tbuckley/cabot-search huggingface dataset:
Abstract 4147061: Left Atrial Epicardial Adipose Tissue Is Associated with Worse Left Ventricular Strain in Atrial Fibrillation Patients
Authors: Ahmad Kassar, Nadia Chamoun, Yaacoub Chahine, Nazem Akoum
Journal: Circulation (2024)

Background: Atrial fibrillation (AF) is associated with abnormal left ventricular systolic and diastolic function. While left atrial epicardial adipose tissue (LA-EAT), a metabolically active visceral fat deposit has been associated with worse phasic left atrial strain, its effect on left ventricular (LV) function in AF patients is not well elucidated. Hypothesis: AF patients with increased LA-EAT have worse LV function. Aims: Assess the association between LV function in terms of global longitudinal strain (GLS) and global radial strain (GRS) and LA-EAT in AF patients. Methods: Patients were identified from the University of Washington Cardiac Arrhythmia Data Repository (CADRe). EAT volume was quantified using Dixon MRI sequences. The Cardiac Electro-Mechanic Research Group Application’s (CemrgApp) built-in tools were used to contour left atrial epicardial adipose tissue and total epicardial adipose tissue volume using Dixon sequences (panel A). Cardiac magnetic resonance cine images were used to extract GLS and GRS using image processing software (CVI42®) (panel B). Results: A total of 101 patients (average age 64 ±11 years; 72.3% male) were included. LA-EAT index was 18.22 ± 9.36 ml/m 2 . The median LV ejection fraction (LV-EF) was 57.6%±11.5. LV GLS and GRS were -14.86% ± 3.74% and 27.67%± 10.22% respectively. LA-EAT was significantly correlated with LV GLS (R=0.261; p=0.008) and GRS (R=0.283; p= 0.004); but not with LV-EF (R=0.134; p=0.181) (panel C). Multivariate linear regression also showed an independent association between LV GLS and GRS along with LA-EAT after adjusting for body mass index, left atrial volume, and congestive heart failure. Conclusion: LA-EAT is independently associated with worse LV global longitudinal strain and global radial strain. LA-EAT may negatively affect LV function in AF patients beyond the ejection fraction.
Abstract 4147261: Explainable AI Better Predicts 3-Year MACE Risk Compared to Clinical and ASCVD Models in the UK Biobank Cohort
Authors: Amritpal Singh, Rohan Dhamdhere, Gourav Modanwal, Sudeshna Sil Kar, Sadeer Al-Kindi, Anant Madabhushi
Journal: Circulation (2024)

Hypothesis: Artificial intelligence (AI)-derived retinal microvascular architecture from fundus images predicts time to MACE events. Objectives: To establish associations of retinal vessel features with 3-year MACE risk, and compare AI-derived retinal vessel-based MACE risk with Atherosclerotic Cardiovascular Disease (ASCVD) risk calculator. Methods: Baseline retinal fundus scans were identified for 2120 patients with no prior CVD events, from UK Biobank Cohort. Retinal features such as angle, tortuosity, curvature, and caliber, were extracted (Fig. A). A Cox proportional hazards model was trained using demographics and clinical risk factors (M clin ). AI-derived top 6 features extracted from retinal vessel analysis (M clin+AI ) were integrated and compared with ASCVD risk calculator. The models were trained on 1060 individuals (50%) and validated on a holdout set of 1060 individuals (50%). Performance was assessed using the concordance index (C-Index), hazard ratio (HR), and Kaplan-Meier (KM) curves, and models were compared using the Likelihood Ratio Test (L.R.T.) Results: In the holdout set, M clin+AI risk score achieved a C-index of 0.688, HR of 4.59 (2.66 -7.93, p&lt;0.001) for 3-year MACE event prediction compared to M clin (C-index=0.667, 3.30 (95% CI: 2.05-5.32), p&lt;0.001). M clin+AI was significantly better (L.R.T p&lt;0.001) than ASCVD risk calculator (C-index=0.640, 3.21 (95% CI: 1.84-5.60), p&lt;0.001), suggesting that retinal features hold promise for capturing novel information not included in current risk assessment tools, enabling improved immediate risk evaluation. M clin+AI demonstrates a notable advantage over other models for MACE risk prediction over 3, 5, and 10-year periods, with highest predictive power in the shorter term. Conclusion: AI-derived retinal features are strongly associated with 3-year MACE. Further multisite prospective validation is warranted.
