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Morphological and functional parameters in X-linked retinoschisis patients–A multicentre retrospective cohort study
Introduction: X-linked retinoschisis (XLRS) is a potential target for gene supplementation approaches. To establish potential structural and functional endpoints for clinical trials, a comprehensive understanding of the inter-eye symmetry, relationship between structural and functional parameters, and disease progression is vital. Methods: In this retrospective multicentre study, 118 eyes of 59 XLRS patients with RS1 mutations were assessed. Information from center databases included: RS1 variant; age at presentation; best-corrected visual acuity (BCVA), central retinal thickness (CRT), macular volume (MV) at presentation and at the last follow up; full-field electroretinogram (ERG) findings; presence of peripheral retinoschisis and complications (vitreous hemorrhage, retinal detachment); treatment with systemic or topical carbonic anhydrase inhibitors (CAI). Results: Inter-eye symmetry revealed strong correlation in CRT (r = 0.77; p < 0.0001) and moderate correlations in MV (r = 0.51, p < 0.0001) and BCVA (r = 0.49; p < 0.0001). Weak or no correlations were observed between BCVA and structural parameters (CRT, MV). Peripheral retinoschisis was observed in 40 (68%), retinal detachment in 9 (15%), and vitreous hemorrhage in 5 (8%) patients, respectively. Longitudinal examinations (mean, 4.3 years) showed no BCVA changes; however, a reduction of the CRT (p = 0.02), and MV (p = 0.01) was observed. Oral and/or topical CAI treatment did not significantly alter the CRT (p = 0.34). Discussion: The XLRS phenotype demonstrates a strong CRT symmetry between the eyes within individual patients and stable BCVA over several years. BCVA exhibits a weak correlation with the morphological parameters of retinal thickness (CRT MV). In our cohort, longitudinal functional changes were not significant, likely attributed to the short average follow-up period. Furthermore, CAI treatment didn’t influence both morphological and functional outcomes.
NHS Health Check attendance is associated with reduced multiorgan disease risk: a matched cohort study in the UK Biobank
Background: The NHS Health Check is a preventive programme in the UK designed to screen for cardiovascular risk and to aid in primary disease prevention. Despite its widespread implementation, the effectiveness of the NHS Health Check for longer-term disease prevention is unclear. In this study, we measured the rate of new diagnoses in UK Biobank participants who underwent the NHS Health Check compared with those who did not. Methods: Within the UK Biobank prospective study, 48,602 NHS Health Check recipients were identified from linked primary care records. These participants were then covariate-matched on an extensive range of socio-demographic, lifestyle, and medical factors with 48,602 participants without record of the check. Follow-up diagnoses were ascertained from health records over an average of 9 years (SD 2 years) including hypertension, diabetes, hypercholesterolaemia, stroke, dementia, myocardial infarction, atrial fibrillation, heart failure, fatty liver disease, alcoholic liver disease, liver cirrhosis, liver failure, acute kidney injury, chronic kidney disease (stage 3 +), cardiovascular mortality, and all-cause mortality. Time-varying survival modelling was used to compare adjusted outcome rates between the groups. Results: In the immediate 2 years after the NHS Health Check, higher diagnosis rates were observed for hypertension, high cholesterol, and chronic kidney disease among health check recipients compared to their matched counterparts. However, in the longer term, NHS Health Check recipients had significantly lower risk across all multiorgan disease outcomes and reduced rates of cardiovascular and all-cause mortality. Conclusions: The NHS Health Check is linked to reduced incidence of disease across multiple organ systems, which may be attributed to risk modification through earlier detection and treatment of key risk factors such as hypertension and high cholesterol. This work adds important evidence to the growing body of research supporting the effectiveness of preventative interventions in reducing longer-term multimorbidity.
Evaluating functional brain organization in individuals and identifying contributions to network overlap
Abstract Individual differences in the spatial organization of resting-state networks have received increased attention in recent years. Measures of individual-specific spatial organization of brain networks and overlapping network organization have been linked to important behavioral and clinical traits and are therefore potential biomarker targets for personalized psychiatry approaches. To better understand individual-specific spatial brain organization, this paper addressed three key goals. First, we determined whether it is possible to reliably estimate weighted (non-binarized) resting-state network maps using data from only a single individual, while also maintaining maximum spatial correspondence across individuals. Second, we determined the degree of spatial overlap between distinct networks, using test-retest and twin data. Third, we systematically tested multiple hypotheses (spatial mixing, temporal switching, and coupling) as candidate explanations for why networks overlap spatially. To estimate weighted network organization, we adopt the Probabilistic Functional Modes (PROFUMO) algorithm, which implements a Bayesian framework with hemodynamic and connectivity priors to supplement optimization for spatial sparsity/independence. Our findings showed that replicable individual-specific estimates of weighted resting-state networks can be derived using high-quality fMRI data within individual subjects. Network organization estimates using only data from each individual subject closely resembled group-informed network estimates (which was not explicitly modeled in our individual-specific analyses), suggesting that cross-subject correspondence was largely maintained. Furthermore, our results confirmed the presence of spatial overlap in network organization, which was replicable across sessions within individuals and in monozygotic twin pairs. Intriguingly, our findings provide evidence that overlap between 2-network pairs is indicative of coupling. These results suggest that regions of network overlap concurrently process information from both contributing networks, potentially pointing to the role of overlapping network organization in the integration of information across multiple brain systems.
