Pericardial Disease in Cardiac Amyloidosis.

In patients with cardiac amyloidosis, pericardial involvement is common, with up to half of patients presenting with pericardial effusions. The pathophysiological mechanisms of pericardial pathology in cardiac amyloidosis include chronic elevations in right-sided filling pressures, myocardial and pericardial inflammation due to cytotoxic effects of amyloid deposits, and renal involvement with subsequent uremia and hypoalbuminemia. The pericardial effusions are typically small; however, several cases of life-threatening cardiac tamponade with hemorrhagic effusions have been described as a presenting clinical scenario. Constrictive pericarditis can also occur due to amyloidosis and its identification presents a clinical challenge in patients with cardiac amyloidosis who concurrently manifest signs of restrictive cardiomyopathy. Multimodality imaging, including echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging, is useful in the evaluation and management of this patient population. The recognition of pericardial effusion is important in the risk stratification of patients with cardiac amyloidosis as its presence confers a poor prognosis. However, specific treatment aimed at the effusions themselves is seldom indicated. Cardiac tamponade and constrictive pericarditis may necessitate pericardiocentesis and pericardiectomy, respectively.

Machine Learning-Enabled Image Classification for Automated Electron Microscopy.

Traditionally, materials discovery has been driven more by evidence and intuition than by systematic design. However, the advent of "big data" and an exponential increase in computational power have reshaped the landscape. Today, we use simulations, artificial intelligence (AI), and machine learning (ML) to predict materials characteristics, which dramatically accelerates the discovery of novel materials. For instance, combinatorial megalibraries, where millions of distinct nanoparticles are created on a single chip, have spurred the need for automated characterization tools. This paper presents an ML model specifically developed to perform real-time binary classification of grayscale high-angle annular dark-field images of nanoparticles sourced from these megalibraries. Given the high costs associated with downstream processing errors, a primary requirement for our model was to minimize false positives while maintaining efficacy on unseen images. We elaborate on the computational challenges and our solutions, including managing memory constraints, optimizing training time, and utilizing Neural Architecture Search tools. The final model outperformed our expectations, achieving over 95% precision and a weighted F-score of more than 90% on our test data set. This paper discusses the development, challenges, and successful outcomes of this significant advancement in the application of AI and ML to materials discovery.

Immune checkpoint inhibitors and pericardial disease: a systematic review.

INTRODUCTION: Despite the growing use of immune checkpoint inhibitors (ICI) in cancer treatment, data regarding ICI-associated pericardial disease are primarily derived from case reports and case series. ICI related pericardial disease can be difficult to diagnose and is associated with significant morbidity. We conducted a systematic review to further characterize the epidemiology, clinical presentation, and outcomes of this patient population. METHODS: A search of four databases resulted in 31 studies meeting inclusion criteria. Patients > 18 years old who presented with ICI mediated pericardial disease were included. Intervention was medical + surgical therapy and outcomes were development of cardiac tamponade, morbidity, and mortality. RESULTS: Thirty- eight patients across 31 cases were included. Patients were majority male (72%) with a median age of 63. Common symptoms included dyspnea (59%) and chest pain (32%), with 41% presenting with cardiac tamponade. Lung cancer (81%) was the most prevalent, and nivolumab (61%) and pembrolizumab (34%) were the most used ICIs. Pericardiocentesis was performed in 68% of patients, and 92% experienced symptom improvement upon ICI cessation. Overall mortality was 16%. DISCUSSION: This study provides the most comprehensive analysis of ICI-mediated pericardial disease to date. Patients affected were most commonly male with lung cancer treated with either Nivolumab or Pembrolizumab. Diagnosis may be challenging in the setting of occult presentation with normal EKG and physical exam as well as delayed onset from therapy initiation. ICI-associated pericardial disease demonstrates high morbidity and mortality, as evidenced by a majority of patients requiring pericardiocentesis.

Outcomes and treatment strategy of transcatheter aortic valve replacement with balloon-expandable valve in borderline-size annulus.

