-ECG based models could serve as a point-of-care screening tool to identify such patients benefiting from further echocardiographic evaluation and consequent management acceleration.
Abstract 4140731: Trends, Outcomes and Predictors of Mortality in Patients with Myeloproliferative Neoplasms Undergoing Percutaneous Coronary Intervention: Insights from National Database
Authors: Song Peng Ang, Jia Ee Chia, Chayakrit Krittanawong, Kanchan Misra, Vikash Jaiswal, David Song, Mohammed Haris Usman, Robert Piana, Debabrata Mukherjee
Journal: Circulation (2024)

Introduction: Myeloproliferative neoplasms (MPN) are stem cell disorders that include include polycythemia vera (PV), essential thrombocythemia (ET), chronic myeloid leukemia (CML), primary myelofibrosis (PMF), chronic neutrophilic leukemia, and less well defined entities such as chronic eosinophilic leukemia. MPN are associated with an increased cardiovascular risk including acute coronary syndrome. However, there is a lack of comprehensive data regarding the rate of coronary revascularization, as well as the in-hospital characteristics and outcomes for MPN patients. Objective: We aimed to evaluate the temporal trends and outcomes of percutaneous coronary intervention (PCI) among patients with MPN. Methods: The National Inpatient Sample database from 2016 to 2020 was queried to identify all PCI hospitalizations. Temporal trends and outcomes of patients with and without MPN following PCI were described. Propensity score matching (PSM) was implemented to compare outcomes between MPN and non-MPN groups. Results: Our study included 2,237,210 PCI hospitalizations with 7,560 (0.27%) patients having MPN. Throughout the study period, the prevalence of MPN among PCI admissions remained stable (p-value for trend = 0.12). Within the MPN subgroup, ET was the predominant condition (53.2%), followed by PV (24.2%), CML (19.6%) and PMF (3.0%), with no significant temporal variation in the distribution of these subtypes. Patients with MPN had higher prevalence of cardiovascular comorbidities than non-MPN patients. Following propensity score matching, MPNs were significantly associated with an higher risk of blood transfusions (OR: 1.66, 95% CI: 1.22-2.24, p=0.001) and AKI (OR: 1.39, 95% CI: 1.17-1.65, p&lt;0.001). In contrast, the risk of in-hospital mortality (OR: 1.18, 95% CI: 0.83-1.69, p=0.354 and bleeding (OR: 1.43, 95% CI: 0.90-2.27, p=0.127) did not significantly differ between the two groups. Conclusion: Our study demonstrated that while the prevalence of MPN among patients undergoing PCI remained stable, those with MPN faced higher risks of bleeding, blood transfusion and acute kidney injury. Further research is warranted to explore the underlying reasons for these increased risks and to improve outcomes in this high risk group.
Abstract 4140672: Integrated Bioinformatic Analysis of the Shared Molecular Mechanisms Between Osteoporosis and Aortic Stenosis
Authors: Yuejiao Yang, Liang Tang, Yang He, Zhaowei Zhu, yiyuan huang, Shenghua Zhou
Journal: Circulation (2024)

Background: osteoporosis (OP) and aortic stenosis (AS) are common in the elderly population, conferring a heavy world burden. Several epidemiological studies show a correlation between AS and OP independent of aging. However, the molecular and cellular mechanisms underlying stenotic calcification and OP remain poorly understood. Herein, this study aimed to identify crosstalk genes between OP and AS and potential mechanism. Method: AS and OP datasets were downloaded from the GEO database and were performed Weighted Gene Co-Expression Network Analysis (WGCNA) to get common key genes, and differential expression analysis to get common differentially expressed genes (DEGs). We also analyzed the protein–protein interactions (PPIs) of the common key genes and DEGs using the NetworkAnalyst online tool to find the intersection of correlated genes in OP and AS, the top 20 genes in each algorithm were selected as the candidate genes and the genes were calculated by more than six algorithms at the same time were chosen as candidate genes. We downloaded genes related to AS in the Comparative Toxicogenomics Database (CTD) to get the intersection with candidate genes as hub genes. The hub genes were certified in another OP dataset and AS dataset downloaded from GEO respectively. Result: 665 common Genes from WGCNA, which were enriched in the myeloid leukocyte activation, secretory granule membrane, cell adhesion molecules.13 of them were screened as candidate genes by 12 prediction algorithms in the Cytoscape. 161 common DEGs were differentiated in another AS database and OP database, which were enriched in natural killer cell mediated immunity, collagen-containing extracellular.19 genes were recognized as candidate genes by Cytoscape in the same way. 15 hub genes were selected by intersecting with candidate genes and genes downloaded from CTD as hub genes, including CD226, CD247, CD38, CD4, CD96, FCGR2B, GNG2, GRB2, GAMB, HSD17B6, ITGB2, KSD17B6, ITGB2, KLRB1, NGF, PECAM1, SDC1. The transcription factors hub genes interaction network was constructed using TRRUST. Hub genes were certified in another AS and OP dataset. CD4, GZMB, SDC1 are upregulated remarkably in AS dataset, whereas SDC1 and ITGB2 are downregulated and GZMB is upregulated in OP dataset. Conclusion: GZMB, SDC1may be potential hub genes in AS and OP, through bioinformatic analysis, we identified potential biomarkers and therapeutic targets for AS and OP, providing a theoretical basis for future studies.
Abstract 4140752: Aspirin Use among Women at High-Risk for Pre-eclampsia in the United States
Authors: Abiah Pritchard, Cancan Zhang, Kenneth Mukamal
Journal: Circulation (2024)

Background: Pre-eclampsia is a major cause of maternal and neonatal morbidity and mortality and impacts 5-7% of pregnancies. Randomized trials have shown that aspirin reduces the risk of pre-eclampsia by 10-20%. In 2018, ACOG recommended the use of aspirin in high-risk women and “consideration” in those with moderate risk factors, which would newly include African American race. We sought to determine the proportion of women at risk for pre-eclampsia in the US receiving aspirin and how new guidelines impacted use. Methods: We used survey data from the National Ambulatory Medical Care Survey (NAMCS), a nationally representative survey conducted by the CDC of ambulatory health visits. We assessed visits of pregnant women from 2014-6 and 2018-9 and examined aspirin use according to pre-eclampsia risk status. High-risk includes those with hypertension, diabetes, or chronic kidney disease; medium-risk includes those with &gt;=2 of the following: Black race, low socioeconomic status (identified by Medicaid enrollment), obesity, and age &gt;=35. To determine if aspirin use was well-captured, we tested validity using coronary heart disease. Results: We identified 3,362 visits among pregnant women 2014-9, of which 8.3% occurred with high-risk women (Table 1). Aspirin use increased modestly at visits among low- and medium-risk women after guideline publication, to 1.7% (95% CI 0.5-3.9%) of visits in 2018-9. In contrast, aspirin use increased substantially at visits with high-risk women, though still remained low at 12.3% (95% CI 3.9-27%). Conclusions: Aspirin is an inexpensive and accessible intervention to reduce pre-eclampsia, a driver of adverse pregnancy outcomes and observed racial disparities. Aspirin use in moderate-risk women had minimal change over the time period, suggesting little immediate impact of the 2018 guidelines. Use in high-risk women increased significantly, but still remains low. Systematic efforts to ensure widespread and equitable use of this therapy are needed.