The over 14 million African children who are HIV-exposed but uninfected (CHEU) are at risk for poor health outcomes, including neurodevelopmental conditions such as autism; however, no study to date has examined autism in CHEU in Africa, where the vast majority of these children live. Scalable diagnostic and neurobehavioural tools, including powerful, low-cost approaches such as eye-tracking, for detection and study of mechanistic neural processes are necessary to advance autism research in these settings. The objective of this study is to examine autism diagnostic outcomes and eye-tracking biomarkers in relation to CHEU while at the same time building capacity for neuro-health research in Kenya.

This study will leverage a longitudinally assessed cohort of CHEU and children who are HIV-unexposed and uninfected (CHUU) with well characterised HIV-related and contextual exposures. We will first determine and compare autism diagnostic outcomes between young CHEU and CHUU across a large cohort (n=850) of Kenyan children using research-grade autism assessment tools, and, second, determine whether neurobehavioural eye-tracking markers predict autism outcomes across this cohort.

Human subjects approvals have been obtained from Moi University Institutional Review and Ethics Committee (IREC; IREC/909/2024; Approval #0004835), Kenya’s National Commission for Science, Technology and Innovation (NACOSTI; Reference #NACOSTI/P/25/415028), the Institutional Review Board of the Indiana University School of Medicine (Protocol #23171), with reliance agreements executed with Purdue University and Boston University. Dissemination of findings will occur through multiple channels within the research and clinical community, including peer-reviewed journal publications and conference abstracts and presentations. As part of capacity building efforts, the research team will also communicate study results to policy makers, the lay public and other health systems involved in the care of young children with disabilities via study-hosted workshops and conferences.

To evaluate how recurrent COVID-19 infections influence the clinical course of patients with chronic obstructive pulmonary disease (COPD), focusing on moderate-to-severe symptom flare-ups, all-cause mortality and long covid.

Nationwide retrospective cohort study.

Korean Health Insurance Review and Assessment database covering the entire Korean population between January 2020 and December 2023.

A total of 313 760 patients aged ≥40 years who met an established operational definition of COPD based on diagnostic codes and inhaled therapy prescriptions. Patients were stratified by the number of COVID-19 events: none, one, two or three or more.

The primary outcomes were moderate-to-severe COPD exacerbations and all-cause mortality. The secondary outcome was long covid, defined by WHO criteria using International Classification of Diseases (ICD)-10 codes persisting ≥2 months within 3 months after infection.

Among 313 760 patients, 154 095 (49.1 %) experienced at least one COVID-19 event. COVID-19 infection was associated with increased risk of exacerbations (adjusted HR (aHR) 1.64, 95% CI 1.62 to 1.66) and mortality (aHR 2.25, 95 % CI 2.19 to 2.31). Risk rose progressively with repeated infections, reaching an aHR of 2.41 for exacerbations and 2.93 for mortality after three or more events. Long covid was more frequent in patients with multiple infections, but most cases occurred after the first event, with diminishing occurrence after subsequent infections.

Recurrent COVID-19 infections in patients with COPD were linked to progressively higher risk of exacerbations and mortality, whereas the burden of long covid was greatest after the first infection. Preventing the initial infection and reducing reinfection risk remain critical components of COPD care in the post-COVID-19 era.

Infant feeding practices in the first 2 years of life are linked to long-term weight trajectories. Despite the importance of obesity prevention interventions, there are no randomised controlled trials (RCTs) evaluating early childhood education and care (ECEC) and primary caregiver-targeted interventions on child weight and feeding outcomes.

To assess the efficacy of an 18-month digital health intervention (Tiny Bites) delivered to ECEC services and primary caregivers of children aged 4 to ≤12 months on child age-adjusted and sex-adjusted body mass index-for-age z-score (zBMI) relative to usual care control in the Hunter New England (HNE) region of New South Wales, Australia.

