Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Charlson comorbidity index has no incremental value for mortality risk prediction in nursing home residents with COVID-19 disease.
BMC Geriatr
January 2025
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Background: During the COVID-19 pandemic, nursing home (NH) residents faced the highest risk of severe COVID-19 disease and mortality. Due to their frailty status, comorbidity burden can serve as a useful predictive indicator of vulnerability in this frail population. However, the prognostic value of these cumulative comorbidity scores like the Charlson comorbidity index (CCI) remained unclear in this population.
View Article and Find Full Text PDFDevelopment and validation of a frailty risk model for patients with mild cognitive impairment.
Sci Rep
January 2025
School of Medicine, Yan'an University, Yan'an, 716000, China.
The study aims to develop and validate an effective model for predicting frailty risk in individuals with mild cognitive impairment (MCI). The cross-sectional analysis employed nationally representative data from CHARLS 2013-2015. The sample was randomly divided into training (70%) and validation sets (30%).
View Article and Find Full Text PDFSignificance of supervision sampling in control of communicable respiratory disease simulated by a new model during different stages of the disease.
Sci Rep
January 2025
School of Mathematics and Statistics, Central South University, Changsha, 410083, China.
The coronavirus disease 2019 (COVID-19) interventions in interrupting transmission have paid heavy losses politically and economically. The Chinese government has replaced scaling up testing with monitoring focus groups and randomly supervising sampling, encouraging scientific research on the COVID-19 transmission curve to be confirmed by constructing epidemiological models, which include statistical models, computer simulations, mathematical illustrations of the pathogen and its effects, and several other methodologies. Although predicting and forecasting the propagation of COVID-19 are valuable, they nevertheless present an enormous challenge.
View Article and Find Full Text PDFAssociation between triglyceride-glucose index and carotid atherosclerosis in Chinese steelworkers: a cross-sectional study.
Sci Rep
January 2025
School of Public Health, North China University of Science and Technology, No. 21 Bohai Avenue, Caofeidian New City, Tangshan City, 063210, Hebei Province, China.
This study aims to explore the association between the triglyceride-glucose (TyG) index and the risk of carotid atherosclerosis (CAS) among Chinese steelworkers. This is a cross-sectional study involving a total of 4,203 Chinese steelworkers. The TyG index was calculated using the formula: TyG = Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL) / 2].
View Article and Find Full Text PDFA comparative methodological approach for argan forest classification using Landsat imagery.
Environ Monit Assess
January 2025
LMFE, Faculty of Sciences Semlalia, Cadi Ayyad University, 40000, Marrakesh, Morocco.
In the last decades, natural and anthropogenic pressures have caused observable changes in the argan landscape despite its significance in Morocco. Remote sensing data can be used to monitor these changes over time and provide information on vegetation health and land cover changes. This study assesses the performance of supervised methods (support vector machine, maximum likelihood, and minimum distance) and unsupervised classification method (Isodata) for mapping the argan forest in the Smimou area of Essaouira province using remote sensing data from Landsat-5 and Landsat-8 (1985 and 2019).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!