Abstract 4147528: Subclinical Cardiac Dysfunction and Circulating Markers of Brain Injury in Older Adults
Authors: Temidayo Abe, William Tressel, Traci Bartz, John Gottdiener, Hooman Kamel, W Longstreth, Sanjiv Shah, JORGE KIZER, Luc Djousse, Kenneth Mukamal
Journal: Circulation (2024)

Introduction: Dementia has been strongly linked with cardiovascular disease, but the relationship between cardiovascular disease and brain health at subclinical stages remains uncertain. We explored the relationships between subclinical cardiac dysfunction, defined by echocardiography and cardiac biomarkers, and novel neurobiomarkers associated with dementia in older adults. Methods: We included 962 Cardiovascular Health Study participants free of previous stroke, transient ischemic attack, atrial fibrillation, heart failure, or myocardial infarction. We analyzed cross-sectional associations with serum neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) using linear regression. Subclinical cardiac measures included echocardiographic left atrial reservoir strain, left ventricular average longitudinal strain, early diastolic strain rate of the left ventricle, decreased left ventricular ejection fraction, average E/e’, percent predicted left ventricular mass, and left atrial diameter and circulating N-terminal pro-brain-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT). Results: Among 844 participants with NT-proBNP/hs-cTnT values, hs-cTnT was significantly associated with NfL, even after mutual adjustment for NT-proBNP (β=0.24, 95% CI: (0.10, 0.40); p=0.001. NT-proBNP was also associated with NfL (β=0.005, 95% CI: (0.000, 0.010), p=0.04), although this association was modestly attenuated and not nominally significant after adjustment for hs-cTnT (β=0.004, 95% CI: (-0.001, 0.010), p=0.08). No significant associations were observed for either circulating marker with GFAP, nor were echocardiographic variables associated with NfL or GFAP. Conclusions: In older adults with no clinically identified cardiovascular disease, subclinical cardiac dysfunction identified through hs-cTnT and, to a lesser degree, NT-proBNP was linked to higher levels of NfL, a marker of brain injury. This novel insight suggests that long-term prevention of even subclinical cardiac disease could also lead to better brain health.
Abstract 4147433: Left Ventricular Outflow Tract Gradient and Left Atrial Strain Predict Cardiac Outcomes in Young Hypertrophic Cardiomyopathy Patients
Authors: Addison Gearhart, Sonia Epstein, Kimberlee Gauvreau, Christina Mangano, Ming-Hui Chen
Journal: Circulation (2024)

Background: In adults with hypertrophic cardiomyopathy (HCM), left ventricular outflow tract (LVOT) obstruction and reduced left atrial strain (LAS) predict heart failure and cardiac event risk. However, data in children are limited. Hypothesis: LVOT gradient and LAS together determine cardiac outcome risk in children and young adults with HCM. Methods: All HCM patients with exercise stress echocardiography (ESE) from 2014-2022 at a single center were included. Patients were stratified by LVOT gradients: Group 1 (n=44, rest/exercise gradients &lt; 30mmHg); Group 2 (n=41, rest &lt; 30mmHg; exercise ≥ 30mmHg); Group 3 (n=29, rest/exercise ≥ 30mmHg). Composite cardiac outcome included cardiac syncope, non-sustained/sustained ventricular tachycardia, cardiac arrest, NYHA heart failure class ≥ II, heart transplantation, and HCM-related death. LA reservoir (LASr) and conduit (LAScd) strain were analyzed with TOMTEC AutoStrain LA. Cumulative incidence of composite outcome by LVOT group was estimated by Kaplan-Meier method. Multivariable Cox regression was used to evaluate the effect of adding LAS to a model containing only LVOT group. Model discrimination was assessed using the concordance (c) index. Results: 114 patients (32%F, median age 17 years) formed the cohort. At median 2.1 years follow-up [IQR: 1.0, 3.4] composite cardiac outcome risk was higher in Group 3 vs. 2 (HR=4.97, p=0.013, Figure 1). Composite cardiac outcome risk was lower in Group 1 vs. 2, but not significant (HR=0.70, p=0.66). Adjusting for LVOT group, lower LASr and LAScd were associated with greater cardiac outcome risk (per 5% LAS decrease: LASr HR=1.56, p=0.008; LAScd HR=1.77, p=0.002, Table 1). C index increased with inclusion of LASr or LAScd in the model (Table 1). Conclusion: In one of the largest young HCM cohorts evaluated with ESE, cardiac outcome risk increased with resting LVOT obstruction and reduced LA strain. LA strain demonstrated additive value for prediction of cardiac outcomes in children.
