tbuckley/cabot-search huggingface dataset:
Abstract 4141803: noise-induced sleep disruption reduces myocardial perfusion and impairs cardiac function in mice
Authors: Kara Gouwens, Yibing Nong, Bradford Hill, Matthew Nystoriak
Journal: Circulation (2024)

Sleep is essential for heart health throughout the lifespan. Although poor sleep is linked to cardiovascular disease and all-cause mortality, there is little known about how chronic sleep disruption affects the heart. Because adequate oxygen delivery is necessary to sustain cardiac function, we hypothesized that sleep disruption suppresses myocardial perfusion, which over time, could impair mechanical performance. To test this, we examined how environmental noise, a major contributor to human sleep disruption, applied during the murine inactive/light phase (noise-induced sleep disruption; NISD) impacts sleep patterns and myocardial perfusion in C57BL/6N male mice. We surgically implanted EEG/EMG transmitters to quantify wake and sleep periods. After recovery and a baseline period (2d), mice were exposed to randomized noise (2,382–4,000 kHz; ≤103 db; ≤39 sec) between 6:00–18:00 (NISD group). Control mice underwent the same procedure, but without noise application. Sleep durations were measured at baseline, 1 d, 2 wk, and 4 wk. Relative to control mice, NISD showed fragmented sleep patterns with reduced sleep bout length (~17%; p=0.02) and increased sleep bout number (~26%; p=0.09) when normalized to respective baseline data, yet similar 24 hr total sleep duration (control: 11.6 ± 0.3 h, NISD: 11.4 ± 0.9 h; n=3–4/group, p=0.82). After 4 wk of NISD, myocardial perfusion and cardiac function were measured using contrast echocardiography and left ventricular pressure-volume recordings at baseline and following norepinephrine-mediated increases in cardiac work. In control mice, myocardial perfusion increased in proportion to increases in cardiac work; however, in the NISD group, the slope of the relationship between myocardial perfusion and cardiac work was significantly blunted (control: 0.0058 ± 0.002; NISD: 0.0002 ± 0.001; n=4–5/group, p=0.01). Echocardiography revealed increased left ventricular diameter (LVID s , control: 2.2±0.2 mm, NISD: 2.6±0.2 mm; p=0.01), and two-dimensional speckle tracking showed a significant reduction in global longitudinal left ventricular strain (control: 19.5±2.5%, NISD: 16.4±0.8%; p=0.02) in NISD mice compared with controls, consistent with moderate systolic impairment following prolonged sleep disruption. Taken together, these data support the concept that environmental factors, via effects on sleep quality, can impact the regulation of blood flow to the heart and cardiovascular health.
Abstract 4141884: Fully Automatic Quantification of the Aortic Root in 4D Transesophageal Echocardiography
Authors: Silvani Amin, Trevor Chan, Nathanael Tran, Lourdes Al Ghofaily, Albert Cheung, Natalie Yushkevich, Jilei Hao, Matthew Jolley, Y Joseph Woo, Joseph Bavaria, Nimesh Desai, Alison Pouch
Journal: Circulation (2024)

Introduction: Aortic root (AoR) morphology and dynamics are integral to understanding aortic valve function and planning patient-specific aortic interventions with transesophageal echocardiography (TEE). Modeling the AoR in time-varying 3D data is advantageous over conventional 2D cross-sectional analysis. However, manual segmentation of the AoR in 3D relies on a learning curve and takes up to 1.5 hours per volume. We hypothesize that the AoR can be rapidly and accurately segmented and quantified fully automatically with deep learning in pre-operative 4D TEE. Methods: Pre-operative TEE from both bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV) patients were semi-automatically segmented and manually verified. A nnU-Net model was trained, validated, and tested with 74 TEE time-series images (46 BAV, 28 TAV) consisting of 1971 individual 3D volumes (60/40% training/testing split) from 2 institutions. The Dice similarity coefficient and average mesh-to-mesh distances were compared to interobserver variability between multiple manual tracers. AoR volume and diameters were automatically computed. Quantification agreement between model-generated and semi-automatic segmentations was analyzed with the intraclass correlation coefficient and Student’s t-test. Results: A representative automatic segmentation and quantification of the AoR is shown in Figure 1a-c. Quantification agreement between automatic and manual segmentations for all test data are shown in Figure 1d. Measurements on automatic segmentations have strong agreement with measurements on manual segmentations (ICC &gt; 0.95). Automatic segmentation results are insignificantly different from interobserver tracings (p &gt; 0.01), suggesting that a reliable AoR segmentation can be produced in inference time as little as 1-2 seconds per 3D volume (Figure 1e-g). Conclusions: The proposed deep learning method rapidly produces AoR segmentations and quantifications that are comparable to manual tracing. This framework can aid in population-based comparison of BAV and TAV roots and facilitate patient-specific AoR assessment for surgical planning. In the future, leaflet segmentations can be incorporated for analysis of the full aortic valve apparatus in TEE.
