The objective of this study was to determine the association between viral subtype/clade and disease severity.

Multicentre retrospective cohort study.

This study used data from the Global Influenza Hospital Surveillance Network (GIHSN). The dataset comprised hospitalised influenza patients with viral sequencing data across 14 countries, collected from August 2022 through October 2023.

A total of 761 hospitalised patients were enrolled during the study period, and 745 patients were included in the analysis. We excluded patients with missing data on explanatory or outcome variables, those infected with viral clades represented by fewer than 11 sequences, and those enrolled at study sites contributing fewer than 5 patients.

Disease severity was defined by admission to intensive care unit (ICU), receipt of non-invasive oxygen supplementation, 3-variable definition (ICU, mechanical ventilation or death) or 4-variable definition (3-variable plus oxygen supplementation).

Outcomes were analysed in association with subtype or clade using the mixed-effects logistic regression models, adjusting for age group, sex, underlying medical conditions, influenza vaccination status, antiviral use, country income level and epidemic period, while study site was included as a random effect.

745 patients were included: 263 A(H1N1)pdm09, 380 A(H3N2), 102 B/Victoria. A(H1N1)pdm09 infection was associated with increased odds of ICU admission (adjusted ORs (aORs) 2.5, 95% CI 1.1 to 5.8) compared with A(H3N2). 6B.1A.5a.2a.1 clade of A(H1N1)pdm09 was associated with increased severity compared with 6B.1A.5a.2a clade (aOR 3.0, 95% CI 1.0 to 9.5) and (aOR 5.4, 95% CI 1.6 to 18.3) for the 3-variable and 4-variable definitions respectively. Among A(H3N2), the (3C.2a1b.2a.)2b clade showed a trend toward increased severity using the 4-variable definition compared with the 2a.1b clade (aOR 2.9, 95% CI 0.8 to 10.0).

This analysis highlights the differential impact of influenza subtypes and clades on disease severity in hospitalised patients. Future research should investigate the role of specific viral mutations of these clades in modulating immune evasion or disease severity. These findings reinforce the GIHSN’s critical role in global surveillance. Ongoing genomic surveillance is crucial for understanding the clinical impact of emerging influenza variants and informing public health responses.

To explore whether routine electronic healthcare records can be used to identify triggers for initiating advance care planning (ACP) and the optimal time window to initiate ACP. We aimed to assess the prevalence of triggers for initiating ACP as defined for use in routine data, whether their presence is associated with death, and what their position is relative to a previously identified ‘optimal time window for ACP’.

Nested case-control study within a large dynamic population cohort dataset.

Primary care population-based, anonymised data extracted from GP centres in the South Holland province, The Netherlands.

We selected records of individuals aged ≥65 registered with their general practice from 1 Jan 2014 to 1 Jan 2017. Cases were individuals who died between 1 Jan 2017 and 1 Jan 2020. Controls were individuals who remained alive. Cases were matched by age to controls in a 1:4 ratio.

Outcomes include prevalence of triggers for ACP in the records of deceased and living individuals; association of the triggers’ presence with death; timing of the identified triggers in deceased individuals relative to the ‘optimal time window for ACP’.

We included 17098 records, 4139 from deceased individuals (mean age 81) and 12959 from living individuals (mean age 79). Triggers most strongly associated with death were consultations concerning malignancy (OR 8.35, 95% CI 7.42 to 9.41), hospital admissions (OR 7.32, 95% CI 6.75 to 7.94), emergency department referrals (OR 7.11, 95% CI 6.52 to 7.75), registered home visits (OR 5.97, 95% CI 5.51 to 6.47), consultations concerning heart failure (OR 5.25, 95% CI 4.59 to 5.99), dementia (OR 4.75, 95% CI 3.99 to 6.56), opioid prescriptions (OR 4.58 (4.25–4.93), consultations concerning general decline/feeling old (OR 4.15, 95% CI 3.72 to 4.64) and skin ulcers/pressure sores (OR 4.04, 95% CI 3.55 to 4.61). Those closest to the median of the optimal time window for ACP were consultations regarding dyspnoea, general decline/feeling old, heart failure, skin ulcers/pressure sores and fever, opioid prescriptions, emergency department referrals, registered home visits and hospital admissions.

Clinical triggers for initiating ACP in general practice can be recognised within the routine electronic health records and they align well with the ‘window of opportunity’ to initiate ACP.

Physical activity is crucial for young children’s health and development. Many young children do not meet the recommended 3 hours of daily physical activity, including 60 min of energetic play. Early childhood education and care (ECEC/childcare) is a key setting to intervene to improve children’s physical activity. The Play Active programme is a scalable evidence-informed ECEC-specific physical activity policy intervention with implementation support strategies to improve educators’ physical activity-related practices.

This hybrid type III effectiveness-implementation trial will use a quasi-experimental repeated measures design to assess the real-world effectiveness of Play Active’s scalable implementation support strategies in helping ECEC services adopt the practices included in the Play Active policy. Secondary aims will examine changes in educator-reported and device-measured children’s physical activity; assess the sustainability of the programme; identify effective dissemination strategies; assess cost-effectiveness; and involve comprehensive process evaluation. All ECEC services in Western Australia (n=776), Queensland (n=1744) and South Australia (n=445) will be invited to participate. Data will be collected at baseline, 6, 12, 18, 24 and 30 months.

Ethics approval has been provided by The University of Western Australia Human Research Ethics Committee (HREC) (2023/ET000187), the University of Queensland HREC (2024/HE000076) and the University of South Australia HREC (206023). This real-world trial of Play Active is vital for understanding its implementation in practice and to generate evidence for further scale-up and roll-out nationally. Key findings will be disseminated to stakeholders, collaborators, policy-makers as well as families and practitioners in the ECEC sector.

ACTRN12624000406505.