tbuckley/cabot-search huggingface dataset:
Abstract 15632: Warfarin Dose Management Using Offline Deep Reinforcement Learning
Authors: Hannah Ji, Matthew F Gill, Evan W Draper, David A Liedl, David O Hodge, Damon E Houghton, Ana I Casanegra
Journal: Circulation (2023)

Introduction: Warfarin is a commonly prescribed anticoagulant for treating atrial fibrillation, mechanical valves, and venous thromboembolism. Warfarin dose management remains challenging due to dosing variability between patients and warfarin’s narrow therapeutic window. Time in therapeutic range (TTR) is critical to warfarin’s safety and efficacy, but TTR typically remains low (40-50%) in community practices. Specialized anticoagulation clinics and protocolized approaches can increase TTR but have great administrative burdens and health care costs. Aim: To develop standardized optimal warfarin dose decision support using a machine learning model based on time series anticoagulation data and patient demographic characteristics Methods: The dataset included 12,497 warfarin patients monitored in the anticoagulation tracker of electronic medical records across the Mayo Clinic Enterprise. The dataset contained time series anticoagulation data (warfarin dose, INR, INR target range) and patient demographic characteristics. We implemented an offline deep reinforcement learning model (DRL) to predict the cumulative warfarin dose for the days until the next INR test based on a patient’s historical anticoagulation data. Prior approaches utilized traditional supervised learning methods such as regression or Long Short Term Memory (LSTM) neural networks to approximate a function mimicking the behavior of the training data. On the other hand, DRL learned an optimal dosing policy through continuous interaction and feedback from the training data. The key advantage of DRL is the model can learn to behave differently (and potentially better) for suboptimal clinical states in the data such as overdosing or underdosing. To evaluate the DRL model we compared the predicted warfarin doses with the physician-prescribed doses Results: DRL model’s prediction accuracy was 96.96%, outperforming our implementation of a baseline LSTM model with a prediction accuracy of 70.58%. Further evaluation of the DRL model indicated that the model correctly adjusted the warfarin dose at time steps when patients had out-of-range INRs. Conclusions: Offline deep reinforcement learning demonstrates potential in supporting warfarin dose management to maximize TTR.
Abstract 19031: Leveraging Electronic Health Records to Examine Blood Pressure Patterns Preceding Stroke Events
Authors: Dana Lee, Aishwarya Nene, Yuntian Liu, Yuan Lu, Erica S Spatz
Journal: Circulation (2023)

Introduction: Hypertension (HTN) is the primary modifiable risk factor for stroke, with blood pressure (BP) control being paramount. Yet only one-fourth of patients with HTN who are receiving medical care have controlled BP. Accordingly, we aimed to elucidate patterns of BP control prior to incident stroke. Methods: We analyzed electronic health record data from patients who were hospitalized for a first stroke within the Yale New Haven Health system between 2015 and 2021. Patients were included if they had ≥2 outpatient visits in the 2 years prior to stroke to capture those regularly seeking care. BP measurements for all ambulatory visits were extracted. Systolic BP (SBP) and diastolic BP (DBP) were categorized as the number of BP measurements that were elevated (SBP &gt;140mmHg or DBP &gt;90mmHg), moderately elevated (SBP &gt;160mmHg or DBP &gt;100mmHg), and severely elevated (SBP &gt;180mmHg or DBP &gt;120mmHg), and by age group, sex, race and ethnicity. Results: Among 6,047 patients with a first stroke, the mean age was 72 years, SD= 15; 52% were female; 17% were Black/African American; and 8% were Hispanic/Latino. Table 1 displays the proportion of patients with ≥2, ≥3, ≥ 4, and ≥5 BP measurements by category of BP elevation. Patients who were aged 55-64 years, of Black/African American race, and of Hispanic/Latino ethnicity were more likely to have severely elevated BP than their relative subgroups, with Black/African American patients having the highest proportion of BP elevation across all categories compared to other racial/ethnic groups. Conclusion: Despite receiving regular medical care, 75% of patients had ≥2 BP measurements &gt;140/90mmHg in the 2 years prior to stroke; over 1 in 5 patients had &gt;2 BP measurements ≥160/100mmHg. BP patterns were most elevated among middle-aged and Black/African American patients. New approaches are urgently needed to control BP and prevent stroke.
