Prevalence and patient risk factors for pneumothorax in COVID-19 and in influenza pneumonia: a nationwide comparative analysis.

Background: Pneumothorax is a rare but deadly complication in patients who require mechanical ventilation. As with any condition associated with acute respiratory distress syndrome (ARDS), coronavirus disease 2019 (COVID-19) is known to be associated with pneumothorax. However, in the literature, comparative data on the risk factors for pneumothorax in COVID-19 and other diseases like influenza are limited. The aim of this study is to determine the prevalence and risk factors for pneumothorax in hospitalized COVID-19 patients and compare them with influenza pneumonia patients. Methods: This study is a retrospective analysis of the National Inpatient Sample (NIS) 2020 database cohort. Univariate and multivariate logistic regression were used to identify the prevalence and risk factors for pneumothorax in COVID-19 patients and compared with the risk of pneumothorax in influenza patients. Results: The NIS 2020 database includes 1,608,980 hospitalizations of COVID-19 patients, of which 22,545 [95% confidence interval (CI): 21,491-23,598] (1.4%) developed pneumothorax. On multivariate analysis, factors associated with pneumothorax in COVID-19 included patient age of 41-64 years; male sex; Hispanics, Native Americans, and other races; hospitals with large-bed size; privately owned hospitals; urban teaching hospitals; hospitals in the southern United States (US); stroke; malnutrition; chronic obstructive pulmonary disease (COPD); bronchiectasis; pulmonary fibrosis; liver disease; non-invasive and invasive ventilation; and extracorporeal membrane oxygenation (ECMO). Of 184,980 influenza patients, 1,630 (95% CI: 1,448-1,811) (0.88%) developed pneumothorax. The prevalence of pneumothorax was higher (1.4%) in COVID-19 patients compared to patients with influenza pneumonia (0.88%). Conclusions: COVID-19 patients who develop pneumothorax have a poor prognosis. Several risk factors for the development of pneumothorax were identified. Patients with these risk factors should be prioritized in applying evidence-based guidelines to prevent pneumothorax.

Glucagon-Like Peptide-1 Receptor Agonists and Major Adverse Cardiovascular Events in Patients With and Without Diabetes: A Meta-Analysis of Randomized-Controlled Trials.

INTRODUCTION: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have shown encouraging results regarding cardiovascular outcomes mainly in patients with diabetes. In the present study, we compared the efficacy of GLP-1 RAs in cardiovascular events between patients with and without diabetes. METHODS: After finding eligible studies assessing the impact of GLP-1 RAs on cardiovascular events in patients with and without diabetes using a systematic search, we performed a meta-analysis on randomized-controlled trials (RCTs) comparing cardiovascular outcomes between patients taking GLP-1 RAs and placebo stratified by the presence or absence of diabetes. Relative risk (RR) and its 95% confidence interval (CI) were set as the reporting effect size using the random-effects model. RESULTS: A total of 24 RCTs (50 033 with GLP-1 RAs and 44 514 with placebo) were included. Patients on GLP-1 RAs had lower risk of major adverse cardiovascular events (MACE) (RR 0.87, 95% CI 0.82-0.93), cardiovascular death (RR 0.88, 95% CI 0.82-0.94), myocardial infarction (MI) (RR 0.87, 95% CI 0.77-0.97), stroke (RR 0.86, 95% CI 0.80-0.92), and hospitalization for heart failure (RR 0.90, 95% CI 0.83-0.98). Both subgroups were shown to be effective in terms of MACE and mortality. Nondiabetic patients had decreased risk of hospitalization for heart failure and MI, whereas the diabetic subgroup had marginally nonsignificant efficacy. CONCLUSION: The findings of this meta-analysis indicated that patients who are overweight/obese but do not have diabetes have a comparable reduction in the risk of adverse cardiovascular events as those with diabetes. These results need to be confirmed further by large-scale randomized trials in the future.

Incidence, Predictors, and Outcomes of Venous and Arterial Thrombosis in COVID-19: A Nationwide Inpatient Analysis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is known to increase the risk of venous thromboembolism (VTE) and arterial thromboembolism (ATE). However, the incidence, predictors, and outcomes of clinical thrombosis for inpatients with COVID-19 are not well known. This study aimed to enhance our understanding of clinical thrombosis in COVID-19, its associated factors, and mortality outcomes. METHOD: Hospitalised adult (≥18 years of age) patients with COVID-19 in 2020 were retrospectively identified from the US National Inpatient Sample database. Clinical characteristics, incident VTE, ATE, and in-hospital mortality outcomes were recorded. Multivariable logistic regression was performed to identify clinical factors associated with thrombosis and in-hospital mortality in COVID-19 inpatients. RESULTS: A total of 1,583,135 adult patients with COVID-19 in the year 2020 were identified from the National Inpatient Sample database; patients with thrombosis were 41% females with a mean age of 65.4 (65.1-65.6) years. The incidence of thrombosis was 6.1% (97,185), including VTE at 4.8% (76,125), ATE at 3.0% (47,790), and the in-hospital mortality rate was 13.4% (212,785). Patients with thrombosis were more likely to have respiratory symptoms of COVID-19 (76.7% vs 75%, p<0.001) compared with patients without thrombosis. The main factors associated with overall thrombosis, VTE, and ATE were paralysis, ventilation, solid tumours without metastasis, metastatic cancer, and acute liver failure. Although all thrombosis categories were associated with higher in-hospital mortality for COVID-19 inpatients in univariable analyses (p<0.001), they were not in multivariable analyses-thrombosis (odds ratio [OR] 1.24; 95% confidence interval [CI] 0.90-1.70; p=0.19), VTE (OR 0.70; 95% CI 0.52-1.00; p=0.05), and ATE (OR 1.07; 95% CI 0.92-1.25; p=0.36). CONCLUSIONS: The association of COVID-19 with thrombosis and VTE increases with increasing severity of the COVID-19 disease. Risk stratification of thrombosis is crucial in COVID-19 patients to determine the necessity of thromboprophylaxis.

