24-h continuous non-invasive multiparameter home monitoring of vitals in patients with Rett syndrome by an innovative wearable technology: evidence of an overlooked chronic fatigue status.

Background: Sleep is disturbed in Rett syndrome (RTT), a rare and progressive neurodevelopmental disorder primarily affecting female patients (prevalence 7.1/100,000 female patients) linked to pathogenic variations in the X-linked methyl-CpG-binding protein 2 () gene. Autonomic nervous system dysfunction with a predominance of the sympathetic nervous system (SNS) over the parasympathetic nervous system (PSNS) is reported in RTT, along with exercise fatigue and increased sudden death risk.

Machine learning-enhanced noninvasive prenatal testing of monogenic disorders.

Objective: Single-nucleotide variants (SNVs) are of great significance in prenatal diagnosis as they are the leading cause of inherited single-gene disorders (SGDs). Identifying SNVs in a non-invasive prenatal screening (NIPS) scenario is particularly challenging for maternally inherited SNVs. We present an improved method to predict inherited SNVs from maternal or paternal origin in a genome-wide manner.

Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review.

Worldwide, population aging and unhealthy lifestyles have increased the incidence of high-risk health conditions such as cardiovascular diseases, sleep apnea, and other conditions. Recently, to facilitate early identification and diagnosis, efforts have been made in the research and development of new wearable devices to make them smaller, more comfortable, more accurate, and increasingly compatible with artificial intelligence technologies. These efforts can pave the way to the longer and continuous health monitoring of different biosignals, including the real-time detection of diseases, thus providing more timely and accurate predictions of health events that can drastically improve the healthcare management of patients.

Implementation of a Personalized Digital App for Pediatric Preanesthesia Evaluation and Education: Ongoing Usability Analysis and Dynamic Improvement Scheme.

Background: Preanesthesia evaluation is a basic practice preceding any surgical procedure, aimed at tailoring individualized anesthetic plans for patients, improving safety, and providing patients with educational knowledge and tools in preparation for the surgery day. In the last 2 decades, eHealth and mobile health (mHealth) settings have gradually replaced part of the face-to-face encounters as the platform for preanesthesia communication between doctor and patient, yielding a range of benefits as demonstrated in recent publications. Nevertheless, there is a lack of studies examining the effectiveness of surgical mHealth apps focusing on the pediatric preanesthetic setting and addressing their usability among families.

Changes in High-Frequency Intracardiac Electrogram Indicate Cardiac Ischemia.

High-frequency QRS (HFQRS) analysis of surface ECG is a reliable marker of cardiac ischemia (CI). This study aimed to assess the response of HFQRS signals from standard intracardiac electrodes (iHFQRS) to CI in swine and compare them with conventional ST-segment deviations. Devices with three intracardiac leads were implanted in three swine in a controlled environment.

High-frequency QRS electrocardiogram analysis during exercise stress testing for detecting ischemia.

Introduction: ECG stress testing is an inexpensive and non-invasive detector of myocardial ischemia; addition of high-frequency QRS analysis (HFQRS) may improve accuracy. This study compared HFQRS during exercise in patients with and without ischemia as defined by multiple criteria.

Material And Methods: High-resolution ECGs were recorded for 139 patients undergoing T99-sestamibi/T201-thallium stress testing.