Abstract 13650: Trends in Women Cardiac Operators of Structural and Interventional Procedures in the United States
Authors: Sowmya Dandu, Hira Akhlaq, Steven Imburgio, Helen Pozdniakova, Ndausung Udongwo, Anton Mararenko, Sherif Eltawansy, ARIF ASIF, Palak Patel, Beverly Demchuk, Daniel Kiss, Jesus Almendral, Joseph Heaton
Journal: Circulation (2023)

Background: Women have historically been underrepresented in cardiology workforces. Throughout the United States, there is a major underrepresentation of women in cardiology as operators within structural proceduralists and interventional cardiology (IC). Methods: We extracted data from the Medicare Provider Utilization and Payment Database (MPUPD) from 2013 to 2020. The MPUPD is an administrative database of services rendered to Medicare patients enrolled in a fee-for-service program. We sought operators who performed &gt;10 procedures using procedure codes for percutaneous transcatheter closure of congenital atrial septal defect (ASD) with implant and percutaneous coronary intervention, transcatheter mitral valve replacement via transcutaneous edge to edge repairs (TEER), and percutaneous left atrial appendage closure (PLAAO) using relevant CPT codes. The proportion of women operators was analyzed across the 8-year period. Results: Between 2013 and 2020, women on average represented 3.02% of the 1,260 cardiac operators identified. Despite the number of total structural operators performing 10 or more procedures increasing from 9 to 871 over the 8-year period, the proportion of women remained unchanged at less than 4.5% (P = 0.712) (Figure 1). By procedure, the total ASD, TEER, and PLAAO operators have increased, though the proportion of women operators remained constant over time (P = .913, .725 and .891). Over the studied period, there were no women operators identified with over 10 operations in 28 states (56%) for any structural procedures, 49 states (98%) for ASD procedures, 39 states (78%) for TEER, and 33 states (66%) of PLAAO. Conclusion: Women continue to represent an overwhelming minority of structural cardiac operators. Despite a rapid rise in the total number of operators, the proportion of female operators has not increased. Prospective studies are needed to investigate the underlying factors contributing to these sex-related differences.
Abstract 18827: Emergency Department Threat Perceptions and PTSD Symptoms After Suspected Stroke
Authors: Sitara P Kumar, Adriana Wu Clark, Victor Jerez, Julia Ellis, Charles Keys McKay, Jennifer Aguirre, Margaret E Murdock, Keith M Diaz, Ian M Kronish
Journal: Circulation (2023)

Introduction: Stroke is a leading cause of death, physical, and psychological disability in the United States. One in four stroke survivors develop significant PTSD symptoms (PTSS), which can influence disease outcomes. It is important to identify factors that increase early psychological distress and subsequent PTSS development, such as threat perceptions in the emergency department (ED). Understanding the relationship between ED threat and PTSS may help identify areas for improving early stroke care. The purpose of this study was to determine whether ED threat perceptions influence PTSS development at 1-, 6- and 12-months after suspected stroke. Methods: The sample consisted of patients (n = 203, 48% female, 59.4 ± 15.5 years) who presented to the ED of an academic medical center for suspected stroke. ED threat was assessed in-hospital using the ED Threat Perceptions questionnaire, and PTSS were assessed at 1-, 6- and 12- months post-stroke using the PCL-5 tool. Linear regression was used to assess the association between ED threat and PTSD symptoms, adjusting for demographics, depression, chronic disease severity (Charlson index), and stroke severity (NIHSS). Results: In unadjusted analyses, ED threat perceptions were associated with higher PTSS at 1- (β=0.42, 95% CI [0.16-0.68] p=0.002), 6- (β=0.32, 95% CI [0.07-0.58], p=0.013), and 12-mo (β=0.44, 95% CI [0.15-0.72], p=0.003), independent of demographics, stroke severity, and depressive symptoms when expressed continuously. In nested models, addition of ED threat perceptions to a model including demographics and stroke severity significantly improved the model (Δ-2 log likelihood = 7.15, df=1; p=0.007), indicating independent effects in the association of ED threat perceptions with PTSD symptoms beyond stroke severity. Conclusions: ED threat perceptions were associated with higher PTSS at 1-, 6-, and 12-months after suspected stroke even after accounting for clinician-measured stroke severity. This suggests that early threat perceptions contribute to PTSD risk above and beyond the physical impact of the event. These results indicate the importance of the ED environment and provide a target for future interventions to minimize the development of PTSD symptoms post-stroke.
