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Objective Cerebrospinal fluid (CSF) drainage is a technique that has significantly reduced the incidence of spinal cord ischaemia (SCI). We present results of a systematic review to assess the literature on this topic in relation to thoracoabdominal aortic aneurysm repair (TAAR). Methods Major medical databases were searched to identify papers related to CSF biomarkers measured during TAAAR. Results Fifteen papers reported measurements of CSF biomarkers with 265 patients in total. CSF biomarkers measured included S-100ß, neuron-specific endolase (NSE), lactate, glial fibrillary acidic protein A (GFPa), Tau, heat shock protein 70 and 27 (HSP70, HSP27), and proinflammatory cytokines. Lactate and S-100ß were reported the most, but did not correlate with SCI, which was also the case with NSE and TAU. GFPa showed significant CSF level rises, both intra and postoperative in patients who suffered SCI and warrants further investigation, similar results were seen with HSP70, HSP27 and IL-8. Conclusions Although there is significant interest in this topic, there still remains a significant lack of high-quality studies investigating CSF biomarkers during TAAR to detect SCI. A large and multicentre study is required to identify the significant role of each biomarker.

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Background and Aim: ADHD is the most common childhood neurodevelopmental disorder. ADHD symptoms can lead to impairments in other areas of functioning approximately 75% of children with ADHD also experience difficulties with sleep. Childhood sleep difficulties intensify ADHD symptom severity and cause additional impairments. There is growing support for routine assessment of sleep as part of standard ADHD management. However, assessment of sleep difficulties remains poorly addressed as they fail to account for the unique expression of sleep difficulties present in children with ADHD. Our recently submitted systematic review identified the lack of appropriate tools to screen children with ADHD for sleep difficulties. Research Method: This multi-phase research will address this gap in current knowledge by undertaking a comprehensive project that will develop, trial, and evaluate a fit-for-purpose screening assessment of sleep difficulties in children with ADHD. This project will: (i) develop a purpose-built screening instrument with the aid of consumer and clinician engagement, (ii) validate this this new measure for the assessment of sleep in children with ADHD, and (iii) evaluate an information intervention of sleep problems for children with ADHD with the new measure. Anticipated Results: A screening instrument will be developed through collaboration with sleep experts and parents of children with ADHD which will then be piloted and validated using best practice methods. Implications: It is anticipated that this research will help to provide clinicians with greater accuracy in identifying sleep difficulties in children with ADHD and therefore enabling opportunities for early intervention and improved treatment outcomes.

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Patterns of mental health have been well characterised in the Avon Longitudinal Study of Parents and Children (ALSPAC), but there is a paucity of longitudinal medication data for depression and anxiety within the ALSPAC study. Understanding types and usage of pharmacological treatment allows for a deeper understanding of mental health in the ALSPAC study and key factors influencing illness outcomes, such as access to service provision. Enhanced understanding of the types of medication people have used to manage depression and anxiety could also give insight into which treatments work for individuals over the life course. This data note describes data collection on medication for depression and anxiety in the offspring (ALSPAC-G1) at ages 28-29 (born 1991/1992). Data were collected through a questionnaire deployed between December 2020 and April 2021. First, we highlight the variables collected as part of the questionnaire, specifically on medication use for depression and anxiety. We then outline how we have derived antidepressant variables including type of antidepressants, length of time used, and treatment phenotypes such as ‘remission’ and ‘non remission’. Finally, we also report associations between longitudinal mental health variables and reported use of medication and antidepressant variables to validate these new measures. Considerations for how the data collected can be used for researchers is also summarised.