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The cingulum: anatomy, connectivity and what goes beyond
Abstract For over half a century, the cingulum has been the subject of neuroanatomical and therapeutic investigations owing to its wide range of functions and involvement in various neurological and psychiatric diseases. Recent clinical studies investigating neurosurgical techniques targeting the cingulum, like deep brain stimulation of the anterior cingulate cortex (DBS-ACC) and cingulotomy, have further boosted interests in this central ‘hub’ as a target for chronic intractable pain. Proper targeting within the cingulum is essential to achieve sufficient pain relief. Despite the cingulum being the center of research for over a century, its structural and functional organization remain a subject to debate, consequently complicating neurosurgical targeting of this area. This study aims to review anatomical and connectivity data of the cingulum from a clinical perspective in order to improve understanding of its role in pain. For the current study, a systematic literature search was performed to assess the anatomy, and functional and structural connectivity of the cingulate bundle and -cortex. These outcomes focus on Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) data. Articles were searched within the PubMed database and additional articles were found manually through reviews or references cited within the articles. After exclusion, 70 articles remained included in this analysis, with 50, 29 and 10 studies describing human, monkey and rat subjects respectively. Outcomes of this analysis show the presence of various anatomical models, each describing other subdivisions within the cingulum. Moreover, connectivity data suggest that the cingulate bundle consists of three distinct fibre projections, including the thalamocortical, cingulate gyrus and anterior frontal and posterior parietal projections. Further, the cingulum is responsible for a variety of functions involved in chronic pain, like sensory processing, memory, spatial functioning, reward, cognition, emotion, visceromotor and endocrine control. Based on the current outcomes, it can be concluded that the cingulum is a central ‘hub’ for pain processing, because it is a melting pot for memory, cognition and affect that are involved in the complex phenomenon of pain experience, memory, spatial functioning, reward, cognition, emotion, visceromotor and endocrine control. Variability in anatomical and connectivity models complicate proper and standardized neurosurgical targeting, consequently leading to clinicians often being reluctant on stimulation and/or lesioning of the cingulum. Hence, future research should be dedicated to the standardization of these models, to allow for optimal targeting and management of patients with chronic intractable pain.
Evaluating the generalisability of region-naïve machine learning algorithms for the identification of epilepsy in low-resource settings.
OBJECTIVES: Approximately 80% of people with epilepsy live in low- and middle-income countries (LMICs), where limited resources and stigma hinder accurate diagnosis and treatment. Clinical machine learning models have demonstrated substantial promise in supporting the diagnostic process in LMICs by aiding in preliminary screening and detection of possible epilepsy cases without relying on specialised or trained personnel. How well these models generalise to naïve regions is, however, underexplored. Here, we use a novel approach to assess the suitability and applicability of such clinical tools to aid screening and diagnosis of active convulsive epilepsy in settings beyond their original training contexts. METHODS: We sourced data from the Study of Epidemiology of Epilepsy in Demographic Sites dataset, which includes demographic information and clinical variables related to diagnosing epilepsy across five sub-Saharan African sites. For each site, we developed a region-specific (single-site) predictive model for epilepsy and assessed its performance at other sites. We then iteratively added sites to a multi-site model and evaluated model performance on the omitted regions. Model performances and parameters were then compared across every permutation of sites. We used a leave-one-site-out cross-validation analysis to assess the impact of incorporating individual site data in the model. RESULTS: Single-site clinical models performed well within their own regions, but generally worse when evaluated in other regions (p<0.05). Model weights and optimal thresholds varied markedly across sites. When the models were trained using data from an increasing number of sites, mean internal performance decreased while external performance improved. CONCLUSIONS: Clinical models for epilepsy diagnosis in LMICs demonstrate characteristic traits of ML models, such as limited generalisability and a trade-off between internal and external performance. The relationship between predictors and model outcomes also varies across sites, suggesting the need to update specific model aspects with local data before broader implementation. Variations are likely to be particular to the cultural context of diagnosis. We recommend developing models adapted to the cultures and contexts of their intended deployment and caution against deploying region- and culture-naïve models without thorough prior evaluation.
European Stroke Organisation (ESO) standard operating procedure for white papers (expert consensus based clinical guidance).
Promoting the highest quality, evidence-based research across Europe is a priority of the European Stroke Organisation (ESO). The ESO Guideline Board communicate and promote evidence-based recommendations for clinical practice through their Guidelines. However, there are many aspects of stroke care where robust scientific evidence may be unavailable or difficult to obtain. Thus, there is a need for practical, consensus guidance, produced following robust, consistent, and transparent methods, that is suitable for high-priority clinical scenarios where evidence is currently lacking. The ESO Guideline Board developed methods for producing practical clinical guidance based on expert consensus in response to this need. These ESO' White Papers' are intended to complement standard ESO Guidelines. Here, we outline the ESO White Papers' standard operating procedure (SOP). We will describe the motivation for creating White Papers, the preferred composition of writing groups and expert consensus panellists, the methods for achieving consensus, and how results will be communicated. To ensure that all voting members have an equal voice, our methods are based upon the Delphi process of repeated rounds of anonymous voting, feedback and review. We hope that the White Papers will add further value to the clinical practice guidance that is offered by ESO. We look forward to receiving suggestions for White Paper topics from the stroke community.