Abstract 179: Reversal of Clinical Death by Intra-Arterial Infusion of Phospholipid Nanoparticles (VBI-1)
Authors: Stephen Mishriky, Philemon Shallie, Prashanth Anamthathmakula, Cuthbert Simpkins
Journal: Circulation (2023)

Introduction: Ninety percent of deaths from potentially survivable injuries on the battlefield are attributed to hemorrhagic shock, leading to clinical death (CD) with the loss of pulse and respiratory drive before reaching a surgeon. However, currently available fluids are inadequate for rescuing warfighters who have experienced exsanguination. Furthermore, these fluids have the potential to cause reperfusion injury in vital organs. We developed a rat model of CD to evaluate the effectiveness of two phospholipid nanoparticle formulations (VBI-1, VBI-S) and compared intra-arterial (IA) versus intravenous (IV) infusion on resuscitation. Hypothesis: We hypothesized that the nanoparticles would restore breathing and blood pressure (BP) in rats after CD induced by hemorrhagic shock. Goals: To establish a model that reliably restores breathing and maintains a survivable BP for 240 minutes after CD. Methods: Male and female Sprague Dawley rats were divided into four groups (n=6-7). The rats were anesthetized with isoflurane, followed by cannulation of femoral arteries. Blood was withdrawn over two minutes until respiration ceased. Equal volumes of either Ringer’s Lactate (LR), shed blood, VBI-1, or VBI-S were infused over one minute, with continuous monitoring of BP. Results: Loss of respiration occurred with blood withdrawal ranging from 39.8% to 43.2% of the predicted total blood volume. Post-IA infusion, the survival rates of the four groups for 240 minutes were as follows: 100% with VBI-1 (n=6), 83.3% with blood (n=7), 66.7% with VBI-S (n=6), and 0% with LR (n=6). Two-way ANOVA analysis revealed a significant difference in mean arterial pressure (MAP) among the four fluids (p=0.0004). Post-hoc analysis indicated the fluid responsiveness in elevating MAP as follows: VBI-1 &gt; VBI-S = shed blood &gt; LR. Regarding the VBI-1 infusion routes, the IA infusion demonstrated 100% survival (n=6) compared to the IV infusion with 40% (n=6) survival. Conclusion: VBI-1 outperformed all other fluids, including blood, in achieving reanimation and elevating MAP. IA infusion of VBI-1 demonstrated a higher reanimation rate compared to IV infusion. Based on these findings, VBI-1 is a promising new treatment for CD due to severe hemorrhagic shock; potentially saving lives.