BACKGROUND: Candidates for transcatheter aortic valve replacement (TAVR) occasionally have a "borderline-size" aortic annulus between 2 transcatheter heart valve sizes, based on the manufacturer's sizing chart. Data on TAVR outcomes in such patients are limited. METHODS: We retrospectively reviewed 1816 patients who underwent transfemoral-TAVR with balloon-expandable valve (BEV) at our institution between 2016 and 2020. We divided patients into borderline and non-borderline groups based on computed tomography-derived annular measurements and compared outcomes. Furthermore, we analyzed procedural characteristics and compared outcomes between the smaller- and larger-valve strategies in patients with borderline-size annulus. RESULTS: During a median follow-up of 23.3 months, there was no significant difference between the borderline (n = 310, 17.0 %) and non-borderline (n = 1506) groups in mortality (17.3 % vs. 19.5 %; hazard ratio [HR] = 0.86 [95% CI = 0.62-1.20], p = 0.39), major adverse cardiac/cerebrovascular events (MACCE: death/myocardial infarction/stroke, 21.2 % vs. 21.5 %; HR = 0.97 [0.71-1.32], p = 0.85), paravalvular leak (PVL: mild 21.8 % vs. 20.6 %, p = 0.81; moderate 0 % vs. 1.2 %; p = 0.37), or mean gradient (12.9 ± 5.8 vs. 12.6 ± 5.2 mmHg, p = 0.69) at 1 year. There was no significant difference between the larger-(n = 113) and smaller-valve(n = 197) subgroups in mortality (23.7 % vs. 15.2 %; HR = 1.57 [0.89-2.77], p = 0.12), MACCE (28.1 % vs. 18.4 %; HR = 1.52 [0.91-2.54], p = 0.11), mild PVL (13.3 % vs. 25.9 %; p = 0.12), or mean gradient (12.3 ± 4.5 vs. 13.6 ± 5.3 mmHg, p = 0.16); however, the rate of permanent pacemaker implantation (PPI) was higher in the larger-valve subgroup (15.9 % vs. 2.6 %, p < 0.001). CONCLUSION: Borderline-size annulus is not associated with higher risk of adverse outcomes after BEV-TAVR. However, the larger-valve strategy for borderline-size annulus is associated with higher PPI risk, suggesting a greater risk of injury to the conduction system.

Simultaneously improving accuracy and computational cost under parametric constraints in materials property prediction tasks.

Modern data mining techniques using machine learning (ML) and deep learning (DL) algorithms have been shown to excel in the regression-based task of materials property prediction using various materials representations. In an attempt to improve the predictive performance of the deep neural network model, researchers have tried to add more layers as well as develop new architectural components to create sophisticated and deep neural network models that can aid in the training process and improve the predictive ability of the final model. However, usually, these modifications require a lot of computational resources, thereby further increasing the already large model training time, which is often not feasible, thereby limiting usage for most researchers. In this paper, we study and propose a deep neural network framework for regression-based problems comprising of fully connected layers that can work with any numerical vector-based materials representations as model input. We present a novel deep regression neural network, iBRNet, with branched skip connections and multiple schedulers, which can reduce the number of parameters used to construct the model, improve the accuracy, and decrease the training time of the predictive model. We perform the model training using composition-based numerical vectors representing the elemental fractions of the respective materials and compare their performance against other traditional ML and several known DL architectures. Using multiple datasets with varying data sizes for training and testing, We show that the proposed iBRNet models outperform the state-of-the-art ML and DL models for all data sizes. We also show that the branched structure and usage of multiple schedulers lead to fewer parameters and faster model training time with better convergence than other neural networks. Scientific contribution: The combination of multiple callback functions in deep neural networks minimizes training time and maximizes accuracy in a controlled computational environment with parametric constraints for the task of materials property prediction.

Intracardiac Thrombus in COVID-19 Inpatients: A Nationwide Study of Incidence, Predictors, and Outcomes.