Abstract Sa1109: Aerobic Capacity of Adults with Fontan Palliation: Disease-specific Reference Values and Relationship to Outcomes
Authors: Ahmed Ali, Ahmed Goda, Omar Abozied, Alexander Egbe
Journal: Circulation (2024)

Background: Patients with Fontan palliation have reduced aerobic capacity because of impaired cardiac, pulmonary, and skeletal muscle function. However, the assessment of aerobic capacity in this population still relies on comparisons with people without cardiovascular disease, rather than comparison with the expected aerobic capacity of other Fontan patients. The purpose of this study was to determine the expected aerobic capacity of adults with Fontan palliation. Method: Adults with Fontan palliation who underwent cardiopulmonary exercise test at Mayo Clinic (2003-2023) were stratified into quartiles based on the predicted peak VO 2 . We assessed the correlates of predicted peak VO 2 , and the relationship between predicted peak VO 2 quartiles and cardiovascular outcomes (death/transplant). Results: Of 323 patients (age 29±9 years; 177 [55%] men), the median peak VO2 was 19.1 (15.2 - 23.9) ml/kg/min, and this corresponds to a predicted peak VO 2 of 51% (range 19 -88; interquartile range 41 - 62). The correlates of higher predicted peak VO 2 were smaller body mass index, higher systemic saturation, and lower Fontan pressures. The top, 2 nd ,3 rd , and bottom quartile of predicted peak VO 2 corresponds to predicted peak VO 2 of 63-88%, 51-62%, 41-50%, and 19-40%, respectively. Using the top quartile as the reference, the 3 rd quartile (HR 1.13, 95% CI 1.03-1.28, p=0.02), and 4 th quartile were associated with a higher risk of death/transplant (HR 1.32, 95% CI 1.16-1.69, p&lt;0.001). Conclusions: The results of the current study would help calibrate the interpretation of exercise test data in adults with Fontan palliation and improve risk stratification in this population.
