Shoulder osteoarthritis most commonly affects older adults, causing pain, reduced function and quality of life. Total shoulder replacements (TSRs) are indicated once other non-surgical options no longer provide adequate pain relief. Two main types of TSRs are widely used: anatomic TSR (aTSR) and reverse TSR (rTSR). It is not clear whether one TSR type provides better short- or long-term outcomes for patients, and which, if either, is more cost-effective for the National Health Service (NHS).

RAPSODI-UK is a multi-centre, pragmatic, two-parallel arm, superiority randomised controlled trial comparing the clinical- and cost-effectiveness of aTSR versus rTSR for adults aged 60+ with a primary diagnosis of osteoarthritis, an intact rotator cuff and bone stock suitable for TSR. Participants in both arms of the trial will receive usual post-operative rehabilitation. We aim to recruit 430 participants from approximately 28 NHS sites across the UK. The primary outcome is the Shoulder Pain and Disability Index (SPADI) at 2 years post-randomisation. Outcomes will be collected at 3, 6, 12, 18 and 24 months after randomisation. Secondary outcomes include the pain and function subscales of the SPADI, the Oxford Shoulder Score, health-related quality of life (EQ-5D-5L), complications, range of movement and strength, revisions and mortality. The between-group difference in the primary outcome will be derived from a constrained longitudinal data analysis model. We will also undertake a full health economic evaluation and conduct qualitative interviews to explore perceptions of acceptability of the two types of TSR and experiences of recovery with a sample of participants.

Ethics committee approval for this trial was obtained (London - Queen Square Research Ethics Committee, Rec Reference 22/LO/0617) on 4 October 2022. The results of the main trial will be submitted for publication in a peer-reviewed journal and using other professional and media outlets.

ISRCTN12216466.

Neurodegenerative disorders (NDDs) represent an unprecedented public health burden. These disorders are clinically heterogeneous and therapeutically challenging, but advances in discovery science and trial methodology offer hope for translation to new treatments. Against this background, there is an urgent unmet need for biomarkers to aid with early and accurate diagnosis, prognosis and monitoring throughout the care pathway and in clinical trials.

Investigations routinely used in clinical care and trials are often invasive, expensive, time-consuming, subjective and ordinal. Speech data represent a potentially scalable, non-invasive, objective and quantifiable digital biomarker that can be acquired remotely and cost-efficiently using mobile devices, and analysed using state-of-the-art speech signal processing and machine learning approaches. This prospective case–control observational study of multiple NDDs aims to deliver a deeply clinically phenotyped longitudinal speech dataset to facilitate development and evaluation of speech biomarkers.

People living with dementia, motor neuron disease, multiple sclerosis and Parkinson’s disease are eligible to participate. Healthy individuals (including relatives or carers of participants with neurological disease) are also eligible to participate as controls. Participants complete a study app with standardised speech recording tasks (including reading, free speech, picture description and verbal fluency tasks) and patient-reported outcome measures of quality of life and mood (EuroQol-5 Dimension-5 Level, Patient Health Questionnaire 2) every 2 months at home or in clinic. Participants also complete disease severity scales, cognitive screening tests and provide optional samples for blood-based biomarkers at baseline and then 6-monthly. Follow-up is scheduled for up to 24 months. Initially, 30 participants will be recruited to each group. Speech recordings and contemporaneous clinical data will be used to create a dataset for development and evaluation of novel speech-based diagnosis and monitoring algorithms.

Digital App for Speech and Health Monitoring Study was approved by the South Central—Hampshire B Ethics Committee (REC ref. 24/SC/0067), NHS Lothian (R&D ref. 2024/0034) and NHS Forth Valley (R&D ref. FV1494). Results of the study will be submitted for publication in peer-reviewed journals and conferences. Data from the study will be shared with other researchers and used to facilitate speech processing challenges for neurological disorders. Regular updates will be provided on the Anne Rowling Regenerative Neurology Clinic web page and social media platforms.

ClinicalTrials.gov NCT06450418 (pre-results).

Childhood cancer survivors (CCSs) experience educational disruptions during and following treatment, yet robust, longitudinal evidence on educational performance remains limited. We will investigate differences in educational outcomes between CCSs and non-cancer peers during primary and secondary school. We will also explore how sociodemographic factors and age at diagnosis contribute to potential differences in General Certificate of Secondary Education (GCSE) examinations, a critical indicator of future academic and employment prospects.

