Nationwide Trends in Screen Time and Associated Risk Factors by Family Structures Among Adolescents, 2008-2022: Nationwide Cross-Sectional Study.

Background: Although understanding long-term trends in adolescent screen time and the influence of family structure is essential, there is a lack of research addressing these issues comprehensively.

Objective: This study aimed to conduct comprehensive investigations into adolescent screen time before and during the COVID-19 pandemic, with a particular focus on family structures.

Methods: This study used nationwide, large-scale data from the Korea Youth Risk Behavior Web-Based Survey from South Korea.

Associations Between Exercise Training, Physical Activity, Sedentary Behaviour and Mortality: An Umbrella Review of Meta-Analyses.

Background: Numerous studies support the association of exercise training, physical activity (PA) and sedentary behaviour (SB) with both mortality and morbidity outcomes. The results across studies have been inconsistent, and no umbrella reviews have yet been conducted on this topic.

Methods: We conducted an umbrella review of meta-analyses of observational studies by screening articles in PubMed/MEDLINE, EMBASE and Web of Science databases from inception to 30 April 2024.

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.

The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse events, with abnormal uterine bleeding (AUB) emerging as a reported concern in vaccinated females. We aimed to develop a machine learning (ML) model to predict post-vaccination AUB in women aged less than 50 years. A large-scale national cohort, the Korean Nationwide Cohort (K-COV-N cohort), was utilized, comprising over 7 million participants.

Disproportionality analysis from World Health Organization data on migraine-specific medications and cerebrovascular diseases.

Background: Migraine is a major cause of population ill health, with an estimated global prevalence of approximately 14-15%. However, given the limited research on the associations between specific migraine medications and adverse cerebrovascular events, this study aimed to investigate these relationships and their impact on cerebrovascular risk.

Methods: This study utilized data from the global pharmacovigilance database, which covers 170 countries from 1968 to 2024.

Machine Learning-Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study.

Background: To address gaps in global understanding of cultural and social variations, this study used a high-performance machine learning (ML) model to predict adolescent substance use across three national datasets.

Objective: This study aims to develop a generalizable predictive model for adolescent substance use using multinational datasets and ML.

Methods: The study used the Korea Youth Risk Behavior Web-Based Survey (KYRBS) from South Korea (n=1,098,641) to train ML models.

Dose-response association between physical activity and diagnosed hypertension in 2.4 million Korean population: Korea Community Health Survey 2009-2022.

Background: Hypertension, a significant risk factor for global public health, is well-known to be preventable and manageable through physical activity (PA). However, many studies suggest that excessive PA may not provide additional benefits. Thus, we aimed to conduct a quantitative analysis of the relationship between hypertension and PA levels.

Global burden of vaccine-associated kidney injury using an international pharmacovigilance database.

Global evidence on the association between vaccines and renal adverse events (AEs) is inconclusive. This pharmacovigilance study analyzed a total of 120,715,116 reports from VigiBase collected between 1967 and 2022. We evaluated the global reporting of acute kidney injury (AKI), glomerulonephritis (GN), and tubulointerstitial nephritis (TIN) and assessed disproportionate signals between vaccines and renal AEs using reporting odds ratios (ROR) and the lower limit of the 95% confidence interval of the information component (IC) in comparison with the entire database.

Development and Validation of a Machine Learning Algorithm for Predicting Diabetes Retinopathy in Patients With Type 2 Diabetes: Algorithm Development Study.

Background: Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. Machine learning (ML) systems can enhance DR in community-based screening. However, predictive power models for usability and performance are still being determined.

Long-term trends in the prevalence of cardiovascular-kidney-metabolic syndrome in South Korea, 2011-2021: a representative longitudinal serial study.

Background: The American Heart Association recently introduced a new framework, known as cardiovascular-kidney-metabolic (CKM) syndrome, aimed at the early prevention of cardiovascular disease. However, this syndrome has not been studied extensively outside of the United States. Thus, this study aimed to examine the long-term trends in CKM syndrome and its associated demographic features in South Korea.

Prediction model for type 2 diabetes mellitus and its association with mortality using machine learning in three independent cohorts from South Korea, Japan, and the UK: a model development and validation study.

Background: Type 2 diabetes mellitus (T2DM) is a significant global public health concern that has steadily increased over the past few decades. Thus, this study aimed to predict the incidence of T2DM within 5 years and the risk of mortality following the onset of T2DM. Data from three independent cohorts worldwide were used.

Vision impairment and associated daily activity limitation: A systematic review and meta-analysis.

Background: Vision impairment is a common disability that poses significant challenges to individuals' ability to perform activities essential for independent living, including activities of daily living (ADL) and instrumental activities of daily living (IADL). Despite extensive research, the extent and nature of these associations remain unclear, particularly across varying levels and types of vision impairment.

Objectives: This meta-analysis aims to estimate associations between vision impairment and difficulties with ADL and IADL.

Antibiofilm and Anticancer Activity of Multi-Walled Carbon Nanotubes Fabricated with Hot-Melt Extruded Astaxanthin-Mediated Synthesized Silver Nanoparticles.