Abstract 4147439: Accuracy of Rule-based Natural Language Processing Models for Identification of Pulmonary Embolism
Authors: SINA RASHEDI, Darsiya Krishnathasan, Candrika Khairani, Antoine Bejjani, Ying-Chih Lo, Mehrdad Zarghami, Shiwani Mahajan, Cesar Caraballo, jose victor jimenez ceja, David Jimenez, Manuel Monreal, Eric Secemsky, Erik Klok, Andetta Hunsaker, Ayaz Aghayev, Alfonso Muriel, Mohamad Hussain, Abena Appah-Sampong, Sanjay Aneja, HAMID MOJIBIAN, Samuel Goldhaber, Liqin Wang, Li Zhou, Harlan Krumholz, Gregory Piazza, Behnood Bikdeli
Journal: Circulation (2024)

Background: Some rule-based natural language processing (NLP) tools can identify pulmonary embolism (PE) from imaging reports. The external validity of these tools remains to be determined. Methods: We evaluated data for hospitalized patients from the Mass General Brigham (MGB) Health System (2016-2021). The NLP algorithms developed by Verma et al. and Johnson et al. were implemented on radiology reports to identify PE among 1,712 patients (mean age 60.6 years, 52.3% female). Previously, these two models had demonstrated high diagnostic accuracy for PE internally within the derivation cohorts (Figure). Manual chart review by two independent physicians using pre-specified criteria was set as the reference standard. Weighted estimates were determined based on the total number of hospitalizations at MGB (n=381,642). Results: The prevalence of PE in the weighted sample was 2.0% (7,708/ 381,642). The weighted estimates indicated high sensitivity (77.7% and 88.1%) and specificity (98.0% and 97.2%) but low positive predictive values (44.3% and 39.7%) for the models by Verma et al. and Johnson et al. (Figure). The most frequent reason for false positive findings was the inability of the tools to properly detect negation (such as “no PE”) from the radiology reports. Most false negative findings were related to the patients diagnosed with PE at another hospital and transferred to MGB; subsequently, they did not have an available imaging report from the index hospitalization. Therefore, the NLP algorithms led to false negative results (Figure). Conclusions: The rule-based NLP models showed high sensitivity and specificity for PE detection. However, they resulted in low positive predictive value in external validation, contrary to the derivation cohorts, limiting their utilization. Modifying the existing NLP tools and using large language models should be considered in upcoming studies to improve the positive predictive value.
Abstract 4147498: Prognostic Significance of Echocardiographic Transaortic Flow Rate in Aortic Valve Stenosis: a Systematic Review and Meta-Analysis
Authors: Mohammad Reza Hatamnejad, Hoda Mombeini, Fatemeh Chichagi, Mahta Arbabi, Parnian Jamshidi, Setayesh Sotoudehnia, Maryam Sahafi bandary, Moein Piroozkhah
Journal: Circulation (2024)

Background: Echocardiographic evaluation of Aortic valve stenosis (AS) severity relies on aortic valve area, peak jet velocity, and mean transaortic gradient. In pursuit of improving accuracy, the transaortic flow rate (FR), defined as the ratio of stroke volume to systolic ejection time, has been introduced. However, its prognostic value in AS patients remains controversial. Aim: This study aims to systematically review the predictive value of FR in AS patients and provide quantitative pooled analysis results where applicable. Methods: A systematic search of PubMed/Medline, Embase, Scopus, Web of Science, and Cochrane was conducted for observational studies on AS patients published up to March 15, 2024. Studies were included if they assessed the clinical prognostic utility of FR with at least three months of follow-up. Pooled estimates and 95% CI for FR's hazard ratio (HR) in each binary outcome were calculated using a random effects model. Results: Nineteen studies with 9456 patients (mean age 75) underwent descriptive analysis, and 17 eligible studies were included in the meta-analysis. For predicting all-cause mortality, the pooled HR for low FR measured at rest (cut-off value 200-210 mL/s) was 1.32 (95% CI: 1.01–1.63, I2: 69%, p&lt;0.05) (Figure 1. A). For FR measured during stress echocardiography, the pooled HR was higher at 1.58 (95% CI: 1.20–1.96, I2: 0%, p&lt;0.05). Additionally, every 100 mL/s increase in FR significantly reduced all-cause mortality; the HR was 0.61 (95% CI: 0.47–0.75, I2: 47%) for FR measured at rest (Figure 1. B), and 0.61 (95% CI: 0.31–0.91, I2: 65%) for FR measured during stress echo. For the combined endpoint of mortality and hospitalization, the HRs were as follows: 2.54 (95% CI: -0.99–6.08, I2: 48%) and 2.57 (95% CI: 0.69–4.44, I2: 0%) for the low FR group at rest and during stress echo, respectively. For every 100 mL/s increase in FR, the HRs were 0.19 (95% CI: -0.19–0.58, I2: 61%) at rest and 0.36 (95% CI: 0.18–0.54, I2: 0%) during stress echo. Conclusion: FR is a prognostic marker for all-cause mortality in AS patients, indicating its potential for risk stratification. Incorporating FR into clinical assessments could help personalize follow-up and monitoring strategies.