Abstract 14831: Low Positive Social Determinants of Health Exposure Amplifies the Association Between Allostatic Load and Risk of Cardiovascular Mortality in Cancer and Non-Cancer Patients
Authors: Aditya Bhave, Ritu Reddy, Justin Moore, Priyanshu Nain, Biplab Datta, Darryl Nettles, Lakshya Seth, Stephanie Jiang, Vraj Patel, Sarah Malik, Neal L Weintraub, Sadeer Al-Kindi, Sarju Ganatra, Sourbha Dani, Javier Gomez Valencia, Xiaoling Wang, Avirup Guha
Journal: Circulation (2023)

Introduction: Allostatic load (AL) is a measure of the biological “wear and tear” or physiological effects of chronic toxic stress exposure and the body’s adaptive responses over time. High AL is associated with an increased risk of death from cardiovascular disease and cancer. Hypothesis: We examined Positive Social Determinants of Health (PSDOH) exposure as a moderator for the effect of AL on the risk of cardiovascular-related death (CVD) among adults with and without a history of cancer. Methods: We conducted a retrospective cohort analysis of the National Health and Nutrition Examination Survey (NHANES) years 1999 through 2010 linked and followed up with the National Death Index through December 31, 2019. We fit age, race, and sex-adjusted Fine &amp; Gray models to calculate sub-distribution hazard ratios (SHR) of CVD among adults exposed to high versus low levels of PSDOH, stratified by high and low AL status. AL was calculated using a nine-point score previously defined in NHANES literature that uses a combination of serum biomarkers as well as body mass index and blood pressure. PSDOH was calculated using a seven-point score previously defined in NHANES literature examining positive exposures of home ownership, health insurance, educational attainment greater than high school, food security, being above the federal poverty level, health care access, and living with a partner. Results: Among 22,775 eligible participants in this study, 1,939 (8.5%) had a history of cancer. In the full cohort, age, race, and sex-adjusted models found that low PSDOH exposure was associated with a 38% increased risk of CVD among high AL adults (SHR: 1.38, 95% CI: 1.22 - 1.56) and a 57% increased risk among low AL adults (SHR: 1.57, 95% CI: 1.32 - 1.87). Cancer history-stratified adjusted models are presented in Table 1. Conclusions: Low PSDOH exposure amplified the association between AL and CVD in all cohorts, with the highest increases in risk being seen among adults with a history of cancer.
Abstract 15088: Presence and Severity of Subclinical Atherosclerotic Disease in the Primary Prevention of the Oncologic Population
Authors: Sara Diaz Saravia, Sergio Gonzalez, Maria Brenzoni, Pamela Alarcon, Fabian Ferroni, Carlos E Castellaro, Jorge A Chiabaut, Renzo Melchiori
Journal: Circulation (2023)

Introduction: There is scarce evidence about endothelial dysfunction and damage in patients with a history of cancer in cardiovascular primary prevention and the impact in the development of Subclinical Atherosclerotic Disease (SCAD). Methods: A cross-sectional study was carried out on a registry of patients enrolled in primary prevention who had a Doppler ultrasound (DUS) screening for SCAD in the carotid and ileofemoral territory from 09/2020 to 04/2023. Inclusion criteria: 18 years old or older. Exclusion criteria: Previous cardiovascular and/or cerebrovascular event. History of cancer was defined as active or remitted cancer, excluding basal cell and squamous cell carcinoma. Population was divided in two, G1: non-oncologic group; G2 oncologic group. SCAD was defined as the presence of more than 1 atherosclerotic plaque in the carotid and/or ileofemoral territory. Univariate and bivariate analysis were done to establish population characteristics. Results: A total of 7920 patients were included: 7694 in G1 and 226 in G2 (97.15% vs 2.85%). G2 patients were older, mostly women and had higher prevalence of hypertension and dyslipidemia. Clinical characteristics and findings of the DUS are shown in Table1. A linear regression was done to assess the total plaque area compared to oncologic history, adjusted for age, sex, smoking history, dyslipidemia, obesity, sedentarism, diabetes, and hypertension. Results show that history of cancer is a predictor for SCAD (OR=1.43 [IC 95%: 1.1-1.9], p=0.021). Cancer also seems to be associated with a higher number of territories affected by SCAD (OR=1.63 [IC 95%: 1.2-2.1], 0.001) adjusted for age, sex, tobacco use, obesity, dyslipidemia, diabetes, sedentarism, and hypertension. Conclusions: Patients with history of cancer had more SCAD. Cancer behaved as a predisposing factor for increased plaque presence and area, adjusted for classic risk factors. This raises the need for more intensive control of SCAD in cancer patients.
