The specific and multifaceted service needs of young people have driven the development of youth-specific integrated primary mental healthcare models, such as the internationally pioneering headspace services in Australia. Although these services were designed for early intervention, they often need to cater for young people with severe conditions and complex needs, creating challenges in service planning and resource allocation. There is, however, a lack of understanding and consensus on the definition of complexity in such clinical settings.

This retrospective study involved analysis of headspace’s clinical minimum data set from young people accessing services in Australia between 1 July 2018 and 30 June 2019. Based on consultations with experts, complexity factors were mapped from a range of demographic information, symptom severity, diagnoses, illness stage, primary presenting issues and service engagement patterns. Consensus clustering was used to identify complexity subgroups based on identified factors. Multinomial logistic regression was then used to evaluate whether these complexity subgroups were associated with other risk factors.

A total of 81,622 episodes of care from 76,021 young people across 113 services were analysed. Around 20% of young people clustered into a ‘high complexity’ group, presenting with a variety of complexity factors, including severe disorders, a trauma history and psychosocial impairments. Two moderate complexity groups were identified representing ‘distress complexity’ and ‘psychosocial complexity’ (about 20% each). Compared with the ‘distress complexity’ group, young people in the ‘psychosocial complexity’ group presented with a higher proportion of education, employment and housing issues in addition to psychological distress, and had lower levels of service engagement. The distribution of complexity profiles also varied across different headspace services.

The proposed data-driven complexity model offers valuable insights for clinical planning and resource allocation. The identified groups highlight the importance of adopting a holistic and multidisciplinary approach to address the diverse factors contributing to clinical complexity. The large number of young people presenting with moderate-to-high complexity to headspace early intervention services emphasises the need for systemic change in youth mental healthcare to ensure the availability of appropriate and timely support for all young people.

Multimorbidity, the presence of two or more health conditions, has been identified as a possible risk factor for clinical dementia. It is unclear whether this is due to worsening brain health and underlying neuropathology, or other factors. In some cases, conditions may reflect the same disease process as dementia (e.g. Parkinson's disease, vascular disease), in others, conditions may reflect a prodromal stage of dementia (e.g. depression, anxiety and psychosis).

To assess whether multimorbidity in later life was associated with more severe dementia-related neuropathology at autopsy.

We examined ante-mortem and autopsy data from 767 brain tissue donors from the UK, identifying physical multimorbidity in later life and specific brain-related conditions. We assessed associations between these purported risk factors and dementia-related neuropathological changes at autopsy (Alzheimer's-disease related neuropathology, Lewy body pathology, cerebrovascular disease and limbic-predominant age-related TDP-43 encephalopathy) with logistic models.

Physical multimorbidity was not associated with greater dementia-related neuropathological changes. In the presence of physical multimorbidity, clinical dementia was less likely to be associated with Alzheimer's disease pathology. Conversely, conditions which may be clinical or prodromal manifestations of dementia-related neuropathology (Parkinson's disease, cerebrovascular disease, depression and other psychiatric conditions) were associated with dementia and neuropathological changes.

Physical multimorbidity alone is not associated with greater dementia-related neuropathological change; inappropriate inclusion of brain-related conditions in multimorbidity measures and misdiagnosis of neurodegenerative dementia may better explain increased rates of clinical dementia in multimorbidity

The utility of quality of life (QoL) as an outcome measure in youth-specific primary mental health care settings has yet to be determined. We aimed to determine: (i) whether heterogeneity on individual items of a QoL measure could be used to identify distinct groups of help-seeking young people; and (ii) the validity of these groups based on having clinically meaningful differences in demographic and clinical characteristics.

Young people, at their first presentation to one of five primary mental health services, completed a range of questionnaires, including the Assessment of Quality of Life–6 dimensions adolescent version (AQoL-6D). Latent class analysis (LCA) and multivariate multinomial logistic regression were used to define classes based on AQoL-6D and determine demographic and clinical characteristics associated with class membership.

1107 young people (12–25 years) participated. Four groups were identified: (i) no-to-mild impairment in QoL; (ii) moderate impairment across dimensions but especially mental health and coping; (iii) moderate impairment across dimensions but especially on the pain dimension; and (iv) poor QoL across all dimensions along with a greater likelihood of complex and severe clinical presentations. Differences between groups were observed with respect to demographic and clinical features.

Adding multi-attribute utility instruments such as the AQoL-6D to routine data collection in mental health services might generate insights into the care needs of young people beyond reducing psychological distress and promoting symptom recovery. In young people with impairments across all QoL dimensions, the need for a holistic and personalised approach to treatment and recovery is heightened.

Early administration of antibiotics in sepsis is associated with improved patient outcomes, but safe and generalizable approaches to de-escalate or discontinue antibiotics after suspected sepsis events are unknown.