Abstract 4147781: ADMET-AI enables interpretable predictions of drug-induced cardiotoxicity
Authors: Kyle Swanson, Souhrid Mukherjee, Parker Walther, Celine Lai, Christopher Yan, Rabindra Shivnaraine, Jeremy Leitz, Paul Pang, James Zou, Joseph Wu
Journal: Circulation (2024)

Background: Drug-induced cardiotoxicity (DICT) is a severe adverse drug reaction that contributes to clinical trial failures and drug withdrawals. Forecasting DICT is challenging due to the property’s complex nature, and experimental assays are cumbersome and poorly correlate with human outcomes. Machine learning trained on clinical DICT data can quickly and accurately predict cardiotoxicity, pre-empting clinical failure and providing insight. Methods: We used our previously developed ADMET-AI machine learning platform to predict DICT and its sources. ADMET-AI is a freely available web tool (admet.ai.greenstonebio.com) that predicts 41 absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of a given molecule. We coupled ADMET-AI’s 41 ADMET property predictions with an Extreme Gradient Boosting (XGB) model to output a probability of cardiotoxicity. This XGB model was trained on 555 drugs from the published DICTrank dataset that have been labeled as having either no cardiotoxicity (262 drugs) or severe cardiotoxicity (293 drugs). Notably, over 67% of the DICTrank drugs are not in any of the 41 ADMET-AI training datasets. Results: The ADMET-AI-based cardiotoxicity XGB model, evaluated with 10-fold cross-validation, achieved an average area under the precision-recall curve (PR-AUC) of 0.75. Our model outperformed an XGB model trained on SwissADME predictions (PR-AUC=0.69). Shapley values identified CYP2D6 Substrate and Nrf2-Antioxidant Responsive Element as key predictors of severe cardiotoxicity, while CYP2D6 inhibition and Aromatase were linked to non-cardiotoxicity. t-SNE analysis of the DICTrank chemical space using the five most predictive ADMET-AI properties showed clear clustering of toxicity. Case studies of cisapride and lactulose illustrated the model’s ability to distinguish between cardiotoxic and non-cardiotoxic drugs based on predictions. Compared to publicly available models, ADMET-AI is currently the fastest and most accurate tool for ADMET and DICT prediction. Conclusions: ADMET-AI effectively predicts DICT with insight into potential causes, surpassing the current standard of public tools. The ADMET-AI-based cardiotoxicity prediction models are freely available to enable DICT prediction, with the potential to prevent late-phase clinical failures. While this study focuses on DICT, a similar workflow can adapt ADMET-AI to make predictions for other key properties in drug discovery.
