International prevalence patterns of low eGFR in adults aged 18-60 without traditional risk factors from a population-based cross-sectional disadvantaged populations eGFR epidemiology (DEGREE) study.

The disadvantaged populations eGFR (estimated glomerular filtration rate) epidemiology (DEGREE) study was designed to gain insight into the burden of chronic kidney disease (CKD) of undetermined cause (CKDu) using standard protocols to estimate the general-population prevalence of low eGFR internationally. Therefore, we estimated the age-standardized prevalence of eGFR under 60 ml/min per 1.73m in adults aged 18-60, excluding participants with commonly known causes of CKD; an ACR (albumin/creatinine ratio) over 300 mg/g or equivalent, or self-reported or measured (HT) hypertension or (DM) diabetes mellitus, stratified by sex and location.

'I Feel Disempowered Because I Could Not Do Anything': Clinical Facilitators' Perception of Violence Towards Nursing Students During Clinical Placement.

Aims: To explore clinical facilitators' understanding, experiences and perceptions of their role in supporting registered nurse students (RNS) who experience workplace violence (WPV) during clinical placement.

Design: An exploratory, qualitative design.

Methods And Data Source: Data were collected between September and November 2022 using semi-structured interviews of 1-h duration with 11 clinical facilitators working in South Australia.

Attainment of World Health Organization physical activity recommendations by Ecuadorian children: Analysis of social and anthropometrics factors in two distinct populations.

Daily adherence to WHO recommended physical activity guidelines has multiple health benefits in children and adolescents. Limited data from low and middle-income countries are available regarding adherence to WHO physical activity recommendations. This study aims to objectively measure physical activity intensities and explore associations with sociodemographic and anthropometric factors related to nonadherence to the WHO minimum physical activity recommendations.

Predicting remission following CBT for childhood anxiety disorders: a machine learning approach.

Background: The identification of predictors of treatment response is crucial for improving treatment outcome for children with anxiety disorders. Machine learning methods provide opportunities to identify combinations of factors that contribute to risk prediction models.

Methods: A machine learning approach was applied to predict anxiety disorder remission in a large sample of 2114 anxious youth (5-18 years).

Rurality and relative poverty drive acquisition of a stable and diverse gut microbiome in early childhood in a non-industrialized setting.

There are limited longitudinal data from non-industrialized settings on patterns and determinants of gut bacterial microbiota development in early childhood. We analysed epidemiological data and stool samples collected from 60 children followed from early infancy to 5 years of age in a rural tropical district in coastal Ecuador. Data were collected longitudinally on a wide variety of individual, maternal, and household exposures.