tbuckley/cabot-search huggingface dataset:
Abstract 16844: Identifying Splenic Radiomics Features Associated With Risk of Coronary Artery Disease
Authors: Meghana Kamineni, Zhi Yu, Vineet Raghu, Ahmed M Alaa, Art Schuermans, Sam F Friedman, Christopher Reeder, Patrick T Ellinor, Mahnaz Maddah, Anthony A Philippakis, Whitney Hornsby, Pradeep Natarajan
Journal: Circulation (2023)

Introduction: Inflammation is a validated mechanism for residual coronary artery disease (CAD) risk via clinical trials and analysis of germline and somatic genetic variation in blood cells. While the spleen plays an important role in regulating inflammation, the role it plays in CAD is unclear. Hypothesis: We aim to test the hypothesis that radiographic splenic biomarkers may offer novel insights for CAD. Methods: We used deep learning to segment spleens from the abdominal MRIs of 38,474 patients in the UK Biobank. CAD was defined as history of coronary artery bypass grafting, myocardial infarction (MI), coronary artery angioplasty, or billing codes (OPCS-4: K40, K41, K45, K49, K50.2, K75). We extracted image features using the pyradiomics package. To identify image features associated with CAD, we used L1-regularized logistic regression models with the splenic features and clinical features used in the Pooled Cohort Equations (PCE) for outcomes of CAD and cardiovascular disease (CVD) events (defined as a composite of CAD, MI, and stroke outcomes). We computed the area under the receiver operating characteristic (AUROC) on a held-out 30% of the patient population and determined 95% confidence intervals using 1,000 Monte-Carlo resampled bootstraps. Results: Study participants had mean (SD) age 55.1 (7.5) years, 19,921 (51.8%) were women, 1,412 (3.7%) had CAD, and 2,473 (6.4%) had CVD events. The model to predict CAD using the splenic and PCE features had an AUROC of 0.84 (95% CI, 0.84-0.85), and 3 out of 10 significant covariates were splenic features. 1-SD increases in sphericity, minor axis length, and entropy in neighboring voxel gray levels were associated with 5.4% (95% CI, 5.1-5.7) higher, 13.3% (95% CI, 13.0-13.6) lower, and 10.5% (95% CI, 10.2-10.8) higher odds of CAD after adjustment. Results were consistent in the model to predict CVD events, and decreased minor axis length and increased texture variation were associated with increased risk. Model performance was lower for older age groups, who had higher incidences of CAD. Conclusions: This study leverages deep-learning methods across a population based cohort to highlight splenic features correlated with CAD and offers new opportunities to understand the role of the hematopoietic system in CAD.
Abstract 16357: Reducing Repeat Transthoracic Echocardiograms in the Inpatient Setting
Authors: Shannon Anderson, Rebecca Engels, Ken Lee, Stacie Richardson, Andrew Gagel, Allison Hays, Nisha A Gilotra, Amit Pahwa
Journal: Circulation (2023)

Background: Transthoracic echocardiogram (TTE) is a common cardiovascular imaging test for hospitalized patients. Repeat TTE testing, defined as a TTE done within one year of a prior TTE, contribute to high resource utilization without clear impact on changes in management. Hypothesis: An interruptive electronic medical record (EMR) alert deployed for repeat TTEs will decrease TTE overordering and will help elucidate reasons behind TTE ordering practices. Methods: We created an interruptive EMR alert for five hospitals within the Johns Hopkins Health System (JHHS). The alert was triggered when an inpatient TTE was ordered for non-ICU/non-cardiology service patients with a completed TTE within the prior 90 days. The alert displayed most recent TTE results and prompted the clinician to continue with the order or not. If order continuation was selected a free text clinician reason was required. Outcomes were length of stay (LOS) and reduction in repeat TTE orders. Focus groups were held with internal medicine residents to understand practice behaviors, given this was a leading cohort that continued with orders. Results: From July 2021- July 2022 the alert triggered 4,976 times, of these 32% of orders were discontinued while 68% were continued. There was no significant reduction in repeat TTE order attempts per month. More orders were continued at academic hospitals compared to the community setting (71% vs 63%, p=&lt;0.01). Medicine and non-medicine departments continued the order at similar rates (69% and 67%, p=0.12). Patients who had a repeat TTE had a longer average LOS compared to those who did not (14 vs 11 days, p=0.08). Twenty internal medicine residents were interviewed for focus groups. Top reasons for order continuation were a change in clinical status (n=8), worsening of chronic conditions (n=5), and post procedure monitoring (n=3). Majority (70%) requested more education within the alert to guide indications for repeat TTE ordering. Conclusion: EMR alerts can reduce repeat TTEs without increasing LOS, however knowledge gaps persist for ordering providers. Iterative changes to our health system EMR alert with a focus on best practice guideline incorporation and education may better mitigate overordering, and thus acute care utilization, in the future.
Abstract 15685: Artificial Intelligence Analysis of Facial Photographs for the Prediction of Abdominal Aortic Aneurysms
Authors: Damon E Houghton, Adelaide A Arruda-Olson, Vinod C Kaggal, Naresh Prodduturi, David A Liedl, Ana I Casanegra, Robert D McBane, Paul W Wennberg, Thom W Rooke, Sean P Murphy
Journal: Circulation (2023)