Purpose: Multi-walled carbon nanotubes (MWCNTs) were used as carriers for silver nanoparticles (AgNPs). In this process, MWCNTs were coated with mesoporous silica (MWCNT-Silica) for uniform and regular loading of AgNPs on the MWCNTs. In addition, astaxanthin (AST) extract was used as a reducing agent for silver ions to enhance the antioxidant, antibiofilm, and anticancer activities of AgNPs.

Global, regional, and national trends in drug use disorder mortality rates across 73 countries from 1990 to 2021, with projections up to 2040: a global time-series analysis and modelling study.

Background: Drug use disorder (DUD) poses a major public health crisis globally, necessitating immediate attention to global trends and future projections to develop effective health policies and interventions. Thus, we aimed to estimate the global trends in DUD mortality rates from 1990 to 2021 and future projections of DUD deaths until 2040 across 73 countries.

Methods: In this time-series analysis and modelling study, we investigated the global trends in DUD mortality rates from 1990 to 2021 using the WHO Mortality Database and forecasted future trends through 2040.

External validation of an artificial intelligence model using clinical variables, including ICD-10 codes, for predicting in-hospital mortality among trauma patients: a multicenter retrospective cohort study.

Artificial intelligence (AI) is being increasingly applied in healthcare to improve patient care and clinical outcomes. We previously developed an AI model using ICD-10 (International Classification of Diseases, Tenth Revision) codes with other clinical variables to predict in-hospital mortality among trauma patients from a nationwide database. This study aimed to externally validate the performance of the AI model.

Antipsychotic use during pregnancy and outcomes in pregnant individuals and newborns.

Background: Despite the increasing use of antipsychotics during pregnancy, comprehensive evaluations of their individual safety profiles using global data remain limited. This study aimed to assess the safety of various antipsychotics during pregnancy by comparing them to quetiapine, which has a relatively large body of safety data.

Method: Utilizing the World Health Organization pharmacovigilance database (1968-2023; n = 131,255,418 reports), we identified 11,406 reports of antipsychotic exposure during pregnancy.

Associations between weight-control methods and depression among Korean adolescents: a study based on a national dataset.

Background/objectives: The increasing prevalence of overweight and obesity has become a significant global burden, with more than 40% of the global adult population attempting to lose weight. Previous studies on the impact of weight-control methods on mental health, especially among adolescents, are limited. Thus, this study aimed to investigate the association between various weight-control methods and depression among adolescents, with the goal of informing healthier weight management decisions and promoting effective methods.

Racial Discrimination and Multiple Health Outcomes: An Umbrella Review of Systematic Reviews and Meta-Analyses.

Objective: We aimed to systematically investigate the associations between racial discrimination and various health outcomes and to evaluate the certainty of evidence from existing meta-analyses of observational studies.

Method: We systemically searched the associations between racial discrimination and health outcomes for PubMed/MEDLINE, Embase, WoS, and Google Scholar up until January 31, 2024. Notably, the included studies were predominantly conducted in the USA and Europe, limiting the generalizability of our findings to a global context.

Global, Regional, and National Trends in Liver Disease-Related Mortality Across 112 Countries From 1990 to 2021, With Projections to 2050: Comprehensive Analysis of the WHO Mortality Database.

Background: Liver disease causes over two million deaths annually worldwide, comprising approximately 4% of all global fatalities. We aimed to analyze liver disease-related mortality trends from 1990 to 2021 using the World Health Organization (WHO) Mortality Database and forecast global liver disease-related mortality rates up to 2050.

Methods: This study examined age-standardized liver disease-related death rates from 1990 to 2021, employing data from the WHO Mortality Database across 112 countries across five continents.

Global Burden of Vaccine-Associated Chronic Urticaria, 2010-2023: From the Global Pharmacovigilance Database.

Purpose: The etiology and pathophysiology of vaccine-associated chronic urticaria (CU) remain unclear, particularly during the coronavirus disease 2019 (COVID-19) pandemic. Thus, this study aimed to comprehensively investigate the global burden and long-term trends of vaccine-associated CU, with a focus on the associated vaccines and the distribution of cases across different age groups and sexes.

Methods: Using data from the World Health Organization international pharmacovigilance database (VigiBase), which encompasses reports from 156 countries and territories between 1968 and 2023, we systematically analyzed the global burden and long-term trends in vaccine-associated CU reports (total individual case safety reports = 131,255,418).

Global trends of secondhand smoke exposure among young adolescents from 27 countries, 2003-2021: findings from the World Health Organization database.

The issue of adolescent secondhand smoke (SHS) is globally significant, given that it serves as a preventable risk factor for disease prevalence and mortality rates among youth. This study evaluates trends in adolescent SHS across 27 countries from 2003 to 2021, aiming to identify global variations and sex-specific differences, providing insights for future policy recommendations. The data for this study were collected from the Global School-based Student Health Survey conducted by the World Health Organization, 2003-2021.

Hot-Melt Extrusion Drug Delivery System-Formulated Extracts Regulate Inflammation and Oxidative Stress in Lipopolysaccharide-Stimulated Macrophages.

contains valuable bioactive compounds, including astaxanthin, proteins, and fatty acids. Astaxanthin is known for its various health benefits, such as preserving the redox balance and reducing inflammation. However, its low stability and poor water solubility present challenges for various applications.