Actual issues of an improvement of the medical aid delivery system in case of acute radiopathology in the Armed Forces of the Russian Federation. The article provides information on characteristics of the stage system of medical aid delivery in case of acute radiologic traumas. The authors formulated main directions of improvement of the system under modern conditions. It is shown that as a basis of its improvement may be considered the complex of measures, including formation of standardized clinical recommendations (treatment protocols) on medical care delivery to the wounded at different stages of medical evacuation, expanding of possibilities of special medical aid delivery to patients with acute radiopathology, including formation of mobile reserves for deployment of specialized units under conditions of mass admission of patients with severe forms of radiopathology; renewal of the training system for medical specialists working in the field of acute radiopathology; implementation of information technologies; improvement of interdepartmental interaction on the problems of medical consequences after radiologic emergency situations in peacetime.
Download full-text PDF |
Source |
---|
Ann Intern Med
January 2025
Department of Medicine, Division of Gastroenterology and Hepatology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts (S.M.J.A., M.L.).
Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease in the United States. It is characterized by steatosis in the liver and is potentially reversible. Risk factors include obesity, type 2 mellitus, and other metabolic disorders.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, RI, United States of America.
Introduction: Respiratory syncytial virus (RSV) is the leading cause of hospitalization among US infants. Characterizing service utilization during infant RSV hospitalizations may provide important information for prioritizing resources and interventions.
Objective: The objective of this study was to describe the procedures and services received by infants hospitalized during their first RSV episode in their first RSV season, in addition to what proportion of infants died during this hospitalization.
PLoS One
January 2025
Department of Computer Science and Technology, School of Computer Science, Northeast Electric Power University, Jilin, China.
Predicting Drug-Drug Interactions (DDIs) enables cost reduction and time savings in the drug discovery process, while effectively screening and optimizing drugs. The intensification of societal aging and the increase in life stress have led to a growing number of patients suffering from both heart disease and depression. These patients often need to use cardiovascular drugs and antidepressants for polypharmacy, but potential DDIs may compromise treatment effectiveness and patient safety.
View Article and Find Full Text PDFNeurology
January 2025
Department of Neurology, Massachusetts General Hospital, Boston.
Background And Objectives: Rolandic epilepsy (RE), the most common childhood focal epilepsy syndrome, is characterized by a transient period of sleep-activated epileptiform activity in the centrotemporal regions and variable cognitive deficits. Sleep spindles are prominent thalamocortical brain oscillations during sleep that have been mechanistically linked to sleep-dependent memory consolidation in animal models and healthy controls. Sleep spindles are decreased in RE and related sleep-activated epileptic encephalopathies.
View Article and Find Full Text PDFClin Oral Investig
January 2025
Department of Periodontology, Semmelweis University, Budapest, Hungary.
Objectives: To investigate the performance of a deep learning (DL) model for segmenting cone-beam computed tomography (CBCT) scans taken before and after mandibular horizontal guided bone regeneration (GBR) to evaluate hard tissue changes.
Materials And Methods: The proposed SegResNet-based DL model was trained on 70 CBCT scans. It was tested on 10 pairs of pre- and post-operative CBCT scans of patients who underwent mandibular horizontal GBR.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!