Abstract 4141883: The out-of-hospital cardiac arrest in patients with acute myocardial infarction and pre-existing aortic stenosis.
Authors: Tamilla Muzafarova, Zuzana Motovska, Ota Hlinomaz, Petr Kala, Milan Hromadka, Jan Mrozek, Marek Sramko, Martin Hutyra, Robert Petr, Teodora Vichova, Oana Ionita, Jiri Jarkovsky
Journal: Circulation (2024)

Background: Pre-existing significant aortic stenosis (sAS) in patients with out-of-hospital cardiac arrest (OHCA) may lead to ineffective chest compressions due to the pathophysiology and hemodynamics of stenosis, reducing the probability of return of spontaneous circulation, and the resuscitation may be complicated. Aim: To analyze the influence of sAS on the risk of OHCA in patients with acute myocardial infarction (AMI-OHCA), on the complicity of resuscitation and survival. Methods: The analysis was based on the national all-comers’ registry of coronary interventions enriched by information from the National Registry of Reimbursed Health Services and the Registry of Deaths. Complicity of resuscitation was defined as the necessity of mechanical ventilation up to hospital admission. The association between AS, patient characteristics and mortality was analyzed using logistic regression, multivariate model was used for adjusting for co-founders. Results: Our dataset included all patients with AMI-OHCA in the country in the period from 2017 to 2021 (N=4,414), of whom 1.8% (N=80) patients had pre-existing sAS and were followed up at the medical institutions (Table 1). The incidence of sAS was 1.7% in those who suffered OHCA and 1.8% in AMI patients without this complication, p=0.66 . The AMI-OHCA patients were divided into three groups – those who died during OHCA (N=238, sAS in 4.2%), those who were admitted after OHCA on mechanical ventilation (N=3,255, sAS in 1.8%), and spontaneously ventilating patients (N=921, sAS in 1.2%). Multivariate analysis showed that sAS was not recognized as a risk factor for the use of mechanical ventilation in AMI-OHCA patients, odds ratio (OR) 1.61 (95%CI 0.83;3.09), p=0.16, however sAS presents a significant risk of pre-hospital mortality of AMI-OHCA patients, multivariate OR 3.4 (95%CI 1.20;9.58), p= 0.02. Additionally, the in-hospital, 30-day, and long-term prognosis of AMI patients after OHCA is adversely affected by AS with odds ratio of 2.47 (95%CI 1.38;4.41), 2.83 (95%CI 1.61;4.95), and 1.81 (95%CI 1.38;2.38) vs. non-VHD respectively. Conclusion: Pre-existing sAS has a significant adverse influence on the survival of AMI-OHCA patients and is a significant risk factor of pre-hospital mortality. Therefore, patients with AS should be carefully screened for coronary artery disease, antithrombotic therapy should be considered, and the earlier planning of valvular intervention after AMI should be evaluated.
