Predicting a diagnosis of ankylosing spondylitis using primary care health records–A machine learning approach

Ankylosing spondylitis is the second most common cause of inflammatory arthritis. However, a successful diagnosis can take a decade to confirm from symptom onset (via x-rays). The aim of this study was to use machine learning methods to develop a profile of the characteristics of people who are likely to be given a diagnosis of AS in future. The Secure Anonymised Information Linkage databank was used. Patients with ankylosing spondylitis were identified using their routine data and matched with controls who had no record of a diagnosis of ankylosing spondylitis or axial spondyloarthritis. Data was analysed separately for men and women. The model was developed using feature/variable selection and principal component analysis to develop decision trees. The decision tree with the highest average F value was selected and validated with a test dataset. The model for men indicated that lower back pain, uveitis, and NSAID use under age 20 is associated with AS development. The model for women showed an older age of symptom presentation compared to men with back pain and multiple pain relief medications. The models showed good prediction (positive predictive value 70%-80%) in test data but in the general population where prevalence is very low (0.09% of the population in this dataset) the positive predictive value would be very low (0.33%-0.25%). Machine learning can be used to help profile and understand the characteristics of people who will develop AS, and in test datasets with artificially high prevalence, will perform well. However, when applied to a general population with low prevalence rates, such as that in primary care, the positive predictive value for even the best model would be 1.4%. Multiple models may be needed to narrow down the population over time to improve the predictive value and therefore reduce the time to diagnosis of ankylosing spondylitis

Biologic use in psoriatic arthritis and ankylosing spondylitis patients: a descriptive epidemiological study using linked, routine data in Wales, UK

ObjectivesPsA and AS are chronic diseases associated with significant morbidities. National and international management guidelines include treatment with biologic therapies to improve outcomes and quality of life. There are limited real-world data on the patients’ journey from symptom onset to diagnosis and treatment in the UK. We use real-life, linked health data to explore patient pathways and the impact of biologics on patient outcomes.MethodsData from the Secure Anonymised Information Linkage databank in Wales were used to assess diagnosis and treatment of patients ≥18 years of age with at least one International Classification of Diseases, Tenth Revision code present for PsA/AS in rheumatology clinic data and at least one Read code present in primary care records. We investigated the use of biologics while exploring demographics, comorbidities and surgical procedures of 641 AS patients and 1312 PsA patients.ResultsAS patients were significantly younger at diagnosis and were predominantly male. The average time from presenting symptoms to diagnosis of AS and PsA was 7.9 (S.D. 5.5) and 9.3 (S.D. 5.5) years, respectively. The proportion of patients receiving biologic treatment was significantly higher in AS (46%) compared with PsA patients (28.8%); of these, 23.1% of AS and 22.2% of PsA patients stopped/switched a biologic. There was a significant reduction in primary care involvement, sick notes and disability living allowance for both AS and PsA patients following biologic initiation.ConclusionThis real-world descriptive study confirms that patients treated with biologics have reduced disability and time off work despite being initiated ∼13 years after the first symptoms and 6 years after diagnosis

Impact of school closures on the health and well-being of primary school children in Wales UK: a routine data linkage study using the HAPPEN Survey (2018–2020)

Objectives: This study aimed to explore the relationship between initial school closures and children’s health by comparing health and well-being outcomes collected during school closures (April–June 2020) via HAPPEN (the Health and Attainment of Pupils in a Primary Education Network) with data from the same period in 2019 and 2018 via the HAPPEN Survey. Setting: The study was conducted online with 161 primary schools across Wales involved in the ‘HAPPEN At Home’ Survey. Participants: Data were collected via the ‘HAPPEN At Home’ Survey capturing the typical health behaviours of children aged 8–11 years from 1333 participants across Wales. These data were compared with data in 2018 and 2019 also collected between April and June, from HAPPEN (2019 (n=1150) and 2018 (n=475)). Primary and secondary outcome measures: Primary outcomes included validated measures of physical activity, screen time, diet and dental health, as well as well-being, competency and autonomy. Free school meal (FSM) status was used as a proxy for socioeconomic deprivation. Analyses were repeated stratifying by FSM. Results: Comparing responses between April–June in 2020 (n=1068), 2019 (n=1150) and 2018 (n=475), there were improvements in physical activity levels, sleep time, happiness and general well-being for children during school closures compared with previous years. However, children on FSM ate fewer fruits and vegetables (21% less at five or more portions of fruits and vegetables (95% CI: 5.7% to 37%)) and had lower self-assessed school competence compared with 2019. Compared with those not on FSM, they also spent less time doing physical activity (13.03%, 95% CI: 3.3% to 21.7%) and consumed more takeaways (16.3%, 95% CI: 2% to 30%) during school closures. Conclusions: This study suggests that schools are important in reducing inequalities in physical health. The physical health (eg, physical activity and diet) of children eligible for FSM may be affected by prolonged school closures