CBT-I protocols for insomnia co-morbid with other mental disorders
Insomnia is a frequent co-morbidity of many mental disorders: Almost 70% of patients with mental disorders find it difficult to fall asleep or maintain sleep. Insomnia increases the risk of a negative course of the mental disorder and of poorer treatment efficacy. Cognitive behavioural therapy for insomnia (CBT-I) is effective for the reduction of insomnia in this patient group and has been recommended as a first-line treatment in European and American treatment guidelines. Among different mental disorders, depression is the best investigated co-morbidity (see Chapter 12). A wide range of studies demonstrates the efficacy of CBT-I for the reduction of insomnia. Whereas some studies found a positive effect of CBT-I also on depressive symptoms, other studies could not replicate these effects. Treatment efficacy of CBT-I has also been demonstrated for patients with post-traumatic stress disorder, bipolar disorder and schizophrenia. For depression, bipolar disorder and schizophrenia, research suggests that CBT-I may contribute to the prevention of further episodes of the disease. More research is needed to evaluate the efficacy of CBT-I for patients with yet under-investigated co-morbidities such as ADHD.
From dawn till dusk: Time-adaptive bayesian optimization for neurostimulation
Stimulation optimization has garnered considerable interest in recent years in order to efficiently parametrize neuromodulation-based therapies. To date, efforts focused on automatically identifying settings from parameter spaces that do not change over time. A limitation of these approaches, however, is that they lack consideration for time dependent factors that may influence therapy outcomes. Disease progression and biological rhythmicity are two sources of variation that may influence optimal stimulation settings over time. To account for this, we present a novel time-varying Bayesian optimization (TV-BayesOpt) for tracking the optimum parameter set for neuromodulation therapy. We evaluate the performance of TV-BayesOpt for tracking gradual and periodic slow variations over time. The algorithm was investigated within the context of a computational model of phase-locked deep brain stimulation for treating oscillopathies representative of common movement disorders such as Parkinson’s disease and Essential Tremor. When the optimal stimulation settings changed due to gradual and periodic sources, TV-BayesOpt outperformed standard time-invariant techniques and was able to identify the appropriate stimulation setting. Through incorporation of both a gradual “forgetting” and periodic covariance functions, the algorithm maintained robust performance when a priori knowledge differed from observed variations. This algorithm presents a broad framework that can be leveraged for the treatment of a range of neurological and psychiatric conditions and can be used to track variations in optimal stimulation settings such as amplitude, pulse-width, frequency and phase for invasive and non-invasive neuromodulation strategies.
Parallel Session 2: Neurodegeneration| Wed 18 May, 1115 – 1230|4 Novel complex motor behaviours in LGI1-autoantibody encephalitis
BackgroundPathognomonic clinical signs are increasingly well recognised across the autoim- mune encephalitides. Faciobrachial dystonic seizures (FBDS) are exclusively present in patients with LGI1-autoantibodies. Owing to their recent description and rarity, however, the wider clinical phenotypes remain less well-defined.AimsTo describe novel clinical features in a large cohort of patients with LGI1-autoantibodies.MethodsPatients were recruited for clinical research following either direct referral to the Oxford Autoim- mune Neurology Service, or via notification to the national Association of British Neurologists Rare Disease Ascertainment and Recruitment (RaDaR) Surveillance Unit. Novel clinical signs were identified through clinical assessment of 107 LGI1-autoantibody patients. We use video footage to present the phenotypes.Results5/104* (5%) of patients with LGI1-autoantibodies displayed highly unusual manual stereotypies which we have termed ‘complex motor behaviours’. These behaviours consisted of the patients acting out intricate manual behaviours using imaginary objects, for example drinking from a cup, writing, and imitation of winding a piece of string around the fingers. They typically occurred during sleep or periods of relaxed wakefulness, were of short duration (30-60 seconds), and were associated with loss of awareness. All patients had multiple seizure semiologies (3-5) and associated visual hallucinations and sleep disorder.ConclusionsComplex motor behaviours were observed in 5% of patients with LGI1-autoantibodies and may represent either a novel seizure semiology or the sleep disorder agrypnia excitata. These findings expand the clinical phenotypes of LGI1-autoantibody encephalitis.