Abstract 4141779: Metabolomic Markers of Aortic Stenosis Development: the Atherosclerosis Risk in Communities (ARIC) Study
Authors: Khaled Shelbaya, Victoria Lamberson, Yimin Yang, peidi zhou, Taryn Alkis, Kuni Matsushita, Bing Yu, Amil Shah
Journal: Circulation (2024)

Background: Prior metabolomics studies in aortic stenosis (AS) have focused on patients with severe stenosis and their response to intervention. Limited data exist regarding circulating metabolites predictive of AS development. Aim: Identify circulating metabolites associated with aortic valve (AV) hemodynamics and incident AV events. Hypothesis: We hypothesized that large-scale metabolomics can identify novel circulating metabolites relevant to AS development. Methods: Among participants in the community-based ARIC cohort study who underwent protocol echocardiography and metabolomic profiling by chromatography mass spectrometry (Metabolon) at study Visit 5 (2011-2013) and were free of AV replacement, we related metabolite values to AV peak velocity (AVmax) and dimensionless index (DI) cross-sectionally and to incident AV events using multivariable linear and Cox regression models. Metabolites with ≤10% missingness (n=736 metabolites) were included and normalized using log2 transformation. Post-Visit 5 AV events were ascertained based on ICD codes for AV-related hospitalization and interventions. Regression models were adjusted for age, sex, race, center, heart rate, blood pressure, estimated glomerular filtration rate, and cardiovascular (CV) risk factors and diseases. Statistical significance was based on a False Discovery Rate (FDR) &lt;0.05. Results: Among 5,107 participants included, mean age was 75±5 years, 57% were women, and 18% reported Black race. Mean LVEF was 65 ±7%, AVmax 1.3 ±0.4 m/s, and DI 0.76 ±0.14. After adjusting for CV risk factors and disease, 80 metabolites were cross-sectionally associated with AVmax at FDR &lt;0.05, 28 of which were further associated with DI ( Figure A ). Over a median follow-up of 8 [Q1- Q3, 7-9] years, 245 experienced an AV-related hospitalization. Of the 28 metabolites associated with AV hemodynamics, 20 were associated with incident AV-related hospitalization ( Figure B ). Amino acids and amino sugar metabolites were associated with greater hemodynamic AV stenosis and a higher risk of AV events, while higher dicarboxylic fatty acids and other lipids values were associated with better AV hemodynamics and a lower risk of AV-related hospitalization ( Figure C ). Conclusion: Large-scale metabolomics in an older community-based cohort identifies novel circulating markers of AS risk. While amino acid metabolites associated with high risk, dicarboxylic fatty acids were associated with lower risk.
Abstract 4141861: Detecting Acute Ischemia Prior to Troponin-I Rise Using Hyper-Acute Native T1 Mapping with Ultrastructural Tissue Validation: Implications for Rapid Diagnosis of Non-ST-Elevation Myocardial Infarction
Authors: Shing Fai Chan, Ting Liu, Dhirendra Singh, Yuheng Huang, Hsin-jung Yang, Ghazal Yoosefian, Richard Tang, Andrew Howarth, Keyur Vora, Rohan Dharmakumar
Journal: Circulation (2024)

Background and Hypothesis: Early detection of acute ischemia in non-ST-elevation MI (NSTEMI+) patients is crucial for timely treatment. Traditional biomarkers like high sensitivity cardiac troponin-I level [hs-cTnI] can take hours after myocardial injury to rise in NSTEMI+ patients and potentially delay diagnosis and treatment. We hypothesized that hyper-acute native T1 mapping with cardiac MRI (CMR) can rapidly identify ongoing ischemia. We studied this in canine models of ischemia and then in patients suspected of NSTEMI+. Methods: We performed LAD coronary artery ligation inside a CMR system to induce no-flow ischemia in a canine model (n=18) and performed repeat T1 and T2 mapping every 5 min. We also biopsied myocardial tissue at baseline and at defined time points from ischemic and remote areas. We used transmission electron microscopy (TEM) to analyze cardiac ultrastructure. Patients suspected