Introduction: Predictive algorithms using multiple clinical variables can identify patients at higher risk for abdominal aortic aneurysms (AAA), however they are cumbersome and cannot used directly by patients. A simple, cheap, noninvasive, and readily available (virtual) screening tool for identification of AAA could aid in screening algorithms. Aims: We sought to determine if a machine learning algorithm could predict the presence of an AAA by using a image of the face Methods: Diagnostic imaging studies were extracted from the electronic health record (EHR) from 5/7/2018 through 1/1/2023 and analyzed by a natural language processing algorithm previously validated to identify abdominal aortic aneurysms. Patient EHR profile pictures were extracted and matched to imaging studies. Various deep neural network (DNN) architectures were explored, all trained as classifiers on the face images along with clinical variables to predict clinical outcomes. All models used were CNNs with an EfficientNet architecture. Model performance was evaluated by standard metrics such as the area under the curve (AUC), specificities (Sp), and sensitivities (Sn). All performance metrics reported results from the test subset of the primary dataset and did not contain any observations considered during training. Results: A total of 5522 patients with facial images and AAA diagnostic studies were analyzed, among whom 1314 (23.8%) had a AAA. The optimal model had an AUC of 0.72 (Sn 0.44, Sp 0.83) for predicting AAA and remained similar in women (AUC 0.7), men (AUC 0.65), age &gt;65 (AUC 0.63), and age &lt;=65 (AUC 0.72) (Table). Conclusions: Using only an image of a patients face, the presence of an AAA could be identified with moderate performance in men, women, and in those less than 65. The model’s performance in demographics not typically screened for AAA may allow for targeted screening programs in these groups.
Abstract 18192: Sleep Apnea and Incident Atrial Fibrillation : Implications for Targeted Screening
Authors: Brototo Deb, Sunil K Vasireddi, neal bhatia, Albert J Rogers, Alexander C Perino, Sanjiv M Narayan
Journal: Circulation (2023)

Introduction: In younger individuals, the factors contributing to atrial fibrillation (AF) and ischemic stroke are not entirely understood. Despite the frequent coexistence of obstructive sleep apnea (OSA) and AF, current guidelines do not advise routine screening for either condition. Hypothesis: OSA may be an independent predictor of AF in younger adults Methods: We mined electronic health records of patients aged 20-50 Y who have had &gt;=2 visits within Stanford Healthcare System during the period of 2008 to 2022. Our primary endpoint was incident AF. A comprehensive list of risk factors was mined as covariates. Time-varying covariate survival analysis was done to relate the covariates to the primary endpoint. Analysis was performed in R. Results: From a total population of approximately 1.3 million patients aged between 20 and 50 years, we identified 541168 individuals. Among them, 66088 (12.2%) had OSA. During the follow-up, 5060 young adults (67 per 100,000 person-years) developed new AF. In the multivariable adjusted time-varying analysis, apart from previously reported cardiovascular and demographic risk factors, sleep apnea [aHR:1.13 (1.06,1.20)], CKD [aHR:1.91 (1.22,1.44)], cancer [aHR:1.12, (1.04,1.20)], chronic liver disease [aHR:1.13, (1.05,1.21)] were independent risk factors of AF (Fig 1a). Although risk portended by sleep apnea may be slightly lower than some CHADS2VASC factors, sleep apnea is much more prevalent than them, which may support the benefit for screening in this young population (Fig 1b). Conclusions: In a cohort of over half a million adults aged between 20 and 50, sleep apnea significantly and independently predicts incident AF, which may have implications in screening and treatment strategies for younger patients.
Abstract 12661: Area Deprivation Index, Symptoms, and Biomarkers Among Black and African Americans Living With Heart Failure
Authors: Christopher H Herring, Erica Davis, Melinda K Higgins, Alanna Morris, Sandra B Dunbar, Brittany Butts
Journal: Circulation (2023)

