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Standard CBT-I protocol for the treatment of insomnia disorder
The purpose of this chapter is to provide an overview of what you might expect to find in a CBT program for insomnia. That is, what would comprise the standard treatment protocol. I have taken the perspective that the published literature provides us with the greatest confidence in knowing what is effective, and so have included, as standard, those elements of CBT that have the strongest evidence base. That said, a feature of the insomnia trials literature is that CBT has typically been evaluated as a multicomponent therapy, so discrete elements have not necessarily been investigated as fully as one might wish, and the contribution of those elements to the overall treatment effect remains largely unknown. Consequently, where a given intervention has been a common component in trials demonstrating the effectiveness of CBT, I have taken the view that there are good grounds for thinking of that intervention as part of the standard protocol. In other words, it is at the very core of CBT for insomnia. Inevitably, I have had to make some choices and some judgements in proposing this standard protocol, and I recognise that others may take a different view. My intention is that the chapter is practical, in keeping with the purpose of this book, rather than heavily referenced to source materials, so I have relied mainly on clinical guidelines, practice parameters and systematic reviews when citing evidence. It is important to note, however, that clinical trials, of which there are many, are readily accessible through these overviews and I would recommend that you look at some of those to see just how varied CBT for insomnia can be, in content, content ordering, in treatment duration and in format of delivery. There are situations, however, where I have felt it helpful, and interesting perhaps, to provide more referencing1; for example, to the scientific and historical roots of CBT. I often feel that these are overlooked. It is very important to appreciate the strength, depth and longevity of our field, even if the terminology we use (and sometimes re-brand) appears as if it is novel! Our confidence that CBT works is also based on this provenance, and the diligent work of countless clinicians and researchers over many decades. Finally, this chapter is provided as a platform upon which other chapters may build. By presenting this standard protocol, focussed primarily in relation to adults with insomnia, applications of CBT to other populations, age groups and circumstances, protocol variations, and emerging approaches to therapeutics can compare, contrast and evolve through the course of the textbook. I have also tried to write as much as possible in plain language, and to share personal accounts of how I would deliver CBT, to make this chapter as clinically informative as possible. If you would like further insight into my approach to the actual delivery of CBT-I, I would refer you to two recent books, one for patients (Espie, 2021) and the other for clinicians (Espie, 2023).
Digital CBT for insomnia
Complaints of insomnia are common, yet provision of the recommended treatment, Cognitive Behavioural Therapy (CBT), is limited. In this chapter we discuss how a digital medicine approach, in the form of CBT delivered by web or mobile (dCBT), could have a transformative impact on insomnia care provision by enabling universal implementation of clinical guidelines for the treatment of insomnia, with consequent improvement in patient outcomes, and patient and clinician satisfaction. We summarize the evidence that supports the potential of dCBT as an evidence-based intervention for insomnia and illustrate ways to advance the implementation of digital medicine for the treatment of insomnia.
Somnotate: A probabilistic sleep stage classifier for studying vigilance state transitions
Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and current computational annotation methods ignore intermediate states because the classification features become ambiguous, even though intermediate states contain important information regarding vigilance state dynamics. To address this problem, we have developed "Somnotate"—a probabilistic classifier based on a combination of linear discriminant analysis (LDA) with a hidden Markov model (HMM). First we demonstrate that Somnotate sets new standards in polysomnography, exhibiting annotation accuracies that exceed human experts on mouse electrophysiological data, remarkable robustness to errors in the training data, compatibility with different recording configurations, and an ability to maintain high accuracy during experimental interventions. However, the key feature of Somnotate is that it quantifies and reports the certainty of its annotations. We leverage this feature to reveal that many intermediate vigilance states cluster around state transitions, whereas others correspond to failed attempts to transition. This enables us to show for the first time that the success rates of different types of transition are differentially affected by experimental manipulations and can explain previously observed sleep patterns. Somnotate is open-source and has the potential to both facilitate the study of sleep stage transitions and offer new insights into the mechanisms underlying sleep-wake dynamics.
Evaluating functional brain organization in individuals and identifying contributions to network overlap
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.
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.
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.