Limited column formation in the embryonic growth plate implies divergent growth mechanisms during pre- and postnatal bone development.

Chondrocyte columns, which are a hallmark of growth plate architecture, play a central role in bone elongation. Columns are formed by clonal expansion following rotation of the division plane, resulting in a stack of cells oriented parallel to the growth direction. In this work, we analyzed hundreds of Confetti multicolor clones in growth plates of mouse embryos using a pipeline comprising 3D imaging and algorithms for morphometric analysis. Surprisingly, analysis of the elevation angles between neighboring pairs of cells revealed that most cells did not display the typical stacking pattern associated with column formation, implying incomplete rotation of the division plane. Morphological analysis revealed that although embryonic clones were elongated, they formed clusters oriented perpendicular to the growth direction. Analysis of growth plates of postnatal mice revealed both complex columns, composed of ordered and disordered cell stacks, and small, disorganized clusters located in the outer edges. Finally, correlation between the temporal dynamics of the ratios between clusters and columns and between bone elongation and expansion suggests that clusters may promote expansion, whereas columns support elongation. Overall, our findings support the idea that modulations of division plane rotation of proliferating chondrocytes determines the formation of either clusters or columns, a multifunctional design that regulates morphogenesis throughout pre- and postnatal bone growth. Broadly, this work provides a new understanding of the cellular mechanisms underlying growth plate activity and bone elongation during development.

Predicting Long-Term Clinical Outcomes of Patients With Recurrent Pericarditis.

BACKGROUND: Recurrent pericarditis (RP) is a complex condition associated with significant morbidity. Prior studies have evaluated which variables are associated with clinical remission. However, there is currently no established risk-stratification model for predicting outcomes in these patients. OBJECTIVES: We developed a risk stratification model that can predict long-term outcomes in patients with RP and enable identification of patients with characteristics that portend poor outcomes. METHODS: We retrospectively studied a total of 365 consecutive patients with RP from 2012 to 2019. The primary outcome was clinical remission (CR), defined as cessation of all anti-inflammatory therapy with complete resolution of symptoms. Five machine learning survival models were used to calculate the likelihood of CR within 5 years and stratify patients into high-risk, intermediate-risk, and low-risk groups. RESULTS: Among the cohort, the mean age was 46 ± 15 years, and 205 (56%) were women. CR was achieved in 118 (32%) patients. The final model included steroid dependency, total number of recurrences, pericardial late gadolinium enhancement, age, etiology, sex, ejection fraction, and heart rate as the most important parameters. The model predicted the outcome with a C-index of 0.800 on the test set and exhibited a significant ability in stratification of patients into low-risk, intermediate-risk, and high-risk groups (log-rank test; P < 0.0001). CONCLUSIONS: We developed a novel risk-stratification model for predicting CR in RP. Our model can also aid in stratifying patients, with high discriminative ability. The use of an explainable machine learning model can aid physicians in making individualized treatment decision in RP patients.

Malignant Pericardial Effusion: A Systematic Review.

Background: Malignant pericardial effusion (Eff) is often asymptomatic and has an unknown prevalence, due to its occult presentation. The condition often is identified postmortem on autopsy, and it is associated with a poor prognosis. Given the late presentation of malignant pericardial Effs, a minimal volume of literature has examined the epidemiology, clinical characteristics, and outcomes of these complex patients. We conducted a systematic review to advance present understanding of this condition. Methods: A search of 4 databases resulted in 41 case reports meeting criteria. Inclusion criteria were being a patient aged > 18 years who presented with pericardial Eff in the setting of malignancy. Intervention was medical and/or surgical therapy, and the outcome was mortality. Results: For the 41 patients included, the median age was 54 years, and the majority were male patients (58%). Dyspnea was the leading symptom (90%), and cardiac tamponade was present in 78% of cases. Common cancers included lung, gastrointestinal, and renal neoplasms (59%). Pericardiocentesis occurred in 98% of cases, with a median fluid extraction volume of 1000 mL. Death occurred in 44%, primarily due to disease progression and/or metastasis. Conclusions: This study presents the largest systematic review on malignancy-induced pericardial Effs to date. Notably, solid tumours, and specifically lung adenocarcinomas, are common culprits. Malignant pericardial Effs are often severe, with a majority of patients presenting with cardiac tamponade. Overall, treatment options are limited, and the associated mortality rate is high.