Introduction: Heart failure (HF) is a complex chronic condition that disproportionally affects Black adults. Social determinants of health, such as the lived environment and socioeconomic status, contribute to higher incidence and poorer outcomes, including higher stress and poorer sleep in this population. This study aims to examine the relationship between neighborhood socioeconomic disadvantage with symptoms, and inflammatory and cardiometabolic markers in Black adults living with HF. Methods: A secondary analysis of a pilot study that enrolled self-identified Black adults living with HF was performed (N=41, 57 ± 11 years of age, 66% women). Neighborhood socioeconomic disadvantage was measured by Area Deprivation Index (ADI) national and state rankings generated from the Neighborhood Atlas; higher scores reflect higher neighborhood disadvantage. Questionnaires included Perceived Stress Scale (PSS) and PROMIS Sleep Disturbance. Inflammatory and cardiometabolic biomarkers were measured via immunoassay. Spearman correlation analyses were performed. Results: Mean ADI scores were 61.23 ± 21.1 (national) and 5.7 ± 2.4 (state). National and State ADI scores were positively associated with both PSS (ρ=.584, p&lt;.001; ρ=.551, p&lt;.001) and PROMIS Sleep Disturbance (ρ=.486, p=.04; ρ =.551, p=&lt;.001), respectively. Additionally, National and State ADI scores were positively associated with inflammatory cytokines IL-4 (ρ=.345, p=.031; ρ=.371, p=.020) and IL-18 (ρ=.408, p=.009; ρ=.392, p=.012). National and State ADI scores were also related to cardiometabolic biomarkers VCAM-1 (ρ=.360, p=.022; ρ=.363, p=.021) and C1QNTF1 (ρ=.483, p=.002; ρ=.447, p=.004). No significant association was found between ADI scores and demographics. Discussion: These findings suggest higher ADI scores are associated with higher perceived stress, sleep disturbance, and inflammatory and cardiometabolic biomarkers among Black adults living with HF. These results highlight the potential role neighborhood socioeconomic status contributes to adverse health outcomes in this population.Further research is warranted to identify mechanisms contributing to these relationships and to develop approaches to reduce the impact of health disparities in HF.
Abstract 16360: Myocardial Injury and Rapid Unsupervised Topological Clustering of Electronic Health Record Features Predict Death and Length of Stay During a COVID-19 Hospitalization
Authors: Juan C Zarate Jarquin, Eliseo T Vazquez, Esha Datta, Aditya Ballal, Leighton T Izu, Angela Haczku, Jennifer L Whistler, Javier E Lopez
Journal: Circulation (2023)

Background: Elevated troponin levels, a biomarker of myocardial injury (MI), has emerged as a predictor of acute COVID-19 outcomes. However, a lack of routine use in most patients makes it difficult to evaluate as a stand-alone predictor. We aimed to combine troponin levels and a new rapid, unbiased topological clustering pipeline to test for improvements in clinical risk stratification during COVID hospitalizations. Methods: SlicerDicer (SD) is an intuitive, anonymous clinical electronic health record (EHR) data exploration tool that helps characterize clinical outcomes in hospital cohorts. EHR data and outcomes were extracted with SD and clustered with Mapper Plus (MP), a clustering tool that identifies clinically relevant disjoint clusters. Initial clusters were further stratified by troponin level. Measured outcomes were in-hospital mortality rates (MR) and in-hospital length of stay (LOS). Results: 2692 patient records (2020-2021) with an overall MR of 6.3% and 97 clinical predictors were analyzed. MP identified 3 clusters with significant differences in MR (C1- 25.8%, C2- 4.2%, C3- 0.23%, P&lt;0.001) and LOS in hours (C1- 290, C2- 132, C3- 8.3, P&lt;0.001). Further stratification based on the troponin level reclassified the 3 MP clusters into 4 sub-clusters with distinctive MR (SC1- 32.6%, SC2- 17.3%, SC3- 2.3%, SC4-0.09%, P&lt;0.001) based on MI presence. Conclusions: Using SD-based anonymous EHR data and unsupervised topological clustering with MP during a COVID hospitalization provides a low-effort, robust pipeline that predicts in-hospital MR and LOS. When MP clusters were re-stratified by the presence of MI, new sub-clusters (4) showed reclassification of both high- and low-risk patients. This risk classification schema provides a new pragmatic and computational framework for selecting hospitalized patients with COVID that can benefit from further in-hospital therapies and mechanistic studies on the role of myocardial injury in COVID-19 prognosis.
Abstract 14319: Riociguat in Pulmonary Arterial Hypertension: Application of the 4-strata COMPERA 2.0 Risk Assessment Tool in the PATENT Studies
Authors: Stephan Rosenkranz, Marius Hoeper, David Badesch, Marc Humbert, David Langleben, John W McConnell, Claudia Rahner, Ardeschir H Ghofrani
Journal: Circulation (2023)