of NSTEMI+ (n=16) underwent native cine, T1, and T2 CMR 3T. Results: T1 values increased significantly from 1182±51ms (baseline) to 1265±56ms (5 to 10 min after onset of ischemia), p&lt;0.05; and continue to rise through 90 min (1327±56ms), while T2 values showed no significant changes over the first 90 min. TEM showed that the mitochondrial cristae density in ischemic zones was significantly decreased: 100±9.8%(baseline) vs 54±4.4% (5 min of ischemia), p&lt;0.01, and decline to 40.6±9.8% by 90 min. After 5 min of ischemia, both mitochondrial width and circuity index showed no difference compared to baseline, but both paraments increased significantly: (a) mitochondrial width: 990.4±118.6nm (15 min of ischemia) vs 577±61nm (baseline), p&lt;0.01; (b) circuity index: 0.87±0.04 (15 min of ischemia) vs 0.8±0.04 (baseline), p&lt;0.01, and continued to rise and persist at high levels at 90 min: 1091±148 nm (mitochondrial width) and 0.94±0.01 (circuity index), respectively. Cristae number was significantly reduced 13.8±2.7 (baseline) vs 24.4±2.9 (5 min of ischemia), p&lt;0.01, and remained low and reduced to 7.6±1.8 by 90 min. ΔT1 value in patients were significantly higher in NSTEMI+ than in NSTEMI- (11.51±3.7% vs 2.06±1.7%, p&lt;0.0001), while [hs-cTnI] levels from NSTEMI+ gradually increased over time and were only significantly higher than NSTEMI-, several hours after CMR and peaked at 24 h (12.6±7.3% (24 h) vs 0.03±0.02% (baseline), p&lt;0.05). Conclusions: Hyper-acute native T1 mapping has the potential to rapidly identify ongoing ischemia even in the absence of troponin-I rise.
Abstract 4141807: Exposure to PM2.5 and 1-year postoperative risk of death among patients with congenital heart surgery: a report from the Pediatric Cardiac Care Consortium
Authors: Yanxu Yang, Ke Xu, Hua Hao, Eugene Huang, Yang Liu, Lazaros Kochilas
Journal: Circulation (2024)

Background: Congenital heart disease (CHD) is the leading cause of birth defect-related deaths among infants in the US. While ambient particulate matter (PM) PM2.5 is a known cardiovascular risk factor, its effect on CHD patients remains unclear. This study examines the link between county-level PM2.5 and 1-year mortality risk following pediatric congenital heart surgery (CHS). Methods: We conducted a retrospective cohort study using data from the Pediatric Cardiac Care Consortium (PCCC), a large US-based multi-institutional registry of interventions for CHD. We included patients with available identifiers, initial CHS, county information and birth between 1989 and 2003. We obtained sex, birth year, CHD severity, chromosomal abnormality and neighborhood socioeconomic status (nSES). PM2.5 concentrations at 1-km resolution across the US were derived using spatiotemporal ensemble models integrating machine learning algorithms. The data were assigned to county-level scale by geo-information provided by the US Census Bureau. We used Cox proportional hazards regression with shared frailty models to estimate the hazard of death considering state as a random effect. Results: We included a total of 27,327 patients who were enrolled in PCCC after an initial CHS (47.3% females). Patients exposed to higher PM2.5 quintile were more likely to be born in early birth era (1990-1993) (p&lt;0.01) and at low nSES (p&lt;0.01). After adjusting for sex, birth era, CHD severity, chromosomal abnormality and nSES, the hazard of death in patients exposed to the highest vs lowest PM2.5 quintile was 1.33 (95%CI: 1.02-1.72, p=0.03). In addition, there was a linear dose-response relationship between PM2.5 exposure and 1-year mortality risk (P non-linearity =0.90) with each 1 μg/m 3 increase in monthly PM2.5 exposure associated with 2% increase in the 1-year post-discharge hazard of death (aHR: 1.02, 95%CI: 1.00-1.04, p=0.05) (Figure). Conclusion: Higher PM2.5 levels were independently associated with increased risk of death after pediatric CHS. Improving environmental conditions may mitigate the adverse health effects of particulate matter exposure for patients with CHD.
