Alan Carson’s research while affiliated with University of Edinburgh and other places

It is established that patients hospitalised with COVID-19 often have ongoing morbidity affecting activity of daily living (ADL), employment, and mental health. However, little is known about the relative outcomes in patients with COVID-19 neurological or psychiatric complications. We conducted a UK multicentre case–control study of patients hospitalised with COVID-19 (controls) and those who developed COVID-19 associated acute neurological or psychiatric complications (cases). Among the 651 patients, [362 (55%) cases and 289 (45%) controls], a higher proportion of cases had impairment in ADLs (199 [68.9%] vs 101 [51.8%], OR 2.06, p < 0.0002) and reported symptoms impacting employment (159 [58.2%] vs 69 [35.6%] OR 2.53, p < 0.0001). There was no significant difference in the proportion with depression or anxiety between case and control groups overall. For cases, impairment of ADLs was associated with increased risk in female sex, age > 50 years and hypertension (OR 5.43, p < 0.003, 3.11, p = 0.02, 3.66, p = 0.04). Those receiving either statins or angiotensin converting enzyme (ACE) inhibitors had a lower risk of impairment in ADLs (OR 0.09, p = 0.0006, 0.17, p = 0.03). Patients with neurological or psychiatric complications of COVID-19 had worse functional outcomes than those with respiratory COVID-19 alone in terms of ADLs and employment. Female sex, age > 50 years, and hypertension were associated with worse outcomes, and statins or ACE inhibitors with better outcomes.

Individuals who sustain a concussion can experience a range of symptoms which can significantly impact their quality of life and functional outcome. This study aims to understand the nature and recovery trajectories of post-concussion symptomatology by applying an unsupervised machine learning approach to data captured from a digital health intervention (HeadOn). As part of the 35-day program, patients complete a daily symptom diary which rates 8 post-concussion symptoms. Symptom data were analysed using K-means clustering to categorize patients based on their symptom profiles. During the study period, a total of 758 symptom diaries were completed by 84 patients, equating to 6064 individual symptom ratings. Fatigue, sleep disturbance and difficulty concentrating were the most prevalent symptoms reported. A decline in symptom burden was observed over the 35-day period, with physical and emotional symptoms showing early rates of recovery. In a correlation matrix, there were strong positive correlations between low mood and irritability (r = 0.84), and poor memory and difficulty concentrating (r = 0.83). K-means cluster analysis identified three distinct patient clusters based on symptom severity. Cluster 0 (n = 24) had a low symptom burden profile across all the post-concussion symptoms. Cluster 1 (n = 35) had moderate symptom burden but with pronounced fatigue. Cluster 2 (n = 25) had a high symptom burden profile across all the post-concussion symptoms. Reflecting the severity of the clusters, there was a significant relationship between the symptom clusters for both the Rivermead (p = 0.05) and PHQ-9 (p = 0.003) questionnaires at 6-weeks follow-up. By leveraging digital ecological momentary assessments, a rich dataset of daily symptom ratings was captured allowing for the identification of symptom severity clusters. These findings underscore the potential of digital technology and machine learning to enhance our understanding of post-concussion symptomatology and offer a scalable solution to support patients with their recovery.

Background Robust epidemiological data regarding population incidence and prevalence of functional neurological disorder (FND) would be helpful with regards to resource allocation and planning for this disorder, particularly given high symptom burden and high healthcare utilisation. We therefore aimed to systematically review and synthesise available data on FND incidence and prevalence. Methods PubMed was searched to identify original research articles that reported on the incidence or prevalence of FND. Risk of bias assessment for each study was conducted. Incidence and prevalence rates of FND were additionally estimated by extrapolating data from low risk of bias studies on functional seizures alone. Results Thirty-nine articles were included. Nineteen reported on FND incidence, 21 reported on prevalence. Comparison between studies was difficult due to methodological differences and significant heterogeneity of incidence and prevalence estimates was found. The incidence of FND was estimated at 10–22/100 00, while minimum prevalence of FND was estimated at 80–140/100 000, with a possible range of 50–1600/100 000. Incidence of paediatric FND was estimated to be between 1 and 18/100 000. Conclusions The range of incidence and prevalence varies widely across studies, with significant heterogeneity among studies and most studies likely provide underestimates due to methodological challenges. However, using our best method as a conservative estimate, there are likely a minimum of 50–100 000 people with FND in the UK, as an example country. Given that FND appears to be more prevalent than many other well-known and well-funded neurological disorders, incidence and prevalence data suggested here indicate the need for greater research and clinical funding allocation to FND programmes.