Background: The 2022 ESC/ERS treatment guidelines for pulmonary arterial hypertension (PAH) recommend using a four-strata risk assessment strategy at follow-up. COMPERA 2.0 is a refined four-strata risk assessment tool that subdivides patients at intermediate risk of mortality at 1 year into intermediate-low and intermediate-high risk groups for a more granular approach to risk prediction. Aim: This post-hoc analysis applied COMPERA 2.0 to the PATENT studies of riociguat in patients with PAH. Methods: COMPERA 2.0 was applied to patients who were pretreated with PAH therapy at PATENT-1 entry. Patients with missing data for COMPERA 2.0 variables were excluded. In PATENT-1, risk strata were assessed at baseline and Week 12; and 6-minute walking distance (6MWD) at Week 12 was analyzed by risk strata at baseline. All pretreated patients entering the PATENT-2 open-label extension were included in Kaplan-Meier analyses to assess association of risk strata at PATENT-1 baseline and Week 12 with clinical worsening and survival. Results: At PATENT-1 baseline (riociguat 2.5 mg n=102, placebo n=49), more patients were at intermediate-low risk than intermediate-high risk (Figure 1). At PATENT-1 Week 12, a higher proportion of patients were at low risk with riociguat vs placebo (Figure 1). At PATENT-1 Week 12, the following mean [SD] changes in 6MWD were seen in patients at intermediate-low risk (riociguat 24 m [57 m], placebo 10 m [60 m]) and intermediate-high risk (riociguat 34 m [56 m], placebo –2 m [70 m]) by COMPERA 2.0 at baseline. COMPERA 2.0 assessed at PATENT-1 baseline and Week 12 was able to discriminate between risk strata for clinical worsening and survival in PATENT-2 (n=167, log-rank tests: p≤0.001 for all analyses). Conclusion: This analysis confirmed the risk-reduction benefits of riociguat in patients with PAH and validated the utility of COMPERA 2.0 in the long-term risk assessment of patients from a clinical trial population.
Abstract 16040: Atrial Fibrillation Status and Physical Rehabilitation in Older Patients With Acute Decompensated Heart Failure: An Analysis From the Rehab-HF Trial
Authors: Sean Dikdan, Naman Upadhyay, Douglas R Corsi, Haiying Chen, Dalane W Kitzman, Robert J Mentz, David J Whellan, Daniel Frisch
Journal: Circulation (2023)

Background: The REHAB-HF randomized, controlled trial demonstrated that a transitional, tailored, progressive rehabilitation intervention improved physical function, 6-minute walk distance, frailty, quality-of-life, and depression in older patients hospitalized for acute decompensated heart failure (ADHF). Atrial fibrillation (AF) is common in patients with HF and associated with poor exercise tolerance. However, exercise has proven safe and effective in improving quality of life in AF patients. It is unknown if AF impacts the benefit gained by rehabilitation intervention. Question: We hypothesized that patients with AF and ADHF would significantly improve physical function outcomes, and these improvements would not differ significantly from those gained by patients without AF. Methods: REHAB-HF enrolled 349 patients hospitalized for ADHF. Mean age was 72.7 ± 8.1 years. Participants were randomly assigned to the 12-week progressive rehabilitation intervention or attention control. The trial’s primary outcome was change in short physical performance battery (SPPB) score between baseline and 3 months. Secondary outcomes were clinical endpoints (rehospitalization or death). Results: AF was prevalent in 176 patients (50.4%). Participants with AF were significantly older than those without (74.4 ± 8.3 vs. 70.8 ± 7.5, p&lt;0.001) and had higher prevalence of HFpEF (58.5% vs 47.4%, p=0.037). Patients with and without AF had similar improvement in SPPB score (mean between-group difference, 1.5; 95% CI 0.4-2.5; p=0.001). There was no significant difference in mean SPPB between the two groups (p=0.98). KCCQ score and 6-minute walk distance significantly improved in patients with AF (p&lt;.05). The interaction P-values for 3-month outcomes by AF status were not significant (P &gt;0.1). There were no significant differences in deaths, all-cause rehospitalizations, or HF hospitalizations at 6 months. Conclusions: In older, hospitalized patients with ADHF, the presence of AF did not significantly affect the benefit of the transitional, tailored, progressive rehabilitation intervention. These findings suggest the intervention is safe to use to improve physical function and quality of life in patients hospitalized for ADHF regardless of AF status.
Abstract 17950: Atrial Fibrillation Impacts Mortality, Length of Stay, Resources Utilization and Need for Endotracheal Intubation in Patients Who Were Submitted to C-section or Natural Delivery: A Nationwide Analysis 2016-2020
Authors: Ricardo Carvalhais, Frederick B Rivera, Kamran Mahfooz, Akanimo Antia, Saher Taj Shiza, Linjie Yan, Jiahe Zhao, Nikolozi Bostashvili, Lia Veronique Priela
Journal: Circulation (2023)

