Welcome to the RWT Staff Publications Repository

The repository contains the records of published and unpublished research authored by NHS staff working for the Royal Wolverhampton NHS Trust and its partners. The repository is managed by the Library and Knowledge Services of the Trust and supported by the Non-Medical Research Leads Network Group and the Research and Development Directorate.

If you are a member of RWT staff and you would like to submit an item to the repository, please fill in this online form.

If you have a list of publications you'd like to submit, please e-mail the repository rwh-tr.rwtrepository@nhs.net admin team.

For more information contact the library on 01902 695322 or email or take a look at our website. You will also find guidance on the webpage about publishing your work.

Recent Submissions

  • Item
    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).
  • Item
    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.
  • Item
    The impact of ferric derisomaltose on cardiovascular and noncardiovascular events in patients with anemia, iron deficiency, and heart failure with reduced ejection fraction.
    (Elsevier., 2024-05-01) Spencer, Charles
    Background: In some countries, intravenous ferric derisomaltose (FDI) is only licensed for treating iron deficiency with anemia. Accordingly, we investigated the effects of intravenous FDI in a subgroup of patients with anemia in the IRONMAN (Effectiveness of Intravenous (IV) Iron Treatment Versus Standard Care in Patients With Heart Failure and Iron Deficiency) trial. Method and results: IRONMAN enrolled patients with heart failure, a left ventricular ejection fraction of ≤45%, and iron deficiency (ferritin <100 µg/L or transferrin saturation of <20%), 771 (68%) of whom had anemia (hemoglobin <12 g/dL for women and <13 g/dL for men). Patients were randomized, open label, to FDI (n = 397) or usual care (n = 374) and followed for a median of 2.6 years. The primary end point, recurrent hospitalization for heart failure and cardiovascular death, occurred less frequently for those assigned to FDI (rate ratio 0.78, 95% confidence interval 0.61-1.01; P = .063). First event analysis for cardiovascular death or hospitalization for heart failure, less affected by the coronavirus disease 2019 pandemic, gave similar results (hazard ratio 0.77, 95% confidence interval 0.62-0.96; P = .022). Patients randomized to FDI reported a better Minnesota Living with Heart Failure quality of life, for overall (P = .013) and physical domain (P = .00093) scores at 4 months. Conclusions: In patients with iron deficiency anemia and heart failure with reduced left ventricular ejection fraction, intravenous FDI improves quality of life and may decrease cardiovascular events.
  • Item
    A National audit of the care of patients with acute kidney injury in England and Wales in 2019 and the association with patient outcomes.
    (Elsevier, 2024-03-01) Yin, Bo-Song
    Background: Acute kidney injury (AKI) is a common complication of hospitalisations. This national audit assessed the care received by patients with AKI in hospital Trusts in England and Wales. Methods: Twenty four hospital Trusts across England and Wales took part. Patients with AKI stage2/3 were identified using the UK Renal Registry AKI master patient index. Data was returned through a secure portal with linkage to hospital episode statistic mortality and hospitalisation data. Completion rates of AKI care standards and regional variations in care were established. Results: 989 AKI episodes were included in the analyses. In-hospital 30-day mortality was 31-33.1% (AKI 2/3). Standard AKI interventions were completed in >80% of episodes. Significant inter-hospital variation remained in attainment of AKI care standards after adjustment for age and sex. Recording of urinalysis (41.9%) and timely imaging (37.2%) were low. Information on discharge summaries relating to medication changes/re-commencement and follow-up blood tests associated with reduced mortality. No quality indicators relating to clinical management associated with mortality. Better communication on discharge summaries associated with reduced mortality. Conclusions: Outcomes for patients with AKI in hospital remain poor. Regional variation in care exists. Work is needed to assess whether improving and standardising care improves patient outcomes.
  • Item
    Characteristics of emerging new autoimmune diseases after COVID-19 vaccination: a sub-study by the COVAD group.
    (Wiley, 2024-05-01) Gupta, Latika
    Background: Despite the overall safety and efficacy of COVID-19 vaccinations, rare cases of systemic autoimmune diseases (SAIDs) have been reported post-vaccination. This study used a global survey to analyze SAIDs in susceptible individuals' post-vaccination. Methods: A cross-sectional study was conducted among participants with self-reported new-onset SAIDs using the COVID-19 Vaccination in Autoimmune Diseases (COVAD) 2 study dataset-a validated, patient-reported e-survey-to analyze the long-term safety of COVID-19 vaccines. Baseline characteristics of patients with new-onset SAIDs and vaccinated healthy controls (HCs) were compared after propensity score matching based on age and sex in a 1:4 ratio. Results: Of 16 750 individuals, 74 (median age 52 years, 79.9% females, and 76.7% Caucasians) had new-onset SAID post-vaccination, mainly idiopathic inflammatory myopathies (IIMs) (n = 23, 31.51%), arthritis (n = 15; 20.53%), and polymyalgia rheumatica (PMR) (n = 12, 16.40%). Higher odds of new-onset SAIDs were noted among Caucasians (OR = 5.3; 95% CI = 2.9-9.7; p < .001) and Moderna vaccine recipients (OR = 2.7; 95% CI = 1.3-5.3; p = .004). New-onset SAIDs were associated with AID multimorbidity (OR = 1.4; 95% CI = 1.1-1.7; p < .001), mental health disorders (OR = 1.6; 95% CI = 1.3-1.9; p < .001), and mixed race (OR = 2.2; 95% CI = 1.2-4.2; p = .010), where those aged >60 years (OR = 0.6; 95% CI = 0.4-0.8; p = .007) and from high/medium human development index (HDI) countries (compared to very high HDI) reported fewer events than HCs. Conclusion: This study reports a low occurrence of new-onset SAIDs following COVID-19 vaccination, primarily IIMs, PMR, and inflammatory arthritis. Identified risk factors included pre-existing AID multimorbidity, mental health diseases, and mixed race. Revaccination was well tolerated by most patients; therefore, we recommend continuing COVID-19 vaccination in the general population. However, long-term studies are needed to understand the autoimmune phenomena arising post-vaccination.

Communities in RWT Staff Repository

Select a community to browse its collections.

Now showing 1 - 5 of 13
  • 00- All RWT Publications by Year
    This community lists all the RWT research outputs, collated by year of publication/issue.
  • 01- Division 1 Surgical Division
    This community includes all the groups within the surgical division as of April 2020. Including: Critical Care Services; Cardiology/Cardiothoracic Services; Surgical and Patient Services; Ophthalmology; Womens and Neonatal Group; Trauma and Orthopaedics Group; Head and Neck Group.
  • 02- Division 2 Emergency and Medical Services Division
    This community includes all the groups within the emergency and medical services division as of April 2020. Including: patient access group; rehabilitation and ambulatory group; medical group; emergency services group; oncology and haematology group.
  • 03- Division 3 Community, Childrens and Support Services Division
    This community includes all the groups within the community, childrens and support division as of April 2020. Including: childrens young people and sexual health; adult community and primary care services; diagnostics; pharmacy; therapies and ambulatory care group.
  • 04- Division 4 Corporate Services
    This community includes all the groups within the Division 4 as of May 2021. Including Service efficiency and delivery team; Emergency planning team; Corporate outpatients and Cancer tracking and improvement team.