The spectrum, pathophysiology, and recovery trajectory of persistent post-COVID-19 cognitive deficits are unknown, limiting our ability to develop prevention and treatment strategies. We report the one-year cognitive, serum biomarker, and neuroimaging findings from a prospective, national study of cognition in 351 COVID-19 patients who had required hospitalisation, compared to 2,927 normative matched controls. Cognitive deficits were global and associated with elevated brain injury markers, and reduced anterior cingulate cortex volume one year after COVID-19. The severity of the initial infective insult, post-acute psychiatric symptoms, and a history of encephalopathy were associated with greatest deficits. There was strong concordance between subjective and objective cognitive deficits. Longitudinal follow-up in 106 patients demonstrated a trend toward recovery. Together, these findings support the hypothesis that brain injury in moderate to severe COVID-19 may be immune-mediated, and should guide the development of therapeutic strategies.

Functional neurological disorder (FND) is continuing to gain increasing recognition globally as a valid and potentially treatable disorder. Iatrogenic harm towards patients with FND is significant, however, and has been around for centuries. Despite advances in our understanding around the aetiology, pathophysiology and treatment of FND, many aspects of such harm continue to persist. Avoidance of iatrogenic harm has been highlighted by clinicians as one of the most important therapeutic considerations in FND; however, the sources and range of potential harms, or indeed ways to mitigate them, have not previously been summarized. Using a combination of clinical and research experience and scoping review methodology, this review aims to describe the main sources of iatrogenic harm towards patients with FND, including harm from misdiagnosis, delayed diagnosis and treatment, direct harm from professional interactions, other stigma-related harms, harm related to diagnostic overshadowing and over-diagnosis of FND. We also describe some potential ways to address and prevent such harms, such as ways to reduce misdiagnosis with a focus on rule in signs, optimizing teaching and communication, ensuring parity of FND with other medical conditions and continued integration of patient and professional organizations.

Even within a single protein, antibody binding can have beneficial, neutral, or harmful effects during the response to infection. Resolving a polyclonal antibody repertoire across a pathogen’s proteome to specific epitopes may therefore explain much of the heterogeneity in susceptibility to infectious disease. However, the three-dimensional nature of antibody-epitope interactions makes the discovery of non-obvious targets challenging. We implemented a novel computational method and synthetic biology pipeline for identifying epitopes that are functionally important in the SARS-CoV-2 proteome and identified an IgM-dominant response to an exposed Membrane protein epitope which to our knowledge is the strongest correlate of severe disease identified to date (adjusted OR 72.14, 95% CI: 9.71 – 1300.15), stronger even than the exponential association of severe disease with age. We also identify persistence (> 2 years) of this IgM response in individuals with longCOVID, and a correlation with fatigue and depression symptom burden. The repetitive arrangement of this epitope and the pattern of isotype class switching is consistent with this being a previously unrecognized T independent antigen. These findings point to a coronavirus host-pathogen interaction characteristic of severe virus driven immune pathology. This epitope is a promising vaccine and therapeutic target as it is highly conserved through SARS-CoV-2 variant evolution in humans to date and in related coronaviruses (e.g. SARS-CoV), showing far less evolutionary plasticity than targets on the Spike protein. This provides a promising biomarker for longCOVID and a target to complement Spike-directed vaccination which could broaden humoral protection from severe or persistent disease or novel coronavirus spillovers.

Even within a single protein, antibody binding can have beneficial, neutral, or harmful effects during the response to infection. Resolving a polyclonal antibody repertoire across a pathogen’s proteome to specific epitopes may therefore explain much of the heterogeneity in susceptibility to infectious disease. However, the three-dimensional nature of antibody-epitope interactions makes the discovery of non-obvious targets challenging. We implemented a novel computational method and synthetic biology pipeline for identifying epitopes that are functionally important in the SARS-CoV-2 proteome and identified an IgM-dominant response to an exposed Membrane protein epitope which to our knowledge is the strongest correlate of severe disease identified to date (adjusted OR 72.14, 95% CI: 9.71 – 1300.15), stronger even than the exponential association of severe disease with age. We also identify persistence (> 2 years) of this IgM response in individuals with longCOVID, and a correlation with fatigue and depression symptom burden. The repetitive arrangement of this epitope and the pattern of isotype class switching is consistent with this being a previously unrecognized T independent antigen. These findings point to a coronavirus host-pathogen interaction characteristic of severe virus driven immune pathology. This epitope is a promising vaccine and therapeutic target as it is highly conserved through SARS-CoV-2 variant evolution in humans to date and in related coronaviruses (e.g. SARS-CoV), showing far less evolutionary plasticity than targets on the Spike protein. This provides a promising biomarker for longCOVID and a target to complement Spike-directed vaccination which could broaden humoral protection from severe or persistent disease or novel coronavirus spillovers.

The COgnitive behavioural therapy versus standardised medical care for adults with Dissociative non-Epileptic Seizures multicentre randomised controlled trial is the largest, fully-powered study to test the clinical and cost-effectiveness of a psychotherapeutic intervention in this population. We also explored predictors or moderators of outcomes and investigated mechanisms of change in therapy. In this current review of findings, we discuss issues related to the design of the trial and consider the study’s nested qualitative studies which were undertaken not only to shed light on the original research questions but to provide insights and recommendations for other researchers in the field of functional neurological disorder. Finally, we consider issues relating to the possible clinical application of our study findings.