Severe mental illness (SMI) is associated with significant morbidity. Frailty combines biological ageing, comorbidity and psychosocial factors and can predict adverse health outcomes. Emerging evidence indicates that frailty is higher in individuals with SMI than in the general population, although studies have been limited by sample size.

To describe the prevalence of frailty in people with SMI in a large cohort using three different frailty measures and examine the impact of demographic and sociodemographic variables.

The UK Biobank survey data, which included individuals aged 37–73 years from England, Scotland and Wales from 2006 to 2010, with linked in-patient hospital episodes, were utilised. The prevalence of frailty in individuals with and without SMI was assessed through three frailty measures: frailty index, physical frailty phenotype (PFP) and Hospital Frailty Risk Score (HFRS). Stratified analysis and dichotomous logistic regression were conducted.

A frailty index could be calculated for 99.5% of the 502 412 UK Biobank participants and demonstrated greater prevalence of frailty in women and an increase with age. The prevalence of frailty for those with SMI was 3.19% (95% CI 3.0–3.4), 4.2% (95% CI 3.8–4.7) and 18% (95% CI 15–23) using the frailty index, PFP and HFRS respectively. The prevalence ratio was between 3 and 18 times higher than in those without SMI.

As a measure, frailty captures the known increase in morbidity associated with SMI and may potentially allow for earlier identification of those who will benefit from targeted interventions.

Although clozapine is the most efficacious medication for treatment-refractory schizophrenia, not all patients will have an adequate response. Optimising clozapine dose using therapeutic drug monitoring could therefore maximise response.

Using individual patient data, we undertook a receiver operating characteristic (ROC) curve analysis to determine an optimal therapeutic range for clozapine levels to guide clinical practice.

We conducted a systematic review of PubMed, PsycINFO and Embase for studies that provided individual participant level data on clozapine levels and response. These data were analysed using ROC curves to determine the prediction performance of plasma clozapine levels for treatment response.

We included data on 294 individual participants from nine studies. ROC analysis yielded an area under the curve of 0.612. The clozapine level at the point of optimal diagnostic benefit was 372 ng/mL; at this level, the response sensitivity was 57.3%, and specificity 65.7%. The interquartile range for treatment response was 223–558 ng/mL. There was no improvement in ROC performance with mixed models including patient gender, age or length of trial. Clozapine dose and clozapine concentration to dose ratio did not provide significantly meaningful prediction of response to clozapine.

Clozapine dose should be optimised based on clozapine therapeutic levels. We found that a range between 250 and 550 ng/mL could be recommended, while noting that a level of >350 ng/mL is the most optimal for response. Although some patients may not respond without clozapine levels >550 ng/mL, the benefits should be weighed against the increased risk of adverse drug reactions.

Child maltreatment is a major public health issue worldwide. Retrospective studies show a strong association between self-reported child maltreatment and poor mental and physical health problems. Prospective studies that use reports to statutory agencies are less common, and comparisons of self- and agency-reported abuse in the same cohort even rarer.

This project will link state-wide administrative health data with prospective birth cohort data (N = 7223) from Brisbane in Queensland, Australia (including notifications to child protection agencies), to compare psychiatric outcomes in adulthood of agency- and self-reported child maltreatment while minimising attrition bias.

We will compare people with all forms of self- and agency-reported child maltreatment to the rest of the cohort, adjusting for confounding in logistic, Cox or multiple regression models based on whether outcomes are categorical or continuous. Outcomes will be hospital admissions, emergency department presentations or community/out-patient contacts for ICD-10 psychiatric diagnoses, suicidal ideation and self-harm as recorded in the relevant administrative databases.

This study will track the life course outcomes of adults after having experienced child maltreatment, and so provide an evidence-based understanding of the long-term health and behavioural consequences of child maltreatment. It will also consider health outcomes that are particularly relevant for adolescents and young adults, especially in relation to prospective notifications to statutory agencies. Additionally, it will identify the overlap and differences in outcome for two different sources of child maltreatment identification in the same cohort.