Abstract 4147740: Association of Tissue Sodium with Nocturnal Hypertension and Dipping in Salt Sensitivity of Blood Pressure
Authors: Mert Demirci, Lale Ertuglu, Michael Pridmore, Rachelle Crescenzi, Cheryl Laffer, Alp Ikizler, Annet Kirabo
Journal: Circulation (2024)

Background: Salt sensitivity of blood pressure (SSBP) is an independent risk factor for cardiovascular mortality but the mechanisms are not fully elucidated. Nocturnal dipping of blood pressure, i.e. a decrease in blood pressure during sleep, is considered a sign of a healthy circadian rhythm. The disrupted dipping pattern,known as the non-dipping phenotype, is seen in individuals with SSBP and is associated with nocturnal hypertension and vascular inflammation. Tissue sodium levels are also associated with vascular dysfunction, but their impact on nighttime blood pressure has not been studied. We hypothesized that increased tissue sodium levels are associated with non-dipping pattern in patients with SSBP. Methods: Thirty hypertensive subjects were examined with an inpatient salt loading (SL) and salt depletion (SD) protocol. SL was achieved through saline infusion and a high-salt diet (460mmol/24 hours), while SD was achieved via diuretic administration (furosemide 40mgx3) and a low-salt diet(10mmol/24hours). BP measurements were recorded via ambulatory BP device (Spacelabs 90207). Baseline muscle and skin Na + levels were assessed with the 23 Na MRI technique. Spearman's correlation was used to analyze the associations. Demographic data are presented with mean and standard error of the mean. Results: Participant demographics and clinical data were as follows: age 53 ± 1.34 years,53% female,baseline systolic 140.2 ± 2.62mmHg, diastolic blood pressure 87.30 ± 1.77 mmHg and salt sensitivity index 3.72 ± 1.4 mmHg. While there were no correlations between baseline muscle Na + levels and daytime BP measurements, we found direct correlations with nighttime systolic BP(r=0.56 p=0.0043), mean arterial pressure (r=0.56 p=0.0039) and pulse pressure (r=0.40 p=0.0481) values after SL. Muscle sodium levels inversely correlated with dipping of SBP in SL Day(r=-0.53 p=0.0072). 24-hour total potassium excretion significantly correlated with dipping of SBP on SL day (r=0.65 p=0.0004). We noted an opposite trend in dipping of BP after SD, but this association did not achieve statistical significance (r=0.24 p=0.24). There were no significant correlations between Skin Na + and other measurements. Conclusion: These preliminary findings showed that lower muscle Na + was associated with greater dipping of BP after SL. The trend to reversal of dipping after SD highlights the potential importance of muscle Na + as a dynamic tissue and suggests a relationship with nocturnal BP dynamics.
Abstract 4147319: Anti-inflammatory Agents and their Effect on Cardiovascular Disease: A Comprehensive Review of Literature
Authors: Hamza Malik, Wissam Harmouch, steven mai, Salman Salehin, Syed Gilani
Journal: Circulation (2024)

Introduction: Historically, the pathogenesis of atherosclerotic disease has been characterized as an inflammatory process that drives the formation, progression, and rupture of plaques. Despite the recognized role of the immune response, current guidelines primarily emphasize statin and non-statin lipid lowering agents for the prevention of atherosclerotic disease. However, the utilization of anti-inflammatory agents and their effects on inflammation with respect to the attenuation of atherosclerosis has been recently highlighted in the literature. Aim: We aimed to investigate the role of immunomodulating agents in the prevention of atherosclerotic disease by means of a systematic review. Methods: We conducted a systematic search of MEDLINE, Cochrane, and Scopus databases through June 2024, for randomized control trials (RCTs) that assessed immunomodulating agents on outcomes of cardiovascular disease (CVD). Keywords included "anti-inflammatory therapy”, “immunomodulator therapy”, and “atherosclerotic disease”. Inclusion criteria involved participants aged 19 years and older with CVD and studies that assessed major adverse cardiovascular events (MACE), or atherosclerotic biomarkers. Results: Five RCTs were included in our systematic review, including CANTOS, COLCOT, LoDoCo2, RESCUE, and CIRT. Two RCT's evaluated immunomodulating agents, including the CANTOS trial which assessed canakinumab, an IL-1β inhibitor and the RESCUE trial which assessed ziltivekimab, an IL-6 inhibitor. The COLCOT and LoDoCo2 trials assessed colchicine while CIRT assessed methotrexate. All trials assessed the primary endpoint of MACE, except the RESCUE trial. The primary endpoint for the RESCUE trial was the percent change in high sensitivity CRP. All trials, except CIRT had statistically significant reductions in their primary endpoints. Conclusion: The advancements in targeted immune therapies offer promising new avenues in cardiovascular medicine. Our systematic review of RCTs suggests that anti-inflammatory agents have a beneficial role in the reduction of cardiovascular events and the progression of CVD in patients with atherosclerotic disease. While the majority of the included RCTs support the use of these agents, the heterogeneity in the individual studies emphasize the need for further research to investigate the role of immunomodulating agents on CVD outcomes.