Concept Libraries for Repeatable and Reusable Research: Qualitative Study Exploring the Needs of Users

Background:Big data research in the field of health sciences is hindered by a lack of agreement on how to identify and define different conditions and their medications. This means that researchers and health professionals often have different phenotype definitions for the same condition. This lack of agreement makes it difficult to compare different study findings and hinders the ability to conduct repeatable and reusable research.Objective:This study aims to examine the requirements of various users, such as researchers, clinicians, machine learning experts, and managers, in the development of a data portal for phenotypes (a concept library).Methods:This was a qualitative study using interviews and focus group discussion. One-to-one interviews were conducted with researchers, clinicians, machine learning experts, and senior research managers in health data science (N=6) to explore their specific needs in the development of a concept library. In addition, a focus group discussion with researchers (N=14) working with the Secured Anonymized Information Linkage databank, a national eHealth data linkage infrastructure, was held to perform a SWOT (strengths, weaknesses, opportunities, and threats) analysis for the phenotyping system and the proposed concept library. The interviews and focus group discussion were transcribed verbatim, and 2 thematic analyses were performed.Results:Most of the participants thought that the prototype concept library would be a very helpful resource for conducting repeatable research, but they specified that many requirements are needed before its development. Although all the participants stated that they were aware of some existing concept libraries, most of them expressed negative perceptions about them. The participants mentioned several facilitators that would stimulate them to share their work and reuse the work of others, and they pointed out several barriers that could inhibit them from sharing their work and reusing the work of others. The participants suggested some developments that they would like to see to improve reproducible research output using routine data.Conclusions:The study indicated that most interviewees valued a concept library for phenotypes. However, only half of the participants felt that they would contribute by providing definitions for the concept library, and they reported many barriers regarding sharing their work on a publicly accessible platform. Analysis of interviews and the focus group discussion revealed that different stakeholders have different requirements, facilitators, barriers, and concerns about a prototype concept library

Timing of parental depression on risk of child depression and poor educational outcomes: A population based routine data cohort study from Born in Wales, UK

Background: Maternal depression is a risk factor for depression in children, though the influence of paternal depression has been less well examined. We examined the association between maternal and paternal depression, and the timing of their depression (before or after the child’s birth) and outcomes for the child including incidence of child depression and poor educational attainment. Methods: A linked routine data cohort study linking General Practitioner(GP), hospital and education records of young people (aged 0 to 30 years) in Wales. Parental and child diagnosis of depression was identified from GP data. Regression analysis examined the association of maternal and paternal depression with time to diagnosis of depression in the child and odds of attaining educational milestones. Outcomes: In adjusted models, the relative risk of offspring developing depression was 1.22 if the mother had depression before the child was born, 1.55 if the mother had depression after the child was born and 1.73 if she had depression both before and after the child was born (chronic depression), compared to those were there was no maternal depression history. For achieving milestones at end of primary school, odds were 0.92, 0.88 and 0.79 respectively. Association of depression in the child was similar if the male living in the household had depression with risk ratios of 1.24 (before), 1.43 (after) and 1.27 (before and after) for child diagnosed depression and 0.85, 0.79 and 0.74 for achieving age 11 milestones. Interpretation: Children who live with a parent who has depression are more likely to develop depression and not achieve educational milestones, compared to children who live with a parent who has a history of depression (but no active depression in child’s lifetime) and compared to those with no depression. This finding suggests that working closely with families where depression (particularly chronic depression) is present in either parent and treating parental depression to remission is likely to have long-term benefits for children’s mental health and educational attainment