Insomnia prehabilitation in newly diagnosed breast cancer patients: Protocol for a pilot, multicentre, randomised controlled trial comparing nurse delivered sleep restriction therapy to sleep hygiene education (INVEST trial)
Introduction Insomnia is a prevalent sleep disorder that negatively impacts daytime functioning and quality of life. Breast cancer patients report higher rates of insomnia and more circadian disruption than other cancer groups. Approximately 50% of patients experience acute insomnia following breast cancer diagnosis, which often persists during cancer treatment and rehabilitation. Sleep Restriction Therapy (SRT) is a clinically effective and tolerable treatment for persistent insomnia in breast cancer survivors. However, SRT has never been tested on patients with early signs of sleep disturbance who are undergoing cancer treatment. The aim of this pilot randomised controlled trial is to explore the feasibility and preliminary effectiveness of nurse delivered SRT for newly diagnosed breast cancer patients with acute insomnia. The trial has been registered on ClinicalTrials.gov (identifier: NCT06294041). Methods The INVEST (INvestigating the Value of Early Sleep Therapy) trial will recruit 50 newly diagnosed breast cancer patients who meet criteria for acute insomnia. Patients will be recruited from breast cancer results clinics within two Scottish health boards (NHS Grampian and NHS Greater Glasgow and Clyde) and will be block randomised (1:1) to receive nurse delivered SRT or Sleep Hygiene Education (SHE). SRT will be delivered over 4 weekly sessions comprising two face-to-face meetings (either in person or online) and two telephone calls, whereas SHE will be administered in booklet form. Outcomes will be collected at baseline, 6 weeks, and 12 weeks post-randomisation. Primary outcomes in this trial relate to the feasibility of SRT for newly diagnosed breast cancer patients with acute insomnia. Specifically, we will explore (i) rates of patient recruitment and retention, (ii) intervention fidelity, (iii) data collection procedures and outcome measure completion, (iv) intervention acceptability. Secondary outcomes will focus on preliminary evaluation of patient responses to SRT, including insomnia severity, rest-activity rhythms, and mental health. Dissemination Our dissemination plan comprises publishing trial outcomes in high-impact, peer-reviewed journals and on breast cancer charity websites and other patient resources. The outcomes from this pilot trial will also inform the development of a full-scale, multicentre RCT of SRT for acute insomnia in newly diagnosed breast cancer patients. University of Strathclyde is the sponsor (reference: UEC23/52). Protocol version v1.2 4 October 2023. Strengths and limitations of this study This trial is the first to explore the value of sleep prehabilitation for newly diagnosed breast cancer patients. This will be the first trial to assess the feasibility of delivering SRT during breast cancer treatment, providing valuable insight into its tolerability and preliminary effectiveness. An embedded process evaluation will assess the acceptability of SRT, providing insight into potential optimisation of the intervention and recommendations for enhancing its future scalability and translation within cancer care. Due to the nature of the SRT intervention, nurse therapists and patients cannot be blinded to treatment allocation, increasing the risk of bias.
The role of accelerometer-derived sleep traits on glycated haemoglobin and glucose levels: a Mendelian randomization study
AbstractSelf-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be ‘objective’ measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.
Efficacy of multicomponent CBT-I and its single components
This chapter provides an overview of contemporary evidence (as of 2021) for the efficacy of CBT-I and its components. The scientific support for the clinical use of CBT-I has emerged over the last 40 years and now comprises over 100 randomised controlled trials (RCTs). These trials have informed numerous meta-analyses that have, as a consequence, shaped the treatment guidelines we use today. The evidence considered in this chapter focuses on the most recent meta-analyses that report on the effects of CBT-I and its components on insomnia symptoms and measures of sleep continuity. The overarching conclusion from meta-analyses is that CBT-I is effective in improving night-time insomnia symptoms in both the short term and the long term. In addition, CBT-I improves daytime functioning and its efficacy seems to be independent of co-morbid conditions, age and use of medication. The efficacy of CBT-I components as standalone therapies has been examined to a lesser extent but shows promising results, especially for behavioural components.
A scoping review of the evidence for the impact of pharmacological and non-pharmacological interventions on shift work related sleep disturbance in an occupational setting.