Abstract 4141869: Effects of Compliant Chest Compression Rate on Return of Spontaneous Circulation in In-Hospital-Cardiac-Arrest
Authors: Janel Atkins, Julia Reynolds, David Pearson
Journal: Circulation (2024)

Introduction: Over 290,000 in-hospital cardiac arrests occur annually in the United States. Survival is about 25% with significant variation across the country. Evidence supports high-quality chest compressions as a vital factor to achieving return of spontaneous circulation (ROSC) and improving outcomes after cardiac arrest. Research illustrates a propensity for healthcare professionals to provide chest compressions at a rate outside the American Heart Association guideline of 100-120 compressions/minute. Goal/Hypothesis: The team hypothesized greater compliance with chest compression rate guidelines would increase ROSC. The goal of this initiative was to increase CC rate compliance from a facility baseline of 15-64% toward the published benchmark of 80%, and to positively impact ROSC. Method: An interdisciplinary team focused on optimizing CC rate compliance. The Plan, Do, Study, Act methodology provided structure and a systematic approach to data informed improvements. Rate data was collected, then shared on a Power BI dashboard and in a facility specific report. The impact of the awareness campaign was assessed at the end of each quarterly cycle for 9 facilities. Results/Outcomes: Data for 2023 included 487 code events and 6,315 minutes of CPR. At year end, improvements were found at 5 facilities (12, 12, 14, 17,&amp;7%) over baseline, and 2 facilities achieved the benchmark. Statistical analysis was conducted to evaluate CC rate compliance in correlation with ROSC. Cases were sorted into 2 groups: Group 1 (compliance 80% or greater) or Group 2 (compliance less than 31.6% - calculated first quartile). Three hundred two cases met inclusion criteria. Cochran’s formula was used (95% CI) to calculate sample size (Group 1:111 cases; Group 2:107cases). A Chi-squared test showed a significant difference in achieving ROSC between the groups (p=0.0223). Group 1 achieved ROSC 20% more frequently than Group 2. Conclusions: Chest compression rate compliance was positively associated with improved rate of ROSC in this project. Project findings prompted the system resuscitation committee to require facilities to set a goal for CC rate compliance improvement. Improvement can be achieved without financial or educational burden. Other performance-based quality metrics to improve clinical outcomes should be included in future research with consideration of co-morbidities.