We will use the Education and Child Health Insights from Linked Data (ECHILD) to capture linked health and education data for children born in National Health Service (NHS)-funded hospitals in England. We will generate birth cohorts spanning September 1997 to August 2015 (estimated sample size: ~10 million), formed of pupils expected to have undertaken national curriculum assessments between academic years 2004/2005 and 2021/2022 including Key Stage (KS) 1, 2 and 4, corresponding to ages 7, 11 and 16 respectively. Cancer diagnosis will be identified from inpatient hospital records, using International Classification of Diseases, 10th Revision codes (ICD-10). We will investigate differences between CCS and their non-cancer peers in terms of their sociodemographic characteristics and describe trends in educational performances at all KSs, recorded Special Educational Needs and Disabilities (SEND) and school absences. Differences in KS4 (GCSE) performances between CCS and non-cancer peers will be quantified, according to and accounting for geographic region, sex, deprivation, ethnicity and birth characteristics. To assess whether cancer diagnosis disrupts academic trajectories, we will restrict analysis to those with KS2 attainment data and investigate KS4 performance. We will finally explore the influence of age at diagnosis on educational performance at KS4.

Ethics approval was granted by NHS Health Research Authority Research Ethics Committee (20/EE/0180). Findings will be shared with academics, policymakers, children and families affected by childhood cancer, and published in journals. Code/metadata will be shared on ECHILD GitHub repository.

The COVID-19 pandemic dramatically affected schools. However, there are insufficient data on the chronic physical and mental health consequences of the pandemic in school workers.

To determine the prevalence and the functional and mental health impact of pandemic-related chronic health symptoms among school workers towards the end of the COVID-19 pandemic.

Cross-sectional analysis of health questionnaires and serology testing data (nucleocapsid, N antibodies) collected between January and April 2023, within a cohort of school workers.

Three large school districts (Vancouver, Richmond, Delta) in the Vancouver metropolitan area, Canada (representing 186 elementary and secondary schools in total).

Active school staff employed in these three school districts.

COVID-19 infection history by self-reported viral and/or nucleocapsid antibody testing.

Self-reported, new-onset pandemic-related chronic health symptoms that started within the past year, lasting at least 3 months, after a positive viral test among those with a known infection.

Of 1128 school staff enrolled from 185/186 (99.5%) schools, 1086 (96.3%) and 998 (88.5%) staff completed health questionnaires and serology testing, respectively. The N-seroprevalence adjusted for clustering by school and test sensitivity and specificity was 84.7% (95% Credible Interval (95% CrI): 79.2% to 91.8%) compared with 85.4% (95% CrI: 81.6% to 90.3%) in a community-matched sample of blood donors. Overall, 31.1% (95% CI: 28.4% to 34.0%) staff reported new-onset chronic symptoms. These symptoms were more frequently reported in staff with viral test-confirmed infections (38.0% (95% CI: 34.3% to 41.9%)) compared with those with positive serology who were unaware that they had COVID-19 (14.3% (95% CI: 7.6% to 23.6%); p

The pandemic had major health impacts on school workers. To our knowledge, this study is among the first to concurrently quantify a broad range of chronic physical and mental health impacts, highlighting the need for further research and targeted health programmes to address this significant burden.

Understanding the prognostic factors associated with the failure of total elbow replacement (TER) is crucial for informing patients about risks and enabling shared decision-making regarding TER as a definitive management option. This protocol outlines the planned analysis of National Joint Registry (NJR) data to investigate prognostic factors for TER failure.

The primary analysis will use the NJR elbow dataset, including all eligible patients who underwent TER surgery between April 2012 and December 2023. To incorporate ethnicity and comorbidities as potential prognostic factors, the NJR will be linked to the National Health Service (NHS) England Hospital Episode Statistics-Admitted Patient Care (HES-APC) data for a secondary analysis. The analysis will adhere to the REporting recommendations for tumour MARKer prognostic studies guidelines. The primary outcome under investigation is TER failure, defined as requiring revision surgery. Initially, the overall prognosis of TER will be examined using unadjusted net implant failure via the Kaplan-Meier method. The list of potential prognostic factors to be investigated in this study has been informed by a systematic review on this topic, input from patient and public involvement and engagement (PPIE) groups and a survey shared with healthcare professionals providing TER services. The relationship between each potential prognostic factor and failure will be assessed using univariable regression methods. Based on the findings from our systematic review, the univariable association will also be adjusted for age, sex and indication for TER surgery using multivariable regression methods. The extent of missing data will be reported, and the reasons for missing data will be explored. A very high degree of data completeness is expected, and a complete case analysis will be performed as the primary analysis. Multiple imputations will be considered as a sensitivity analysis.

The NJR research committee approved this analysis, and the NHS Health Research Authority tool guidance dictates that the secondary use of such data for research does not require approval from a research ethics committee. The results from this analysis will be published in a peer-reviewed journal and presented at scientific conferences.

NCT06760585.