Background: Shift work is essential in society but can be detrimental to health and quality of life and is associated with decreased productivity and increased risk of accidents. Interventions to reduce these consequences are needed, but the extent and range of trial evidence for interventions for those most affected by their shift-work schedules is unclear. We therefore carried out a scoping review to assess the availability of evidence to inform the development and evaluation of future interventions. Methods: We aimed to identify clinical trials of any intervention for shift work-related sleep disturbance that included a comparator group, where the intervention was delivered in an occupational setting. We searched Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, CINAHL, EMBASE, Medline and Science Citation Index from inception to 30 th March 2020 for relevant citations. Citations were screened by two independent reviewers, a third reviewer resolved disagreements. Data were extracted by two independent reviewers. Results: From 1250 unique citations, 14 studies met inclusion criteria for comparative trials of treatment in an occupational setting. There were five trials of hypnotics, five trials of stimulants, and four trials of non-pharmacological therapies (cognitive behavioural therapy, light therapy, aromatherapy and herbal medicine). Outcomes included sleep parameters, day-time sleepiness, and quality of life. There were no consistently reported outcomes across trials. Conclusions: Interventions fell into three distinct groups investigated in distinct time periods without progression from efficacy trials to wider-scale interventions. The lack of consistent patient-reported outcome measures limits synthesising findings. Some trials focussed on optimising sleep, others on reducing wake-time sleepiness. Adequately powered trials of existing interventions are needed, with the development and testing of novel combination treatments in patients with well-defined shift work sleep disorder. A core set of clinically relevant outcomes will develop and standardise the evidence-base for shift work sleep disorder.
Ventromedial prefrontal cortex lesions disrupt learning to reward others
Abstract Reinforcement learning is a fundamental process for how humans and other animals attain rewards for themselves. However, to act prosocially, we must also learn how our choices reward others. The ventromedial prefrontal cortex has been independently linked to reinforcement learning and prosocial behaviour, yet its causal impact on prosocial reinforcement learning and the roles of its multiple subregions remain unknown. Here, a large group of adults with rare focal ventromedial prefrontal cortex damage (n=28), and two carefully age- and gender-matched control groups (lesions elsewhere, n=21; healthy controls, n=124) completed a reinforcement learning task where they learnt to win rewards for another person (prosocial), for themselves (self), or in a control condition where participants saw points but they were not translated into rewards for either individual (no one, control condition) on separate trials. A novel computational model which incorporated separate learning rates for positive and negative prediction errors best explained behaviour in all groups. Importantly, compared to both control groups, patients with ventromedial prefrontal cortex damage were less accurate and had lower learning rates from positive prediction errors when rewarding another person relative to when no one benefitted, and higher learning rates for negative prediction errors when learning for others relative to self. Unlike controls, ventromedial prefrontal cortex lesion patients also showed a reduced self-benefitting advantage. They were equally accurate and learnt at a similar rate from positive prediction errors for self and neither individual. Strikingly, voxel-based lesion-symptom mapping revealed that damage to subgenual anterior cingulate cortex and anterior cingulate cortex gyrus specifically disrupted prosocial reinforcement learning. These findings highlight the importance of ventromedial prefrontal cortex integrity for multiple aspects of reinforcement learning, with damage to subgenual anterior cingulate cortex and anterior cingulate cortex gyrus critical for learning to reward others.
Inter-Laboratory Validation of Nodal/Paranodal Antibody Testing.
BACKGROUND AND AIMS: Reliable detection of antibodies against nodal targets is vital for the diagnosis of autoimmune nodopathies. The performance characteristics of recently developed in-house assays are unknown. We compared testing at four centres. METHODS: Each submitted 29-40 serum samples to a coordinating centre from one of three groups: (1) autoimmune nodopathy patients, with positive nodal/paranodal antibodies; (2) seronegative patients with other inflammatory neuropathies, and (3) healthy individuals or those with other neurological diseases. The coordinating centre recoded all samples and returned 160 identical aliquots to each testing centre for blinded testing. Once data from all centres had been received by the coordinating centre, unblinded results were returned for analysis. Sensitivity was defined by the proportion of group 1 samples returned as positive. Accuracy was defined as 0.075(sensitivity) + 0.925(specificity). RESULTS: Centres performed various combinations of ELISA, cell-based (CBAs) and teased-nerve fibre assays. All labs produced highly accurate results (96%-100%) and concordance for the overall result across at least 3 or all 4 test centres was observed for 98% and 89% of the samples respectively. However, 10/30 individual assays (6/14 CBAs and 4/16 ELISAs) were less than 90% sensitive. Only 3 assays had more than 1 false positive result (2 ELISAs and 1 CBA). Combining different assay modalities to produce an overall result did not improve accuracy. Inter-laboratory consistency in the determination of antibody subclasses was poor. INTERPRETATION: Although most samples were correctly categorised in all 4 centres, the use of a specific test modality or multiple tests did not guarantee accuracy. Early and repeated interlaboratory testing with sharing of samples is important to understand test performance and reproducibility, identify areas for improvement and maintain consistency. To aid this, we provide detailed methods for the best performing tests. Further standardisation of antibody subclass determination is required.