COronaVIrus Disease-2019 (COVID-19) is associated with a hypercoagulable state. Intracardiac thrombosis is a potentially serious complication but has seldom been evaluated in COVID-19 patients. We assessed the incidence, associated factors, and outcomes of COVID-19 patients with intracardiac thrombosis. In 2020, COVID-19 inpatients were identified from the National Inpatient Sample (NIS) database. Data on clinical characteristics, intracardiac thrombosis, and adverse outcomes were collected. Multivariable logistic regression was used to identify factors associated with intracardiac thrombosis, in-hospital mortality, and morbidities. In 2020, 1,683,785 COVID-19 inpatients (mean age 63.8 years, 32.2% females) were studied. Intracardiac thrombosis occurred in 0.10% (1830) of cases. In-hospital outcomes included 13.2% all-cause mortality, 3.5% cardiovascular mortality, 2.6% cardiac arrest, 4.4% acute coronary syndrome (ACS), 16.1% heart failure, 1.3% stroke, and 28.3% acute kidney injury (AKI). Key factors for intracardiac thrombosis were congestive heart failure history and coagulopathy. Intracardiac thrombosis independently linked to higher risks of all-cause mortality (odds ratio [OR]: 3.32 (2.42-4.54)), cardiovascular mortality (OR: 2.95 (1.96-4.44)), cardiac arrest (OR: 2.04 (1.22-3.43)), ACS (OR: 1.62 (1.17-2.22)), stroke (OR: 3.10 (2.11-4.56)), and AKI (OR: 2.13 (1.68-2.69)), but not heart failure. While rare, intracardiac thrombosis in COVID-19 patients independently raised in-hospital mortality and morbidity risks.

Optimal antiplatelet strategy following coronary artery bypass grafting: a meta-analysis.

OBJECTIVE: Coronary artery bypass grafting (CABG) is an established revascularisation strategy for multivessel and left main coronary artery disease. Although aspirin is routinely recommended for patients with CABG, the optimal antiplatelet regimen after CABG remains unclear. We evaluated the efficacies and risks of different antiplatelet regimens (dual (DAPT) versus single (SAPT), and dual with clopidogrel (DAPT-C) versus dual with ticagrelor or prasugrel (DAPT-T/P)) after CABG. METHODS: We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and performed a comprehensive literature search using PubMed, Ovid Medline, Ovid Embase and Cochrane Central Register of Controlled Trials. Data were extracted and pooled using random-effects models and Review Manager (V.5.4). RESULTS: Among the 2970 article abstracts screened, 215 full-text articles were reviewed and 38 studies totaling 77 447 CABG patients were included for analyses. DAPT compared with SAPT was associated with significantly lower all-cause mortality (OR 0.65 with 95% CI 0.50 to 0.86; p=0.002), cardiovascular mortality (OR 0.53, 95% CI 0.33 to 0.84; p=0.008), and major adverse cardiac and cerebrovascular events (MACCE) (OR 0.68, 95% CI 0.51 to 0.91; p=0.01), but higher rates of major (OR 1.30, 95% CI 1.08 to 1.56; p=0.007) and minor bleeding (OR 1.87, 95% CI 1.28 to 2.74; p=0.001) after CABG. DAPT-T/P compared with DAPT-C was associated with significantly lower all-cause (OR 0.43, 95% CI 0.29 to 0.65; p≤0.0001) and cardiovascular mortality (OR 0.44, 95% CI 0.24 to 0.80; p=0.008), and no differences on other cardiovascular or bleeding outcomes after CABG. CONCLUSION: In patients with CABG, DAPT compared with SAPT and DAPT-T/P compared with DAPT-C were associated with reduction in all-cause and cardiovascular mortality, especially in patients with acute coronary syndrome. Additionally, DAPT was associated with reduction in MACCE, but higher rates of major and minor bleeding. An individualised approach to choosing antiplatelet regimen is necessary for patients with CABG based on ischaemic and bleeding risks.

Development and Validation of a Machine Learning Risk-Prediction Model for 30-Day Readmission for Heart Failure Following Transcatheter Aortic Valve Replacement (TAVR-HF Score).

Transcatheter aortic valve replacement (TAVR) is the treatment of choice for patients with severe aortic stenosis across the spectrum of surgical risk. About one-third of 30-day readmissions following TAVR are related to heart failure (HF). Hence, we aim to develop an easy-to-use clinical predictive model to identify patients at risk for HF readmission. We used data from the National Readmission Database (2015-2018) utilizing ICD-10 codes to identify TAVR procedures. Readmission was defined as the first unplanned HF readmission within 30-day of discharge. A machine learning framework was used to develop a 30-day TAVR-HF readmission score. The receiver operator characteristic curve was used to evaluate the predictive power of the model. A total of 92,363 cases of TAVR were included in the analysis. Of the included patients, 3299 (3.6%) were readmitted within 30 days of discharge with HF. Individuals who got readmitted, vs those without readmission, had more emergent admissions during index procedure (33.4% vs 19.8%), electrolyte abnormalities (38% vs 16.7%), chronic kidney disease (34.8% vs 21.2%), and atrial fibrillation (60.1% vs 40.7%). Candidate variables were ranked by importance using a parsimony plot. A total of 7 variables were selected based on predictive ability as well as clinical relevance: HF with reduced ejection fraction (25 points), HF preserved EF (20 points), electrolyte abnormalities (17 points), atrial fibrillation (12 points), Charlson comorbidity index (<6 = 0, 6-8 = 9, 9-10 = 13, >10 = 14 points), chronic kidney disease (7 points), and emergent index admission (5 points). On performance evaluation using the testing dataset, an area under the curve of 0.761 (95% CI 0.744-0.778) was achieved. Thirty-day TAVR-HF readmission score is an easy-to-use risk prediction tool. The score can be incorporated into electronic health record systems to identify at-risk individuals for readmissions with HF following TAVR. However, further external validation studies are needed.