Abstract 14932: Prediction of Pulmonary Embolism Using Random Forest Algorithm: A Study on 917 Patients Over a Period of 1 Year in a New York City Public Hospital
Authors: Amrin M Kharawala, Dimitrios Varrias, Sanjana Nagraj, Dimitrios Karamanis, Jiyoung Seo, Charan Thej Reddy Vegivinti, Diego Barzallo, Gabriel Hernandez Romero, Yunus Emre Demirhan, Prasanth Balasubramanian, Gustavo Duarte, Manuel Hache-Marliere, Heitor Tavares Santos, Majd Al Deen Alhuarrat, ISRAEL SAFIRIYU, Damianos Kokkinidis, Michail Spanos, Leonidas Palaiodimos
Journal: Circulation (2023)

Introduction: Pulmonary Embolism (PE) can be challenging to diagnose. Artificial intelligence (AI)-generated models can help improve the diagnostic accuracy of detecting PE. Aim: Establish the diagnostic accuracy of AI-generated models in predicting PE as compared to routinely used diagnostic predictive tools (Well’s score, YEARS score, and revised Geneva score). Methods: We conducted a single-center retrospective review of patients who underwent computed tomography pulmonary angiography (CTPA) for diagnosing PE over a one-year period. Twenty-five parameters including age, sex, race, BMI, history of deep vein thrombosis or PE, malignancy, hypertension, COPD, CKD, presenting symptoms like chest pain, dyspnea, cough, palpitations, dizziness, lightheadedness/syncope, hemoptysis, fever, pain on palpation of the lower extremity, vitals including heart rate, respiratory rate, oxygen saturation, findings of lower extremity venous duplex, presence of right ventricular dysfunction on echocardiogram, elevated troponin and pro-brain natriuretic peptide were utilized to train the AI model. Random forest algorithms were trained for predicting PE in 80% of the dataset, while the remaining 20% was used to test the AI model. Subsequently, the accuracy of the model was matched with the accuracy of four alternative modalities: clinical judgment of PE being equally or more likely, Well’s score &gt;4, YEARS score ≥1, and revised Geneva score ≥11. CTPA results were used as the gold standard. Analysis was performed using STATA BE/17 and Python 3.8. Results: 917 patients were included in the analysis (median age: 57 years (IQR: 41-68); female: 59%). The AI model correctly classified patients with 84.6% diagnostic accuracy, outperforming every other modality (Figure 1). Conclusion: AI-generated prediction models can be useful in predicting PE with considerable accuracy. Further, large-scale studies are required to validate these results externally.
