Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11306542 | PMC |
| http://dx.doi.org/10.1007/s00134-024-07491-8 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Food insecurity and early childhood development among children 24-59 months in Nigeria: A multilevel mixed effects modelling of the social determinants of health inequities.
PLoS One
January 2025
College of Public Health, University of South Florida, Tampa, Florida, United States of America.
Food insecurity (FI) has been identified as a determinant of child development, yet evidence quantifying this association using the newly developed Early Childhood Development Index 2030 (ECDI2030) remains limited. Herein, we provide national estimates of early childhood development (ECD) risks using the ECDI2030 and examined to what extent FI was associated with ECD among children aged 24-59 months in Nigeria. This population based cross-sectional analyses used data from the UNICEF-supported 2021 Multiple Indicator Cluster Survey in Nigeria.
View Article and Find Full Text PDFMcGrath MAC Versus Three-Dimensional Printed Video Laryngoscopes: A Randomized, Manikin-Simulated Noninferiority Controlled Study with Medical Students.
Anesth Analg
February 2025
From the Department of Surgical Specialties and Anesthesiology of São Paulo State University (UNESP), Medical School, Botucatu, Brazil.
Background: Proficiency in endotracheal intubation (ETI) is essential for medical professionals and its training should start at medical schools; however, large caseload may be required before achieving an acceptable success rate with direct laryngoscopy. Video laryngoscopy has proven to be an easier alternative for intubation with a faster learning curve, but its availability in medical training may be an issue due to its high market prices. We devised a low-cost 3-dimensionally printed video laryngoscope (3DVL) and performed a randomized trial to evaluate if the intubation success rate on the first attempt with this device is noninferior to a standard commercially available video laryngoscope (STVL).
View Article and Find Full Text PDFHeart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study.
Eur Heart J
January 2025
Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT 06510, USA.
Background And Aims: Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF risk.
Methods: Across multinational cohorts in the Yale New Haven Health System (YNHHS), UK Biobank (UKB), and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), individuals without baseline HF were followed for the first HF hospitalization.
Machine learning-based blood pressure estimation using impedance cardiography data.
Acta Physiol (Oxf)
February 2025
Institute of Physiology, Center for Space Medicine and Extreme Environments Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Objective: Accurate blood pressure (BP) measurement is crucial for the diagnosis, risk assessment, treatment decision-making, and monitoring of cardiovascular diseases. Unfortunately, cuff-based BP measurements suffer from inaccuracies and discomfort. This study is the first to access the feasibility of machine learning-based BP estimation using impedance cardiography (ICG) data.
View Article and Find Full Text PDFRegional-specific trends of PM and O temperature sensitivity in the United States.
NPJ Clim Atmos Sci
January 2025
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332 USA.
Climate change poses direct and indirect threats to public health, including exacerbating air pollution. However, the influence of rising temperature on air quality remains highly uncertain in the United States, particularly under rapid reduction in anthropogenic emissions. Here, we examined the sensitivity of surface-level fine particulate matter (PM) and ozone (O) to summer temperature anomalies in the contiguous US as well as their decadal changes using high-resolution datasets generated by machine learning.
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!