Perioperative outcomes of hypertrophic cardiomyopathy: An insight from the National Readmission Database.

BACKGROUND: Data regarding hypertrophic obstructive cardiomyopathy (HOCM) patients undergoing noncardiac surgery is lacking. We sought to examine the perioperative outcomes of HOCM patients undergoing noncardiac surgery using a national database. METHODS: We used the National readmission database from 2016 to 2019. We identified HOCM, heart undergoing noncardiac surgery using ICD 10 codes. We examined hospital outcomes as well as 90 days readmission outcomes. RESULTS: We identified 16,098 HOCM patients and 21,895,699 non-HOCM patients undergoing noncardiac surgery. The HOCM group had more comorbidities at baseline. After adjustment for major clinical predictors, the HOCM group experienced more in-hospital death, odds ratio (OR) 1.33 (1.216-1.47), P < 0.001, acute myocardial infarction (AMI), OR 1.18 (1.077-1.292), P < 0.001, acute heart failure odds ratio OR 1.3 to (1.220-1.431), P < 0.001, 90 days readmission OR 1.237 (1.069-1.432), P < 0.01, cardiogenic shock OR 2.094 (1.855-2.363), P < 0.001. Cardiac arrhythmia was the most common cause of readmission, out of the arrhythmias atrial fibrillation was the most prevalent. Acute heart failure was the most common complication of readmission. There was no difference in major adverse cardiovascular events (MACE), and AMI between both groups and readmission. CONCLUSION: HOCM patients undergoing noncardiac surgery may be at increased risk of in-hospital and readmission events. Acute heart failure was the most common complication during index admission, while cardiac arrhythmias were the most common complication during readmission. More research is needed to address this patient population further.

Feasibility and Safety of Intracardiac Echocardiography Guidance in Mitral Transcatheter Edge-to-Edge Repair: Analysis of the National Inpatient Sample Data From 2015 to 2020.

Data on the use of intracardiac echocardiography (ICE) guidance in mitral transcatheter edge-to-edge repair (mTEER) procedure is limited to case reports and small case series. Our study aims to assess the feasibility, safety, utilization patterns, and clinical outcomes of mTEER procedure with ICE guidance using a nationally representative real-world cohort of patients. This study used the National Inpatient Sample database from quarter 4 of 2015 to 2020. We used a propensity-matched analysis and adjusted odds ratios for in-hospital outcomes/complications. A P value of < 0.05 was considered significant. A total of 38,770 weighted cases of mTEER were identified. Of the included patients 665 patients underwent ICE-guided mTEER while 38,105 had TEE-guided mTEER. There were no differences in the in-hospital mortality between both groups (2.5% vs 3.0%, P = 0.58). Adjusted odds of in-hospital mortality (aOR 0.83, 95%CI [0.42-1.64]) were not significantly different. There were no differences in periprocedural complications including cardiac (aOR 0.85, 95%CI [0.54-1.35]), bleeding (aOR 1.45, 95%CI [0.93-2.33]), respiratory (aOR 0.88, 95%CI [0.61-1.25]), and renal (aOR 0.89, 95%CI [0.66-1.20]) complications between patients undergoing ICE-guided vs TEE-guided mTEER. There was no difference in GI complications between both groups (aOR 1.11, 95%CI [0.46-2.70]). The adjusted length of stay was less among ICE-guided mTEER (median: 1 vs 2, P < 0.01) with lower inflation-adjusted costs of hospitalization ($35,513 vs $47,067, P < 0.01). ICE-guided mTEER is safe when compared with TEE guided mTEER with no significant differences in in-hospital mortality, cardiac, bleeding, respiratory, and renal complications.