Shielding reduced incidence of COVID-19 in patients with inflammatory arthritis but vulnerability is associated with increased mortality

ObjectivesInvestigate whether individuals with inflammatory arthritis (IA), their treatments and shielding status affect the risk of adverse outcomes from COVID-19 for the entire population of Wales, UK.MethodsRetrospective, population-based cohort study using linked, anonymized electronic health data from SAIL Databank, including primary/secondary care, rheumatology, Office for National Statistics Mortality and COVID-19 laboratory data. Individuals aged 18 years and over testing positive for COVID-19 between March 2020 and May 2021 with READ Codes present for rheumatoid arthritis, psoriatic arthritis and ankylosing spondylitis formed the study cases.ResultsA total of 1966 people with IA and 166 602 without tested positive for COVID-19. The incidence rate was 3.5% (1966/56 914) in IA, vs 6% in the general population (166 602/2 760 442), (difference: 2.5%, 95% CI: 2.4%, 2.7%, P ≤0.001). In an adjusted Cox proportional hazard model, IA was not associated with higher mortality (HR: 0.56, 95% CI: 0.18, 1.64, P=0.286). Significant risk factors included shielding (HR: 1.52, 95% CI: 1.40, 1.64, P ≤0.001), hospitalization for previous infections (HR: 1.20, 95% CI: 1.12, 1.28, P ≤0.001), hospitalizations one year pre-pandemic (HR: 1.34, 95% CI: 1.25, 1.44, P ≤0.001) and glucocorticoid use (HR: 1.17, 95% CI: 1.09, 1.25, P ≤0.001).ConclusionsIndividuals with IA had a lower incidence of COVID-19, probably due to shielding. IA was not associated with increased mortality following COVID-19 infection; being vulnerable (shielded), comorbidities and other factors were associated with increased risk. These key risk factors can identify individuals with IA at greater risk from COVID-19 and advised to shield during high community prevalence

The Daily Mile: Whole-school recommendations for implementation and sustainability. A mixed-methods study

Regular physical activity (PA) during childhood is associated with a range of positive health outcomes and higher educational attainment. However, only 2.0% to 14.7% of girls and 9.5% to 34.1% of boys are meeting the current PA guidelines of 60 minutes of moderate to vigorous PA daily. Schools are targeted as a key setting to improve children's PA levels. The Daily Mile (TDM), a teacher-led 15 minute PA intervention was established in 2012 and has been widely adopted globally. However, the dynamic school environment generates challenges for school-based interventions to follow a uniform implementation method resulting in sustainability issues and limited evaluation. The aims of this mixed-methods study were to (1) explore whether whole-school experiences of TDM were related to implementation and (2) examine the association between TDM and CRF in children from high and low socio-economic groups. Focus groups with pupils (n = 6) and interviews with teachers (n = 9) and headteachers (n = 2) were conducted to explore factors associated with successful implementation. Pupils (n = 258 imputed) aged 9-11 from six primary schools in south Wales, United Kingdom participated in CRF assessments (20m shuttle run test) at two time-points (baseline, 6 month follow-up). Thematic analyses of qualitative measures and linear regression analyses of quantitative measures were used to assess the research questions. Qualitative findings identified implementation factors associated with a positive experience of TDM; flexible and adaptable, not replacing current play provision but delivered as an additional playtime, incorporate personal goal setting, teacher participation, whole-school delivery with community support. Both groups demonstrated equal increases in shuttles between baseline and follow-up (deprived: 4.7 ± 13.4, non-deprived: 4.8 ± 16.0). There was no significant difference in this increase for deprived compared to non-deprived children adjusted for age and gender. Findings from this study provide a set of recommendations for the future implementation and sustainability of TDM