The aim of this study was to prioritise a set of indicators to measure World Health Organization (WHO) quality-of-care standards for small and/or sick newborns (SSNB) in health facilities. The hypothesis is that monitoring prioritised indicators can support accountability mechanisms, assess and drive progress, and compare performance in quality-of-care (QoC) at subnational levels.

Prospective, iterative, deductive, stepwise process to prioritise a list of QoC indicators organised around the WHO Standards for improving the QoC for small and sick newborns in health facilities. A technical working group (TWG) used an iterative four-step deductive process: (1) articulation of conceptual framework and method for indicator development; (2) comprehensive review of existing global SSNB-relevant indicators; (3) development of indicator selection criteria; and (4) selection of indicators through consultations with a wide range of stakeholders at country, regional and global levels.

The indicators are prioritised for inpatient newborn care (typically called level 2 and 3 care) in high mortality/morbidity settings, where most preventable poor neonatal outcomes occur.

The TWG included 24 technical experts and leaders in SSNB QoC programming selected by WHO. Global perspectives were synthesised from an online survey of 172 respondents who represented different countries and levels of the health system, and a wide range of perspectives, including ministries of health, research institutions, technical and implementing partners, health workers and independent experts.

The 30 prioritised SSNB QoC indicators include 27 with metadata and 3 requiring further development; together, they cover all eight standard domains of the WHO quality framework. Among the established indicators, 10 were adopted from existing indicators and 17 adapted. The list contains a balance of indicators measuring inputs (n=6), processes (n=12) and outcome/impact (n=9).

The prioritised SSNB QoC indicators can be used at health facility, subnational and national levels, depending on the maturity of a country’s health information system. Their use in implementation, research and evaluation across diverse contexts has the potential to help drive action to improve quality of SSNB care. WHO and others could use this list for further prioritisation of a core set.

The predisposition to food allergy development and the induction of allergen-specific immune responses appears to be initiated early in infancy. Early exposure to food allergens, such as peanut and cashew nut, via human milk is likely important in initiating oral tolerance and reducing risk of food allergy development. This trial aims to determine if the risk of developing peanut and cashew nut allergy during infancy can be reduced by a high peanut and cashew nut maternal diet during lactation.

This is a multisite, parallel, two-arm (1:1 allocation), single-blinded (outcome assessors, statistical analyst and investigators), randomised controlled trial. Target sample size is 4412 participants (2206 per group). Women (aged 18–50 years) with a singleton pregnancy, who are planning to breastfeed and do not have peanut and/or cashew nut allergies are eligible to participate. After obtaining written informed consent, participants are randomised to either a high peanut and cashew nut diet (at least 60 peanuts and 40 cashew nuts per week) or a low peanut and cashew nut diet (no more than 20 peanuts and 12 cashew nuts per week). Participants are asked to follow their allocated diet from birth to 6 months postnatal. Individual lactation consultant advice and support is provided as required. The study’s primary outcome is food challenge proven IgE-mediated peanut and/or cashew nut allergy during infancy (0–18 months). Key secondary outcomes include infant sensitisation to peanut and/or cashew nut. Analyses will be performed on an intention-to-treat basis according to a prespecified statistical analysis plan.

Ethical approval has been granted from the Western Australian Child and Adolescent Health Service Human Research Ethics Committee (approval number RGS0000006685). Trial results will be presented at scientific conferences and published in peer-reviewed journals.

Australian New Zealand Clinical Trials Registry (ACTRN ACTRN12624000134527)

The TRAjectory of knee heaLth in runners (TRAIL) study is a prospective cohort study investigating the long-term knee health trajectories of runners with and without a heightened osteoarthritis risk. This study aims to describe the recruitment results and baseline characteristics of the TRAIL cohort.

Runners aged 18–50 years and running ≥3 times and ≥10 km per week on average in the past 6 months were eligible. Participants were recruited via running podcasts, running clubs and social media between July 2020 and August 2023. Data were collected at study enrolment and at a face-to-face baseline testing session, which occurred a median of 33 weeks (IQR 18 to 86 weeks) after enrolment. Follow-up data collection is ongoing.

Out of 462 runners who completed an online registration form, 268 runners enrolled, of which 135 had a history of knee surgery (46% females) and 133 were non-surgical controls (50% females). 60% of the surgery group had undergone anterior cruciate ligament reconstruction, 33% meniscus and/or cartilage surgery, and 7% other knee surgery. 54 participants previously enrolled were unable to continue in the study before attending baseline data collection. Of the 214 runners who remained in the study and attended baseline data collection, 108 had a history of knee surgery (49% females) and 106 did not have a history of knee surgery (51% females).

