Advancing In Silico Clinical Trials for Regulatory Adoption and Innovation.

The evolution of information and communication technologies has affected all fields of science, including health sciences. However, the rate of technological innovation adoption by the healthcare sector has been historically slow, compared to other industrial sectors. Innovation in computer modeling and simulation approaches has changed the landscape in biomedical applications and biomedicine, paving the way for their potential contribution in reducing, refining, and partially replacing animal and human clinical trials.

Mechanical Barrier for Prevention of Dislodged Stent Embolization in Saphenous Vein Graft.

Percutaneous coronary interventions in vein grafts can be quite challenging, and many complications can occur during the procedure. We present a case of stent dislodgment during percutaneous coronary intervention in a vein graft. It was migrating to the proximal part of the graft and a covered stent was placed in the native vessel in order to isolate the graft.

The Role of Prognostic Scores in Assessing the Prognosis of Patients Admitted in the Cardiac Intensive Care Unit: Emphasis on Heart Failure Patients.

: Patient care in Cardiac Intensive Care Units (CICU) has evolved but data on patient characteristics and outcomes are sparse. This retrospective observational study aimed to define clinical characteristics and risk factors of CICU patients, their in-hospital and 30-day mortality, and compare it with established risk scores. : Consecutive patients ( = 294, mean age 70 years, 74% males) hospitalized within 15 months were studied; APACHE II, EHMRG, GWTG-HF, and GRACE II were calculated on admission.

In-Hospital versus Out-of-Hospital Pulmonary Embolism: Clinical Characteristics, Biochemical Markers and Echocardiographic Indices.

Background: A significant proportion of pulmonary embolisms (PEs) occurs in patients during hospitalisation for another reason. However, limited data regarding differences between out-of-hospital PE (OHPE) and in-hospital PE (IHPE) is available. We aimed to compare these groups regarding their clinical characteristics, biochemical markers, and echocardiographic indices.

Absolute zero-contrast percutaneous coronary interventions: An intravascular ultrasound-guided case series and literature review.

Purpose: Contrast media (CM)-associated adverse effects including mainly acute kidney injury and hypersensitivity reactions still remain a significant treatment burden to vulnerable patients requiring percutaneous coronary intervention (PCI). The complete omission of CM administration accompanied by intravascular ultrasound (IVUS) guidance may offer an appropriate revascularization treatment.

Methods: We hereby present a case series of four patients with challenging coronary lesions and relative/absolute contraindications to CM use [(hypersensitivity reaction owning to CM, history of contrast-induced acute kidney injury, solitary kidney, or advanced chronic kidney disease (CKD)] who underwent absolute zero-contrast IVUS-guided PCI following a predetermined protocol.

The Potential Role of Salivary NT-proBNP in Heart Failure.

Background: Serum natriuretic peptides (NPs) have an established role in heart failure (HF) diagnosis. Saliva NT-proBNP that may be easily acquired has been studied little.

Methods: Ninety-nine subjects were enrolled; thirty-six obese or hypertensive with dyspnoea but no echocardiographic HF findings or raised NPs served as controls, thirteen chronic HF (CHF) patients and fifty patients with acute decompensated HF (ADHF) requiring hospital admission.

What is the real incidence of right ventricular affection in patients with acute pulmonary embolism?

Background: Echocardiographic markers of right ventricular dysfunction or pressure overload (RV) have been used in risk assessment of patients with acute pulmonary embolism (APE). Nevertheless, the role of echocardiography in these patients is incompletely determined. We evaluated the right ventricular function using 'non-conventional' markers of RV in patients with APE.

The role of endothelial shear stress, shear stress gradient, and plaque topography in plaque erosion.

Background And Aims: Plaque erosion is a common underlying cause of acute coronary syndromes. The role of endothelial shear stress (ESS) and endothelial shear stress gradient (ESSG) in plaque erosion remains unknown. We aimed to determine the role of ESS metrics and maximum plaque slope steepness in plaques with erosion versus stable plaques.

The Role of Myocardial Perfusion Imaging in the Prediction of Major Adverse Cardiovascular Events at 1 Year Follow-Up: A Single Center's Experience.

Background: Myocardial perfusion imaging via single-photon emission computed tomography (SPECT MPI) is a well-established method of diagnosing coronary artery disease (CAD). The purpose of this study was to assess the role of SPECT MPI in predicting major cardiovascular events.

Methods: The study population was composed of 614 consecutive patients (mean age: 67 years, 55% male) referred for SPECT MPI due to symptoms of stable CAD.

Coronary microcirculation and left ventricular diastolic function but not myocardial deformation indices are impaired early in patients with chronic kidney disease.