"Quality of life is impaired in children with chronic pancreatitis: A multicenter study".

BACKGROUND AND OBJECTIVES: The impact of chronic pancreatitis (CP) on quality of life (QOL) of children is not well established. Our objective was to evaluate the QOL, identify contributing factors, and determine the prevalence of anxiety and depression in children with CP in India. METHODS: Children (8-18y old) with CP were prospectively enrolled across three pediatric gastroenterology centres in India. QOL was assessed using the pediatric QOL inventory (PedsQL 4.0) scale, administered to both children and their parents. Anxiety and depression was studied using the Revised Children's Anxiety and Depression Scale (RCADS 25). Contributing factors were identified using binary logistic regression analysis. The data was compared against published QOL data in healthy Indian children. RESULTS: 121 children with CP (boys-57.9 %, age at QOL-14 ± 3.2years) were enrolled. A majority (82.7 %) had pain and advanced disease (Cambridge grade IV- 63.6 %). Children with CP had poorer QOL compared to controls (total score 74.6 ± 16 vs. 87.5 ± 11.1, p < 0.0001). QOL scores were similar across centres. Older children were similar to younger ones, except for a poorer emotional QOL. Taking QOL < -2 standard deviation (SD) of controls, ∼35 % had poor physical (50.9 ± 11.9) and 20 % had poor psychosocial (PS) QOL score (52.1 ± 7.2). On analysis, presence of pain and lower socio-economic status (SES) adversely affected both physical and PS-QOL. Additionally, girls had poorer PS-QOL than boys (Odds ratio 3.1, 95%CI:1.23-7.31). Anxiety and depression were uncommon (2,1.6 %). CONCLUSIONS: Patients with CP had impaired physical and psycho-social QOL. Presence of pain and lower SES adversely affected QOL. Psychiatric comorbidities were uncommon.

Pericardial Disease in Cardiac Amyloidosis: A Comprehensive Review.

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.

Cardiovascular Complications With Delivery Hospitalizations in Patients With Pulmonary Hypertension: A Nationwide Study From 2011 to 2020.

BACKGROUND: Pregnancy in patients with pulmonary hypertension (PH) is associated with a heightened risk of medical complications including right heart failure, pulmonary edema, and arrhythmias. Our study investigated the association between PH and these complications during delivery. METHODS AND RESULTS: The National Inpatient Sample was used to identify delivery hospitalizations from 2011 to 2020. Multivariable logistic regression was performed to study the association of PH with the primary outcomes of in-hospital medical and obstetric complications. A total of 37 482 207 delivery hospitalizations in women ≥18 years of age were identified, of which 9593 patients had PH. Pregnant patients with PH had higher incidence of complications during delivery including preeclampsia/eclampsia, arrhythmias, and pulmonary edema among others, compared with those without PH. Pregnant patients with PH also had a higher incidence of in-hospital mortality compared with those without PH (0.51% versus 0.007%). In propensity-matched analyses, PH was still significantly associated with a higher risk of in-hospital mortality (odds ratio [OR], 5.02 [95% CI, 1.82-13.90]; P=0.001), pulmonary edema (OR, 9.11 [95% CI, 6.34-13.10]; P<0.001), peripartum cardiomyopathy (OR, 1.85 [95% CI, 1.37-2.50]; P<0.001), venous thromboembolism (OR, 12.60 [95% CI, 6.04-26.10]; P<0.001), cardiac arrhythmias (OR, 6.11 [95% CI, 4.97-7.53]; P<0.001), acute kidney injury (OR, 3.72 [95% CI, 2.86-4.84]; P<0.001), preeclampsia/eclampsia (OR, 2.24 [95% CI, 1.95-2.58]; P<0.001), and acute coronary syndrome (OR, 2.01 [95% CI, 1.06-3.80]; P=0.03), compared with pregnant patients without PH. CONCLUSIONS: Delivery hospitalizations in patients with PH are associated with a high risk of mortality, pulmonary edema, peripartum cardiomyopathy, venous thromboembolism, arrhythmias, acute kidney injury, preeclampsia/eclampsia, and acute coronary syndrome.

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.

Quality of Life in Recurrent Pericarditis.

Recurrent pericarditis (RP) poses a significant burden on individuals' quality of life. The psychosocial impact of RP is not well understood. It cannot be overlooked, as it can impact the psychosocial well-being of the patients due to the chronicity of the symptoms and multiple flare-ups. Addressing the multifaceted challenges posed by RP requires a comprehensive approach that not only focuses on symptom control but also emphasizes patient education, psychological support, and shared decision-making to optimize both physical and emotional well-being. Therefore, we aim to share our perspective on the effect of RP on the quality of life of the patients.

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.).