2023 Publications

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Now showing 1 - 5 of 239
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    Optimization of the design of rigid ankle foot orthoses (AFOs).
    (International Society for Prosthetics and Orthotics., 2023-04-24) Eddison, Nicola
    The aim of the study was to quantify the effect that AFO thickness and the design of reinforcing features have on AFO stiffness and to set the basis for quantitative guidelines for the design optimisation of rigid ankle AFOs.
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    Do UK prosthetists and orthotists have adequate guidelines and training to provide telehealth patient consultations?
    (International Society for Prosthetics and Orthotics., 2023-04-23) Eddison, Nicola
    The aim of this study was to explore the UK prosthetic and orthotic services’ organisational telehealth readiness, focusing on guideline implementation and staff training, through the perspectives of NHS prosthetists and orthotists.
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    Estimating the likelihood of epilepsy from clinically non-contributory EEG using computational analysis: a retrospective, multi-site case-control study.
    (medRxiv., 2023-03-16) Manfredonia, Francesco; Tittensor, Phil
    Background A retrospective, multi-site case control study was carried out to validate a set of candidate biomarkers of seizure susceptibility. The objective was to determine the robustness of these biomarkers derived from routinely collected EEG within a large cohort (both epilepsy and common alternative conditions which may present with a possible seizure, such as NEAD). Methods The database consisted of 814 EEG recordings from 648 subjects, collected from 8 NHS sites across the UK. Clinically non-contributory EEG recordings were identified by an experienced clinical scientist (N = 281; 152 alternative conditions, 129 epilepsy). Eight computational markers (spectral [N = 2], network-based [N = 4] and model-based [N = 2]) were calculated within each recording. Ensemble-based classifiers were developed using a two-tier cross-validation approach. We used standard regression methods in order to identify whether potential confounding variables (e.g. age, gender, treatment-status, comorbidity) impacted model performance. Findings We found levels of balanced accuracy of 68% across the cohort with clinically non-contributory normal EEGs (sensitivity: 61%, specificity: 75%, positive predictive value: 55%, negative predictive value: 79%, diagnostic odds ratio: 4.64). Group-level analysis found no evidence suggesting any of the potential confounding variables significantly impacted the overall performance. Interpretation These results provide evidence that the set of biomarkers could provide additional value to clinical decision-making, providing the foundation for a decision support tool that could reduce diagnostic delay and misdiagnosis rates. Future work should therefore assess the change in diagnostic yield and time to diagnosis when utilising these biomarkers in carefully designed prospective studies. Evidence before this study We searched Google Scholar and Pubmed (March 21, 2022) for the following phrases ((“EEG” OR “electroencephalogram” OR “electroencephalography”) AND (“biomarker”) AND (“epilepsy” OR “seizure”) AND (“resting state” OR “resting-state”) OR (“normal”)). Several of the existing studies developed deep learning approaches for identifying the presence of interictal epileptiform discharges (IED), with the overarching aim to develop an automated stand-alone diagnostic tool. These approaches are particularly sensitive to the potential presence of artefacts in the EEG recordings and typically include spectral rather than network- or model-based features. We found no studies of more than 100 participants that assessed the cross-validated performance of candidate biomarkers on routine EEG recordings that were clinically non-contributory. One study found near-chance performance of a deep-learning based method using spectral features on a smaller cohort of people suspected of epilepsy (N=33 epilepsy; N=30 alternative conditions) with clinically non-contributory EEGs. Another study found overall accuracy of 69% (N=74 epilepsy; N=74 alternative conditions) but this framework did not use any independent cross-validation methods. Estimates of sensitivity of clinical markers of seizure susceptibility in routine EEG recordings vary between 17-56%. To the best of our knowledge no studies have assessed whether computational biomarkers offer sufficient discrimination between people with epilepsy and an alternative diagnosis to provide potential decision support for people with suspected epilepsy. Added value of this study We show that data-driven analysis of routinely collected EEGs that are currently considered clinically non-informative (i.e. absence of apparent epileptiform activity) can be used to distinguish EEGs from people with epilepsy from people with an alternative diagnosis with better-than-chance performance. To the best of our knowledge, this is the largest retrospective study assessing the performance of computational biomarkers derived from clinically non-contributory EEG recordings. The resulting statistical model is interpretable and relies on both spectral and computational (network- and model-based) features. We perform a series of validity and sensitivity analysis to assess the overall robustness of the final statistical model used for classification. We also conduct several statistical tests to analyse any shared characteristics (e.g. site, comorbidity) amongst the primary classes (FP, FN, TP, TN). These findings validate previous biomarker discovery- or development-studies, and provide evidence that they offer better-than-chance performance in a clinically relevant context. Future large-scale studies could consider combining these methods with interictal features for non-specialist settings. Implications of all the available evidence Our study presents evidence that computational analysis of clinically non-contributory EEGs could provide additional decision support for both epilepsy and alternative conditions. Since the statistical model and underlying features are interpretable, they could provide the starting point for further exploring the mechanisms that drive overall seizure-likelihood. Future work should focus on prospective testing and validation (e.g. identification of specific situations or cases in which these methods could be of added value) as well as assessing heterogeneity across different syndromes and diagnoses (e.g. NEAD, focal vs generalised epilepsy).
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    Awareness of social care needs in people with epilepsy and intellectual disability.
    (Elsevier., 2023-08-01) Tittensor, Phil
    Background: Nearly a quarter of people with intellectual disability (ID) have epilepsy with large numbers experiencing drug-resistant epilepsy, and premature mortality. To mitigate epilepsy risks the environment and social care needs, particularly in professional care settings, need to be met. Purpose: To compare professional care groups as regards their subjective confidence and perceived responsibility when managing the need of people with ID and epilepsy. Method: A multi-agency expert panel developed a questionnaire with embedded case vignettes with quantitative and qualitative elements to understand training and confidence in the health and social determinants of people with ID and epilepsy. The cross-sectional survey was disseminated amongst health and social care professionals working with people with ID in the UK using an exponential non-discriminative snow-balling methodology. Group comparisons were undertaken using suitable statistical tests including Fisher's exact, Kruskal-Wallis, and Mann-Whitney. Bonferroni correction was applied to significant (p < 0.05) results. Content analysis was conducted and relevant categories and themes were identified. Results: Social and health professionals (n = 54) rated their confidence to manage the needs of people with ID and epilepsy equally. Health professionals showed better awareness (p < 0.001) of the findings/recommendations of the latest evidence on premature deaths and identifying and managing epilepsy-related risks, including the relevance of nocturnal monitoring. The content analysis highlighted the need for clearer roles, improved care pathways, better epilepsy-specific knowledge, increased resources, and better multi-disciplinary work. Conclusions: A gap exists between health and social care professionals in awareness of epilepsy needs for people with ID, requiring essential training and national pathways.
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    Anaesthetics and intensive care medicine as a foundation year doctor.
    (Sage., 2023-11-01) Blair, James A
    A foundation year rotation in anaesthetics and/or ICM can provide the ideal environment to begin your career as a doctor with a variety of learning opportunities available. The development of both technical and non-technical skills will be valuable for doctors wishing to pursue a career in any field of medicine or surgery. Foundation programme directors need to work with hospitals to ensure greater access to anaesthetics and ICM during foundation training..