Participants will be followed for 10 years through ongoing patient-reported outcomes and continuous monitoring of training loads using wearable devices. At baseline, 4- and 10-year follow-up, knee MRI and knee-health patient-reported outcomes will be collected to evaluate structural and symptomatic knee osteoarthritis progression. Data will inform guidelines for safe running practices and rehabilitation post-knee surgery.

Women with gestational diabetes mellitus (GDM) are at seven-fold to ten-fold increased risk of type 2 diabetes mellitus (T2DM) when compared with those who experience a normoglycaemic pregnancy, and the cumulative incidence increases with the time of follow-up post birth. This protocol outlines the development and validation of a risk prediction model assessing the 5-year and 10-year risk of T2DM in women with a prior GDM diagnosis.

Data from all birth mothers and registered births in Victoria and South Australia, retrospectively linked to national diabetes data and pathology laboratory data from 2008 to 2021, will be used for model development and validation of GDM to T2DM conversion. Candidate predictors will be selected considering existing literature, clinical significance and statistical association, including age, body mass index, parity, ethnicity, history of recurrent GDM, family history of T2DM and antenatal and postnatal glucose levels. Traditional statistical methods and machine learning algorithms will explore the best-performing and easily applicable prediction models. We will consider bootstrapping or K-fold cross-validation for internal model validation. If computationally difficult due to the expected large sample size, we will consider developing the model using 80% of available data and evaluating using a 20% random subset. We will consider external or temporal validation of the prediction model based on the availability of data. The prediction model’s performance will be assessed by using discrimination (area under the receiver operating characteristic curve, calibration (calibration slope, calibration intercept, calibration-in-the-large and observed-to-expected ratio), model overall fit (Brier score and Cox-Snell R2) and net benefit (decision curve analysis). To examine algorithm equity, the model’s predictive performance across ethnic groups and parity will be analysed. Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis-Artificial Intelligence (TRIPOD+AI) statements will be followed.

Ethics approvals have been received from Deakin University Human Research Ethics Committee (2021–179); Monash Health Human Research Ethics Committee (RES-22-0000-048A); the Australian Institute of Health and Welfare (EO2022/5/1369); the Aboriginal Health Research Ethics Committee of South Australia (SA) (04-23-1056); in addition to a Site-Specific Assessment to cover the involvement of the Preventative Health SA (formerly Wellbeing SA) (2023/SSA00065). Project findings will be disseminated in peer-reviewed journals and at scientific conferences and provided to relevant stakeholders to enable the translation of research findings into population health programmes and health policy.

The use of different electronic devices is increasing among students due to rapid advancements in digital technology. The prevalence of computer vision syndrome (CVS) has increased among school children after the COVID-19 pandemic. Different symptoms of CVS, such as eye strain, headache, blurred vision and visual discomfort, have become major public health problems. This study aimed to assess the prevalence of CVS, identify its risk factors, evaluate parental awareness and examine the impact of COVID-19 on screen time among primary school children in Dhaka, Bangladesh.

Primary data were collected from the parents of 500 primary school students aged 5–14 years using a convenience sampling method through face-to-face interviews. A structured questionnaire was administered to collect demographic information, screen usage patterns, ambient conditions and details regarding the children’s academic performance. The Computer Vision Syndrome Questionnaire scale was used to assess the prevalence and severity of CVS. Various statistical analyses were performed, including ² tests, Fisher’s exact tests and logistic regression, to identify significant predictors of CVS (p

Findings revealed that 16.4% of children were affected by CVS, with key risk factors including age, school year, maternal education and daily screen time. Children with CVS commonly reported headaches and itchy eyes, which negatively impacted their academic performance. Surprisingly, 67.4% of parents were unaware of CVS, and the odds of developing CVS were 3.74 times higher among children using electronic devices for more than 4 hours daily.

The study explored the low prevalence of CVS among primary school students in Dhaka, Bangladesh. Several symptoms, like headaches and eye discomfort, were identified that impaired their academic performance. Additionally, many parents were largely unaware of CVS. Therefore, it is necessary to take proper strategies to be aware of the consequences and lessen the prevalence of CVS to save our future generation.

Diabetes is already known as a risk factor for developing dementia. Multiple factors contribute to this association: presence of microvascular and macrovascular complications, chronic inflammation, hyperglycaemia, hypoglycaemia and hyperinsulinemia.1

Older adult patients often present with multimorbidities, polypharmacy, malnutrition, sarcopenia, longer duration of diabetes and renal and hepatic dysfunction. Furthermore, low education level, high blood pressure, dyslipidemia, obstructive...