Abstract 4141896: Genetic Mimics of GLP-1Ra and SGLT2i Therapy, Heart Failure and Chronic Kidney Disease Outcomes
Authors: Subbaramireddy Remala, Liming Liang, Amil Shah, Leo Buckley
Journal: Circulation (2024)

Background: GLP-1 receptor agonists (GLP-1Ra) prevent atherosclerotic and chronic kidney disease (CKD) progression events in type 2 diabetes. In obesity without diabetes, GLP-1Ra lower the risk of atherosclerotic cardiovascular events. Less is known about the effects of GLP-1Ra on heart failure (HF) events and CKD progression events in people without type 2 diabetes and the benefits of adding GLP-1Ra to standard-of-care SGLT2 inhibitor therapy. Objective: Assess the association between genetic mimics of GLP1-Ra and SGLT2 inhibitor therapy on the risk of coronary artery disease (CAD), HF, and CKD. Methods: We used whole exome sequencing data from the All of Us Research Program to construct genetic instruments mimicking GLP1-Ra and SGLT2i therapy. The genetic instruments included variants in the GLP1R and SLC5A2 genes that associated with lower hemoglobin A1c levels in elastic net regression models with linkage disequilibrium pruning (r 2 &lt; 0.3). Thus, higher genetic scores mimicked lifelong treatment with a GLP-1Ra or SGLT2 inhibitor. Having both higher GLP-1Ra and higher SGLT2i genetic scores mimicked lifelong exposure to combined therapy ( Figure ). Results: We included 245,388 All of Us participants (mean age 55 years, 59% females, 38% males, and 2% other genders). Higher GLP-1Ra genetic scores associated with a lower risk of CAD (OR [95% CI] per 1-standard deviation [SD]: 0.97 [0.95-0.99]; P=0.004), HF (OR [95% CI] per 1-SD: 0.95 [0.93-0.98]; P&lt;0.001) and CKD (OR [95% CI] per 1-SD: 0.95 [0.93-0.97]; P&lt;0.001). The associations between the GLP-1Ra genetic score and HF and CKD were not modified by the SGLT2 inhibitor genetic score ( Figure ). Conclusion: Lifelong exposure to genetic variants mimicking the pharmacologic effects of GLP1-Ra is associated with a lower risk of CAD, HF, and CKD. GLP-1Ra may provide cardio-kidney protection beyond SGLT2i alone. These results also suggest that GLP-1Ra may prevent new-onset CAD, HF and CKD in the general population.
Abstract 4141889: Shifting trends and study characteristics associated with randomization, blinding, and data monitoring committee oversight of cardiovascular trials: analysis of ClinicalTrials.gov listings from 2000 to 2023
Authors: Gerald Chi, Maria Bahit, Alberto Castro Molina, Serge Korjian, Clara Vitarello, Paul Nara, Alka Shaunik, Charles Gibson
Journal: Circulation (2024)

Background: In response to concerns regarding insufficient transparency and selective reporting, the International Committee of Medical Journal Editors (ICMJE) issued a statement in 2004 mandating the registration of all clinical trials in a publicly accessible repository. Its impact on the trend of cardiovascular (CV) trial has not been comprehensively examined. The relationship between trial characteristics and designs aimed at enhancing methodological rigor and scientific validity, such as the implementation of randomization, blinding, and a data monitoring committee (DMC), remains unclear. Methods: The analysis included studies that: (1) were registered in ClinicalTrials.gov between 2000 and 2023; (2) involved ≥1 intervention; and (3) investigated ≥1 CV condition. Interrupted time-series analysis was performed to assess the impact of the ICMJE policy on the annual trend of trial registration. Multivariable logistic regression was conducted to assess the association between study characteristics and randomization, blinding, or DMC oversight. Results: A total of 38,262 CV trials were identified from 473,593 records. Prior to the implementation of ICMJE policy, the number of new CV trials increased by 10.9 (95% confidence interval [CI]: 1.5 to 20.3) every year. Following the implementation, the ascending trend intensified significantly (p&lt;0.001), with a rate of 92.6 (95% CI: 60.6 to 124.5) new CV trials per year (Figure 1). Randomization and blinding were more commonly adopted in preventive trials, trials involving behavioral or dietary interventions, and phase 3 trials (Figure 2). In contrast, diagnostic trials and trials related to devices or procedures were less likely to include randomization or blinding in their design. More recent trials were less likely to implement randomization but more likely to implement blinding than earlier trials. DMC oversight was less prevalent in diagnostic trials, trials involving behavioral or dietary interventions, and non-phase 3 trials. Trials supported by the industry were less inclined to employ randomization, blinding, or DMC oversight. Study size was not correlated with any of these designs. Conclusion: The upward trend of CV trial registration augmented following the implementation of the ICMJE policy. Implementation of randomization, blinding, and DMC oversight was associated with study purpose, intervention, phase, funding source, and start year, with no discernible variation by study size.