This type 1 hybrid cluster RCT will include up to 60 ECEC services and 540 children/caregiver dyads. The intervention supports ECEC services and caregivers to deliver recommended responsive feeding practices to infants. ECEC services will receive access to an online assessment platform, training and resources, and implementation support. Primary caregivers will receive text messages, monthly e-newsletters, online links and direct communication from ECEC services. We will assess the impact on child zBMI at 18-month follow-up. Secondary outcomes include duration of consuming any breastmilk, child diet and caregiver responsive feeding practices. We will also assess ECEC policy and practice implementation related to targeted feeding practices, programme cost effectiveness, adverse effects and engagement with the programme (ECECs and caregivers). For the primary outcome, between-group differences will be assessed for paired data using two-level hierarchical linear regression models.

Ethics approval has been provided by HNE Human Research Ethics Committee (HREC) (2023/ETH01158), Deakin University (2024-202) and University of Newcastle HREC (R-2024-0039). Trial results will be submitted for publication in peer-reviewed journals, presented at scientific conferences locally and internationally and to relevant practice stakeholders.

ACTRN12624000576527.

Although lung cancer remains the leading cause of cancer deaths in the US, recent advances in early detection and treatment have led to improvements in survival. However, there is a considerable risk of recurrence or second primary lung cancer (SPLC) following curative-intent treatment in patients with early-stage non-small cell lung cancer (NSCLC). Professional societies recommend routine surveillance with CT to optimise the detection of potential recurrence and SPLC at a localised stage. However, no definitive evidence demonstrates the effect of imaging surveillance on survival in patients with NSCLC. To close these research gaps, the Advancing Precision Lung Cancer Surveillance and Outcomes in Diverse Populations (PLuS2) study will leverage real-world electronic health records (EHRs) data to evaluate surveillance outcomes among patients with and without guideline-adherent surveillance. The overarching goal of the PLuS2 study is to assess the long-term effectiveness of surveillance strategies in real-world settings.

PLuS2 is an observational study designed to assemble a cohort of patients with incident pathologically confirmed stage I/II/IIIA NSCLC who have completed curative-intent therapy. Patients undergoing imaging surveillance will be followed from 2012 to 2026 by linking EHRs with tumour registry data in the OneFlorida+ Clinical Research Consortium. Data will be consolidated into a unified repository to achieve three primary aims: (1) Examine the utilisation and determinants of CT imaging surveillance by race/ethnicity and socioeconomic status, (2) Compare clinical endpoints, including recurrence, SPLCs and survival of patients who undergo semiannual versus annual CT imaging and (3) Use the observational data in conjunction with validated microsimulation models to simulate imaging surveillance outcomes within the US population. To our knowledge, this study represents the first attempt to integrate real-world data and microsimulation models to assess the long-term impact and effectiveness of imaging surveillance strategies.

This study involves human participants and was approved by the University of Florida Institutional Review Board (IRB), University of Florida IRB 01, under approval number IRB202300782. The results will be disseminated through publications and presentations at national and international conferences. Safety considerations encompass ensuring the confidentiality of patient information. All disseminated data will be de-identified and summarised.

Exposure to prescription opioids following traumatic injury can increase the risk of developing tolerance, persistent opioid use and opioid use disorder. The mechanisms underlying opioid tolerance or dependence are not well understood, and no biomarkers predict risk. Opioid exposure causes epigenetic modifications, including alterations in microRNA (miRNA) expression. Several miRNAs, which regulate synaptic plasticity, are hypothesised to underlie substance use disorders and influence µ-opioid receptor levels, modulating opioid tolerance. This project aims to develop a bio-behavioural signature to predict persistent opioid use and chronic pain up to 6 months post-discharge.

The study will use a prospective cohort design, enrolling 180 adult patients at a Level I Trauma Center who are prescribed opioids at discharge. Prospective data will be collected in the hospital and at 7 days and 1, 3 and 6 months post-discharge. Biological data (genotyping and miRNA levels) and clinical measures of opioid use, pain, pain sensitivity (EEG) and psychosocial functioning will be collected at each time point. Bayesian regression methods will be used to identify baseline clinical, genetic, epigenetic and psychosocial predictors of opioid use and pain outcomes at 6 months post-discharge. Growth mixture modelling will identify distinct subgroups with varying trajectories, followed by Bayesian hierarchical modelling to predict trajectory classification based on predictor variables.

Ethics approval for this study was obtained from the University of Texas Health Science Center at Houston Committee for the Protection of Human Subjects (HSC-MS-24–0314). Findings will be disseminated in peer-reviewed scientific journals and at national and international conferences.