We used a modified Delphi approach to identify safety criteria for an opt-out protocol to guide de-escalation or discontinuation of antibiotic therapy after 72 hours in non-ICU patients with suspected sepsis. An expert panel with expertise in antimicrobial stewardship and hospital epidemiology rated 48 unique criteria across 3 electronic survey rating tools. Criteria were rated primarily based on their impact on patient safety and feasibility for extraction from electronic health record review. The 48 unique criteria were rated by anonymous electronic survey tools, and the results were fed back to the expert panel participants. Consensus was achieved to either retain or remove each criterion.

After 3 rounds, 22 unique criteria remained as part of the opt-out safety checklist. These criteria included high-risk comorbidities, signs of severe illness, lack of cultures during sepsis work-up or antibiotic use prior to blood cultures, or ongoing signs and symptoms of infection.

The modified Delphi approach is a useful method to achieve expert-level consensus in the absence of evidence suifficient to provide validated guidance. The Delphi approach allowed for flexibility in development of an opt-out trial protocol for sepsis antibiotic de-escalation. The utility of this protocol should be evaluated in a randomized controlled trial.

Mild cognitive impairment (MCI) may gradually worsen to dementia, but often remains stable for extended periods of time. Little is known about the predictors of decline to help explain this variation. We aimed to explore whether this heterogeneous course of MCI may be predicted by the presence of Lewy body (LB) symptoms in a prospectively-recruited longitudinal cohort of MCI with Lewy bodies (MCI-LB) and Alzheimer's disease (MCI-AD).

A prospective cohort (n = 76) aged ⩾60 years underwent detailed assessment after recent MCI diagnosis, and were followed up annually with repeated neuropsychological testing and clinical review of cognitive status and LB symptoms. Latent class mixture modelling identified data-driven sub-groups with distinct trajectories of global cognitive function.

Three distinct trajectories were identified in the full cohort: slow/stable progression (46%), intermediate progressive decline (41%) and a small group with a much faster decline (13%). The presence of LB symptomology, and visual hallucinations in particular, predicted decline v. a stable cognitive trajectory. With time zeroed on study end (death, dementia or withdrawal) where available (n = 39), the same subgroups were identified. Adjustment for baseline functioning obscured the presence of any latent classes, suggesting that baseline function is an important parameter in prospective decline.

These results highlight some potential signals for impending decline in MCI; poorer baseline function and the presence of probable LB symptoms – particularly visual hallucinations. Identifying people with a rapid decline is important but our findings are preliminary given the modest cohort size.

Growth in emergency department (ED) attendance and acute medical admissions has been managed to very low rates for 18 years in Canterbury, New Zealand, using a combination of community and hospital avoidance strategies. This paper describes the specific strategies that supported management of acutely unwell patients in the community as part of a programme to integrate health services.

Community-based acute care was established by a culture of close collaboration and trust between all sectors of the health system, with general practice closely involved in the design and management of the services, and support provided by hospital specialists, coordination and diagnostic units, and competent informatics. Introduction of the community-based services was aided by a clinical guidance website and an education programme for general practice teams and allied health professionals.

Attendance at EDs and acute medical admission rates have been held at low growth and, in some cases, shorter lengths of hospital stay. This trend was especially evident in elderly patients and those with ambulatory care sensitive or chronic disorders.

A system of community-based care and education has resulted in sustained gains for the Canterbury health system and freed-up hospital resources. This outcome has engendered a sense of empowerment for general practice teams and their patients.

To investigate the feasibility and acceptability of using wearable cameras as a method to capture the opportunities for food and drink purchasing/consumption that young people encounter on their regular journeys to and from school.

A qualitative study using multiple data-collection methods including wearable cameras, global positioning system units, individual interviews, food and drink purchase and consumption diaries completed by participants over four days, and an audit of food outlets located within an 800 m Euclidean buffer zone around each school.

A community setting.

Twenty-two students (fourteen girls and eight boys) aged 13–15 years recruited from four secondary schools in two counties of England.

Wearable cameras offered a feasible and acceptable method for collecting food purchase and consumption data when used alongside traditional methods of data collection in a small number of teenagers. We found evidence of participants making deliberate choices about whether or not to purchase/consume food and drink on their journeys. These choices were influenced by priorities over money, friends, journey length, travel mode and ease of access to opportunities for purchase/consumption. Most food and drink items were purchased/consumed within an 800 m Euclidean buffer around school, with items commonly selected being high in energy, fat and sugar. Wearable camera images combined with interviews helped identify unreported items and misreporting errors.

Wearable camera images prompt detailed discussion and generate contextually specific information which could offer new insights and understanding around eating behaviour patterns. The feasibility of scaling up the use of these methods requires further empirical work.