Aim: To investigate abnormalities in myocardial strain and classic echocardiographic indices and coronary flow reserve (CFR), in younger versus older CKD patients.

Methods: Sixty consecutive CKD patients (<60 years old n = 30, ≥60 years old n = 30) and 30 healthy controls (age- and gender-matched with younger CKD patients) were recruited. An echocardiographic assessment including myocardial strain indices (i.

An All-in-One Tool for 2D Atherosclerotic Disease Assessment and 3D Coronary Artery Reconstruction.

Diagnosis of coronary artery disease is mainly based on invasive imaging modalities such as X-ray angiography, intravascular ultrasound (IVUS) and optical coherence tomography (OCT). Computed tomography coronary angiography (CTCA) is also used as a non-invasive imaging alternative. In this work, we present a novel and unique tool for 3D coronary artery reconstruction and plaque characterization using the abovementioned imaging modalities or their combination.

Cerebro-/Cardiovascular Collateral Damage During the COVID-19 Pandemic: Fact or Fiction?

Numerous observational studies have identified a decline in cerebro-/cardiovascular (CV) admissions during the initial phase of the COVID-19 pandemic. Recent studies and meta-analyses indicated that the overall decrease was smaller than that found in initial studies during the first months of 2020. Two years later we still do not have clear evidence about the potential causes and impacts of the reduction of CV hospitalizations during the COVID-19 pandemic.

Systemic Thrombolysis for Treatment of Acute Life-threatening Pulmonary Embolism During Cesarean Section Followed by Post-partum Rescue Hysterectomy: A Case Report and Review of the Literature.

Background/aim: Acute pulmonary embolism during cesarean section is extremely rare and only a limited number of cases have been reported in literature. The aim of this study was to report a case of acute high risk pulmonary embolism during elective cesarean section treated with systemic thrombolysis and discuss the multidisciplinary management in both early recognition and prompt treatment.

Case Report: A 39-year-old, G5P2, ASA II parturient presented for repeat cesarean section under general anesthesia.

Segmentation of left atrium using CT images and a deep learning model.

The left atrium (LA) is one of the cardiac cavities with the most complex anatomical structures. Its role in the clinical diagnosis and patient's management is critical, as it is responsible for the atrial fibrillation, a condition that promotes the thrombogenesis inside the left atrial appendage. The development of an automated approach for LA segmentation is a demanding task mainly due to its anatomical complexity and the variation of its shape among patients.

Machine Learning Models for Cardiovascular Disease Events Prediction.

Cardiovascular diseases (CVDs) are among the most serious disorders leading to high mortality rates worldwide. CVDs can be diagnosed and prevented early by identifying risk biomarkers using statistical and machine learning (ML) models, In this work, we utilize clinical CVD risk factors and biochemical data using machine learning models such as Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Naïve Bayes (NB), Extreme Grading Boosting (XGB) and Adaptive Boosting (AdaBoost) to predict death caused by CVD within ten years of follow-up. We used the cohort of the Ludwigshafen Risk and Cardiovascular Health (LURIC) study and 2943 patients were included in the analysis (484 annotated as dead due to CVD).

Histopathological evaluation of a retinoic acid eluting stent in a rabbit iliac artery model.

This study aimed to evaluate the safety and efficacy of innovative retinoic acid (RA) eluting stents with bioabsorbable polymer. Sixty stents divided in ten groups were implanted in the iliac arteries of 30 rabbits. Two polymers ("A", poly (lactic-co-glycolic acid) and "B", polylactic acid), and three doses ("Low", "Medium" and "High") of RA (groups: AL, AM, AH, BL, BM, BH) were used on cobalt chromium stents (Rontis Corporation), one group of bare stent (C), one group (D) of Everolimus eluting stent (Xience-Pro, Abbot Vascular), and two groups of Rontis Everolimus eluting stents coated with polymer A (EA) and B (EB).

Machine Learning Coronary Artery Disease Prediction Based on Imaging and Non-Imaging Data.

The prediction of obstructive atherosclerotic disease has significant clinical meaning for the decision making. In this study, a machine learning predictive model based on gradient boosting classifier is presented, aiming to identify the patients of high CAD risk and those of low CAD risk. The machine learning methodology includes five steps: the preprocessing of the input data, the class imbalance handling applying the Easy Ensemble algorithm, the recursive feature elimination technique implementation, the implementation of gradient boosting classifier, and finally the model evaluation, while the fine tuning of the presented model was implemented through a randomized search optimization of the model's hyper-parameters over an internal 3-fold cross-validation.