Contexte: L'épanchement péricardique malin (EPM) est un état généralement asymptomatique, de prévalence inconnue en raison de son tableau clinique occulte. Il est souvent reconnu post-mortem, à l'autopsie, et est associé à un pronostic médiocre. En raison de la consultation tardive pour un EPM, les données publiées relatives à l'épidémiologie, aux caractéristiques cliniques et à l'issue de ces cas complexes sont limitées. Nous avons réalisé une analyse systématique dans le but d'élargir les connaissances sur cette affection. Méthodologie: Une recherche réalisée dans quatre bases de données a permis de repérer 41 rapports de cas qui répondaient aux critères de recherche. Les critères d'inclusion étaient les suivants : être âgé de plus de 18 ans; présenter un épanchement péricardique en présence d'un cancer; intervention pharmacologique et/ou chirurgicale; issue mortelle. Résultats: L'âge médian des 41 patients inclus était de 54 ans; la majorité d'entre eux étaient des hommes (58 %). Le symptôme principal était la dyspnée (90 %), et une tamponnade cardiaque était présente dans 78 % des cas. Les cancers les plus fréquents étaient le cancer du poumon, le cancer gastro-intestinal et les néoplasmes rénaux (59 %). Une péricardiocentèse a été réalisée dans 98 % des cas. Le volume de drainage médian était de 1 000 mL. Quarante-quatre pour cent des sujets sont décédés, principalement en raison de la progression de la maladie et/ou de métastases. Conclusions: Cette étude est la plus vaste analyse systématique réalisée à ce jour sur l'EPM. Les tumeurs solides, et plus particulièrement les adénocarcinomes pulmonaires, sont des causes fréquentes. L'EPM est souvent grave, la majorité des patients présentant une tamponnade cardiaque. Les traitements disponibles sont généralement limités, et le taux de mortalité associé est élevé.

Outcomes and Predictors of Stroke After Transcatheter Aortic Valve Replacement in the Cerebral Protection Device Era.

BACKGROUND: Studies have shown inconclusive results on the effectiveness of cerebral protection devices (CPDs) with transcatheter aortic valve replacement. We aimed to analyze the national statistics on stroke and other outcomes with CPD use. METHODS AND RESULTS: The Nationwide Readmissions Database (2017-2020) was queried to obtain data on patients undergoing transcatheter aortic valve replacement. Outcomes were compared between patients with a CPD and patients without a CPD. Of 271 804 patients undergoing transcatheter aortic valve replacement, CPD was used in 7.3% of patients. In a multivariable logistic regression analysis, CPD use was not associated with lower overall stroke rates (1.6% versus 1.9% without CPD; odds ratio, 0.95 [95% CI, 0.84-1.07]; P=0.364), but it was significantly associated with lower major stroke rates (1.2% versus 1.5% without CPD; odds ratio, 0.85 [95% CI, 0.74-0.98]; P=0.02). Patients with a CPD also had a shorter length of stay, higher routine discharges to home/self-care (74.9% versus 70.6%), and lower mortality rates (0.7% versus 1.3%). The 30-day (9.6% versus 11.7%) and 180-day (24.6% versus 28.2%) readmission rates were significantly lower in the CPD cohort. Among patients who developed stroke, patients with a CPD had more frequent routine discharges. Prior valve surgery was associated with the highest risk of overall and major stroke. CONCLUSIONS: CPD use during transcatheter aortic valve replacement was not independently associated with a lower risk of overall stroke but was associated with a lower risk of major stroke in a multivariable model. Data from future randomized trials that may offset any potential confounders in our study are required to help identify patients who would benefit from the use of these devices.

Port Catheter Fracture: A Silent Intrusion into the Right Ventricle.

Central venous port-a-catheters play a pivotal role in various medical procedures, yet they are associated with a spectrum of complications. Catheter fracture with cardiac migration is a rare complication, occurring in less than 1% of patients. Although not very common, it can cause severe issues, necessitating fragment removal. We present a case of spontaneous mediport fracture and migration in a patient with a history of Hodgkin's lymphoma and prior chemotherapy. He presented with nausea, vomiting, and tachycardia. Further evaluation revealed elevated total leukocyte count and labs consistent with diabetic ketoacidosis. He was diagnosed with new-onset diabetes mellitus. Imaging studies confirmed the presence of the fragmented catheter within the right ventricle. Although telemetry monitoring and electrocardiogram (EKG) did not detect arrhythmias, interventional radiology successfully removed the critical fragment from the right ventricle while leaving two smaller non-intravascular fragments in the neck. This case underscores the importance of early identification and interdisciplinary collaboration in managing port catheter fractures and migrations, even in the absence of typical symptoms.

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.

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.

"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.

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.

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.

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.

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.

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.

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.