Successful Treatment of Recurrent Pericarditis With Rilonacept in Acute Promyelocytic Leukemia.

A 40-year-old woman presented with recurrent pericarditis and pericardial effusion while receiving treatment with all-trans retinoic acid and arsenic trioxide for recently diagnosed acute promyelocytic leukemia. She was successfully treated with the interleukin-1 inhibitor rilonacept after experiencing multiple recurrences with triple therapy with aspirin, colchicine, and steroids. (Level of Difficulty: Advanced.).

Sex-Specific Differences in Clinical Outcomes in Patients With Coronary Bifurcation Lesions.

Coronary bifurcation lesions are frequent challenging findings during percutaneous coronary intervention (PCI). Contemporary evidence has explored the potential sex-specific differences in patients undergoing PCI. In the present meta-analysis, we compared clinical outcomes of patients undergoing bifurcation PCI between women and men. Using the random-effects method, we compared the clinical outcomes of patients with a coronary bifurcation lesion following PCI between women and men. The results were reported using relative risk (RR) and 95% confidence interval (CI). Baseline comorbidities and mean age were compared between the 2 studied groups. Four observational studies comprising 30,684 patients (8898 women and 21,786 men) were included in the meta-analysis. Women were significantly older than men with a relatively higher prevalence of baseline comorbidities. After using adjusted data from 2 out of 4 available studies, performing PCI for bifurcation lesions in women was not associated with an increased risk of mortality (RR 1.33, 95% CI, 0.78-2.29), myocardial infarction (RR 1.22, 95% CI, 0.41-3.61), target lesion revascularization (RR 1.06, 95% CI, 0.40-2.81), stent thrombosis (RR 0.99, 95% CI, 0.09-10.52), and stroke (RR 1.19, 95% CI, 0.64-2.22). Women were at higher risk of major bleeding compared to male counterparts (RR 2.23, 95% CI, 1.73-2.89). The present study showed no difference in the risk of adverse clinical outcomes except the risk of bleeding between genders with coronary bifurcation lesions. Future studies with adjustment of age and baseline comorbidities are needed to confirm these findings.

An Unusual Case of Parasitic Constrictive Pericarditis.

Parasitic constrictive pericarditis is a rare entity. We present a case of a 75-year-old man who presented with dyspnea, ascites, and pedal edema and was found to have constrictive pericarditis on multimodality imaging with positive serology for Strongyloides Stercoralis. Treatment required ivermectin and radical pericardiectomy with significant clinical improvement. (Level of Difficulty: Intermediate.).

MitraCox Score Predicts In-Hospital Mortality in Patients Admitted for Transcatheter Edge-to-Edge Mitral Valve Repair.

As mitral valve transcatheter edge-to-edge repair (M-TEER) is evolving as an effective treatment for high-risk surgical patients with mitral regurgitation, there is a pressing need for cardiologists to optimize resources through risk stratification of in-hospital mortality for this patient population. Although current risk-prediction models have been shown to predict adverse outcomes with reasonable accuracy, models trained using the US nationwide population are lacking. This study aimed to identify clinical, demographic, and procedural features that predict in-hospital mortality, and to derive and validate an in-hospital mortality risk-prediction tool in patients who have undergone M-TEER. A total of 9,373 admissions from the Nationwide Readmissions Database of patients who underwent M-TEER between 2015 and 2018 were used to develop and validate the model. We first performed least absolute shrinkage and selection operator (LASSO) regularization of Cox regression (Coxnet) that is 10-fold cross-validated. The non-zero coefficients were multiplied with the respective values of each observation of the predictors to build the scoring formula. Out of 9,373 admissions, 196 patients (2%) died in-hospital during index admission. In descending order, the top variables that were most predictive of in-hospital mortality were higher age, presence of fluid and electrolyte disturbance, and large metropolitan location of the hospital. The validation C-statistic of the MitraCox score was 0.82. Using X-tile software (Yale School of Medicine, New Haven, Connecticut), 2 cutoffs of the score were determined on the basis of in-hospital mortality and length of stay, and the survival of the population was classified into 3 risk groups: low, intermediate, and high. The scoring system deployed online as a web-based calculator can be accessed at https://kathavs.shinyapps.io/Mitracox_Kapadia/. In conclusion, MitraCox score is easy to calculate and predicts in-hospital mortality depending on length of stay in a dynamic manner.