Machine Learning Models for the Early Real-Time Prediction of Deterioration in Intensive Care Units-A Novel Approach to the Early Identification of High-Risk Patients.

Predictive machine learning models have made use of a variety of scoring systems to identify clinical deterioration in ICU patients. However, most of these scores include variables that are dependent on medical staff examining the patient. We present the development of a real-time prediction model using clinical variables that are digital and automatically generated for the early detection of patients at risk of deterioration.

Real-world efficacy and safety of dupilumab for paediatric atopic dermatitis: a multicentre retrospective study.

Background: Real-world data regarding the use of dupilumab in children with atopic dermatitis (AD) are limited.

Objectives: To evaluate the real-world efficacy of dupilumab in children with moderate-to-severe AD over an extended follow-up period.

Methods: This was a retrospective study of patients (≤ 18 years) with moderate-to-severe AD treated with dupilumab in four Israeli tertiary centres.

Rebound Growth of Infantile Hemangiomas after Propranolol versus Atenolol Treatment: A Retrospective Study.

Introduction: Propranolol is the first-line treatment for complicated infantile hemangioma (IH). Rebound growth following propranolol discontinuation is reported in 6-25% of patients. Atenolol is considered an effective alternative to propranolol.

Ferritin is closely associated with microglia in amyotrophic lateral sclerosis.

Iron deposition is a hallmark of amyotrophic lateral sclerosis (ALS) and has been strongly implicated in its pathogenesis. As a byproduct of cellular oxidative stress, iron dysregulation modifies basal levels of the regulatory iron-binding protein ferritin. Examination of thoracic and lumbar spinal cord tissues found increased ferritin immunostaining in white matter axons that corresponded to areas of increased microgliosis in 8 ALS patients versus 8 normal subjects.