Background: Atrial fibrillation (AF) is rare during pregnancy but the data on its impact during delivery is scaring. In this study, we aim to analyze the impact of AF in patients who underwent delivery via Cesarean section (CS), natural spontaneous delivery (NSD) or instrumental delivery (ID). Methods: We obtained the data from the National Inpatient Sample from 2016-2020. Our primary outcome was in-hospital mortality. Secondary outcomes included length of stay, total hospital charges and respiratory failure requiring intubation. Primary and secondary outcomes were adjusted to variables that had a p-value&lt;0.2 for that outcome. Results were considered statistically significant if p-value &lt;0.05. Results: There were 17,785,980 deliveries who underwent CS, NSD or ID. Of this, 6,000 patients had the secondary diagnosis of atrial fibrillation. The population had a mean age of 29.13 years. (See table 1) Patient with AF had almost twenty times more change of dying compared to those without AF odds ratio (OR) 19.12, 95% Confidence interval (CI) 4.33 - 84.45, p&lt;0.001. Furthermore, AF cohort stayed for one and a half day longer Coefficient 1.55, CI 1.16 - 1.94, p&lt;0.001, had a higher hospital charge Coefficient 19294.05, CI 14658.17 - 23929.93 and had a higher rate of respiratory complications requiring intubation OR 15.86, CI 7.83 - 32.15, p&lt;0.001. (See table 2) Conclusion: Atrial fibrillation has a substantial negative impact in inpatient outcomes on pregnant patients during delivery. Further research is needed to explore these disparities in maternal care.
Abstract 14779: Whole Exome Sequencing Study in Pediatric Postural Orthostatic Tachycardia Syndrome Unveils a Path Forward From Genes to Drugs
Authors: Huiqi Qu, Joseph Glessner, Xiao Chang, Frank Mentch, Yichuan Liu, Marina A Bakay, Jeffrey Boris, Hakon Hakonarson
Journal: Circulation (2023)

Introduction: Postural orthostatic tachycardia syndrome (POTS) is more common in Caucasian individuals with a positive family history, while the risk in females is ~4-times of that in males. To date, the etiology of POTS is poorly understood. Hypothesis: Integrative sequencing and translational approaches to identify its genetic underpinning may better understand its pathogenesis and molecular mechanisms for the development of novel precision-based therapies. Methods: We adopted exome sequencing to evaluate the etiology and molecular mechanisms of POTS. We examined a unique collection of 87 unrelated pediatric POTS cases (61 females and 26 males, 6~21 years old), using exome sequencing. Non-relationship between individuals were validated by genome wide genotyping and identity by descent (IBD) analysis. Results: All the individuals were classified as European by principal component analysis (Figure 1). We identified 184 pathogenic (P) or likely pathogenic (LP) variants (in 162 genes). Sixty-eight (78%) cases have at least one P/LP variant. Each P/LP mutation is supported by a minimum of two databases, including ClinVar, InterVar or HGMD_Pro_2023.1. Over-representation analysis (ORA) by the DisGeNET approach showed the enriched gene sets of muscle hypotonia and epilepsy/seizures with statistical significance (FDR&lt;E-10). Clinically, among the 87 WES patients, 41 (47%) suffered from chronic fatigue, and 13 (15%) patients have the symptoms of epilepsy, seizure or convulsion. A number of drug targets in these gene sets are highlighted, including vitamin D receptor, carbamoyl-phosphate synthase 1, methylmalonyl-CoA mutase, androgen receptor, and phenylalanine hydroxylase. Conclusions: Our results suggests that chronic fatigue and epilepsy/seizure symptoms are comorbid symptoms in POTS patients, resulting from common genetic defects. Future precision-based therapies targeting these specific genetic defects may lead to improved outcome in POTS.