The dissemination of multidrug-resistant and hypervirulent clones across the Kingdom of Saudi Arabia.

is a Gram-negative bacterium associated with a wide range of community- and hospital-acquired infections. The emergence of clonal hypervirulent strains resistant to last-resort antimicrobial agents has become a global concern. The Kingdom of Saudi Arabia (KSA), with its diverse population and high tourism traffic, serves as a platform where the spread of multidrug-resistant (MDR) strains are facilitated.

Deep learning hybrid model ECG classification using AlexNet and parallel dual branch fusion network model.

Cardiovascular diseases are a cause of death making it crucial to accurately diagnose them. Electrocardiography plays a role in detecting heart issues such as heart attacks, bundle branch blocks and irregular heart rhythms. Manual analysis of ECGs is prone to mistakes and time consuming, underscoring the importance of automated methods.

Synthesis and improved optical, electrical, and dielectric properties of PEO/PVA/CuCoO nanocomposites.

This study investigates the development of novel nanocomposite films based on a blend of polyethylene oxide (PEO) and polyvinyl alcohol (PVA) loaded with varying weight percentages of copper cobaltite nanoparticles (CuCoO NPs). The primary objective was to fabricate these nanocomposites using a solution casting technique and explore the influence of CuCoO content on their structural, optical, electrical, and dielectric properties. Spinel-type CuCoO NPs were synthesized via the hydrothermal method and incorporated into the PEO/PVA blend.

Multi-organ immune-related adverse events from immune checkpoint inhibitors and their downstream implications: a retrospective multicohort study.

Background: Understanding co-occurrence patterns and prognostic implications of immune-related adverse events is crucial for immunotherapy management. However, previous studies have been limited by sample size and generalisability. In this study, we leveraged a multi-institutional cohort and a population-level database to investigate co-occurrence patterns of and survival outcomes after multi-organ immune-related adverse events among recipients of immune checkpoint inhibitors.

AI-Driven Real-Time Classification of ECG Signals for Cardiac Monitoring Using i-AlexNet Architecture.

The healthcare industry has evolved with the advent of artificial intelligence (AI), which uses advanced computational methods and algorithms, leading to quicker inspection, forecasting, evaluation and treatment. In the context of healthcare, artificial intelligence (AI) uses sophisticated computational methods to evaluate, decipher and draw conclusions from patient data. AI has the potential to revolutionize the healthcare industry in several ways, including better managerial effectiveness, individualized treatment regimens and diagnostic improvements.

Augmenting Radiological Diagnostics with AI for Tuberculosis and COVID-19 Disease Detection: Deep Learning Detection of Chest Radiographs.

In this research, we introduce a network that can identify pneumonia, COVID-19, and tuberculosis using X-ray images of patients' chests. The study emphasizes tuberculosis, COVID-19, and healthy lung conditions, discussing how advanced neural networks, like VGG16 and ResNet50, can improve the detection of lung issues from images. To prepare the images for the model's input requirements, we enhanced them through data augmentation techniques for training purposes.

The effect of cumulative night shift duties on insomnia, fatigue, and mental health in intensive care unit.

Background: Night shift duties are crucial in the ICU to ensure care continuity, where critically ill patients require round-the-clock care. However, cumulative night shift duties may disturb circadian rhythm, insomnia, fatigue, and depression, and require further elucidation.

Objectives: This study aims to examine the negative consequences of various night shift patterns on insomnia, fatigue, and mental health of ICU Workers.

De novo autoimmune connective tissue disease and mortality in patients treated with anti-programmed death receptor-1 and anti-programmed death-ligand 1 therapy: a population-level cohort study.

Using a population-level cohort analysis, our study demonstrates that, although rare, autoimmune cutaneous connective tissue diseases (AiCTDs) in the setting of immune checkpoint inhibitors (ICIs) are not associated with a greater risk of mortality and overall approach a statistically significant decrease in mortality when compared with patients treated with ICIs who do not experience cutaneous immune-related adverse events. These findings are significant and highly relevant to dermatologists and oncologists caring for ICI recipients as it adds to the limited information on development of cutaneous AiCTD following ICI administration, for which enhanced understanding is critical to improving the care for this challenging patient population.

Antibody-Drug Conjugates in the Treatment of Genitourinary Cancers: An Updated Review of Data.

The treatment landscape of genitourinary cancers has significantly evolved over the past few years. Renal cell carcinoma, bladder cancer, and prostate cancer are the most common genitourinary malignancies. Recent advancements have produced new targeted therapies, particularly antibody-drug conjugates (ADCs), due to a better understanding of the underlying oncogenic factors and molecular mechanisms involved.

Comprehensive plasma cytokine and chemokine profiling in prurigo nodularis reveals endotypes in Type 2 inflammation.

Prurigo nodularis (PN) is a chronic inflammatory skin disease that is associated with variability in peripheral blood eosinophil levels and response to T-helper 2 targeted therapies (Th2). Our objective was to determine whether circulating immune profiles with respect to type 2 inflammation differ by race and peripheral blood eosinophil count. Plasma from 56 PN patients and 13 matched healthy controls was assayed for 54 inflammatory biomarkers.

Knowledge, attitude, and adherence to coronavirus preventive measures among residents of the Kingdom of Saudi Arabia.

Since the SARS-CoV-2 virus, the virus that causes COVID-19, has been spreading globally, variants have emerged and been identified in many countries around the world. This descriptive cross-sectional study aimed to explore the level of knowledge, attitude, and adherence to coronavirus variant preventive measures among residents of the Kingdom of Saudi Arabia. This is a cross-sectional online survey that was conducted between April and November 2020 and involved the residents of the Kingdom of Saudi Arabia.

Use of 3-Dimensional Stereophotogrammetry to Detect Disease Progression in Craniofacial Morphea.

Importance: Objectively determining disease progression in craniofacial morphea (CM) is challenging, as clinical findings of disease activity are often lacking.

Objective: To evaluate the utility of 3-dimensional (3D) stereophotogrammetry in detecting disease progression in CM over time.

Design, Setting, And Participants: This prospective cohort study included 27 pediatric and adult patients with CM from 2 hospitals in Boston (Boston Children's Hospital and Brigham & Women's Hospital) consecutively enrolled from April 1, 2019, to March 1, 2023.