Abstract 14527: AI-ECG is a Cost-Effective Early Screening Tool for Heart Failure With Reduced Ejection Fraction
Authors: Colin Pawlowski, Matthew Sobiesk, Lars Hegstrom, John Rincon-Hekking, Francisco Lopez-Jimenez, Suraj Kapa, Zachi Attia, Paul Friedman, Sankar Ardhanari, Rakesh Barve, Venky Soundararajan, Samir Awasthi
Journal: Circulation (2023)

Background: Early diagnosis of heart failure with reduced ejection fraction (HFrEF) can lead to reduced healthcare costs and improved outcomes. In this study, we evaluated the economic effectiveness of an AI algorithm for detecting low ejection fraction using 12-lead ECG data. Aims: The primary aim was to estimate the health economic impact of the AI-ECG algorithm intervention to detect low ejection fraction. Methods: The study population consisted of 113,719 individuals without a prior history of HFrEF who visited a multistate health system between 2010-2018 with 12-lead ECG data and an echocardiogram within 1 year. The AI-ECG algorithm was run retrospectively, and projected costs were estimated assuming each patient incurred the average cost based on their age group and AI-detected heart failure stage. Hospitalization costs were estimated using Medicare reimbursement rates, and economic benefits from increased survival were estimated using a willingness to pay of $50,000 per quality-adjusted life year (QALY) gained. Results: At the optimal model threshold, the total cost savings per patient (including benefits from QALYs gained) for the AI-ECG algorithm vs. standard-of-care on the overall study population were projected to be $79.11 (95% CI: [$53.77, $104.44]) and $124.93 (95% CI: [$83.99, $165.88]) for the 2 and 4 year periods, respectively. For patients over 50 years old, the projected total cost savings were $85.56 (95% CI: [$56.35, $114.78]) and $135.28 (95% CI: [$88.18, $182.38]) per patient for the 2 and 4 year periods, respectively. See Figure. Conclusions: The AI-ECG algorithm to detect low ejection fraction is a cost-effective early screening tool for HFrEF.
Abstract 185: Regional Oxygen Saturation and Capnography Monitoring During Resuscitation After Cardiac Arrest in a Swine Pediatric ARDS Model
Authors: Awni Al-subu, Rudolf K Braun, Ava Staehler, Kaisa Q Stolen, Allison Rodgers, Timothy A Hacker, Jens Eickhoff, Vinay M Nadkarni, Marlowe Eldridge
Journal: Circulation (2023)

Introduction: Survival and outcomes after cardiac arrest (CA) depend largely on the effectiveness of cardiopulmonary resuscitation (CPR). Traditional invasive methods of monitoring CPR can be challenging out-of-hospital and are lacking in more than 50% of in-hospital pediatric CA. Regional oxygen saturation (rSO 2 ) monitoring with Near Infrared Spectroscopy (NIRS) and volumetric capnography offers a noninvasive approach that could potentially overcome these challenges. Aim: To determine the feasibility and effectiveness of NIRS and volumetric capnography monitoring in a swine model of pediatric hypoxia induced CA. Approach: Juvenile pigs were sedated and mechanically ventilated. Mild to moderate Acute Respiratory Distress Syndrome (ARDS) was induced by continuous oleic acid infusion. Respiratory and hemodynamic variables were monitored using invasive and noninvasive (NIRS and capnography) monitoring to assess efficacy of CPR. Animals were randomized into one of the two groups: High-quality CPR (hqCPR) to achieve coronary perfusion pressure of 25-30 mmHg and low-quality CPR (lqCPR) to achieve coronary perfusion pressure of 10-15 mmHg. Trajectories over time were analyzed using regression analyses. The discriminatory ability to distinguish between groups based on trajectories were analyzed using receiver operating characteristics curve (ROC) analysis. Results: 39 animals (23±3 kg) were included in our study. In the hqCPR group, there are generally higher values for cerebral and renal rSO 2 , ETCO 2 , volume of CO 2 elimination (VCO 2 ), and carotid blood flow, compared to the lqCPR group (p&lt;0.0001). Cerebral and renal rSO 2 values increase over time, while ETCO 2 , VCO 2 , and carotid flow values decrease in the hqCPR group. Cerebral rSO2 had a ROC AUC of 0.76 (95% CI: 0.58-0.94), whereas renal rSO2 had a ROC AUC of 0.54 (95% CI: 0.22-0.87) representing nearly no discrimination ability. ETCO 2 had a ROC AUC of 0.66 (95% CI: 0.49-0.84), whereas VCO 2 had a ROC AUC of 0.62 (95% CI: 0.38-0.85). Conclusions: Higher mean cerebral rSO2 values during CPR might be used to assess quality of CPR effectiveness and provide real-time adjustments as needed. This could guide healthcare providers in optimizing CPR quality and improving outcomes for cardiac arrest patients.