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Abstract Background Some children and young people (CYP) infected with SARS-COV-2 experience impairing symptoms post-infection, known as post-COVID-19 condition (PCC). Using data from the National Long COVID in Children and Young People (CloCk) study, we report symptoms and their impact up to 24-months post-infection. Methods CloCk is a cohort of CYP in England aged 11-to-17-years when they had a SARS-CoV-2 PCR-test (between September 2020 and March 2021). Of 31,012 eligible CYP 24-months post-PCR test, 12,632 participated (response = 40.7%). CYP were grouped by infection status: ‘initial test-negatives; no subsequent positive-test’ (NN); ‘initial test-negatives; subsequent positive-test’ (NP); ‘initial test-positives; no reported re-infection’ (PN); and ‘initial test-positives; reported re-infection’ (PP). The Delphi research definition of PCC in CYP was operationalised; symptom severity/impact and validated scales (e.g., Chalder Fatigue Scale) were recorded. We examine symptom profiles 24-month post-index-test by infection status. Results 7.2% of CYP consistently fulfil the PCC definition at 3-, 6-, 12- and 24-months. These CYPs have a median of 5-to-6 symptoms at each time-point. Between 20% and 25% of all infection status groups report 3+ symptoms 24-months post-testing; 10–25% experience 5+ symptoms. The reinfected group has more symptoms than the other positive groups; the NN group has the lowest symptom burden (p

Abstract Background Predicting which children and young people (CYP) are at the highest risk of developing post-COVID-19 condition (PCC) could improve care pathways. We aim to develop and validate prediction models for persistent PCC up to 24 months post-infection in CYP. Methods CYP who were PCR-positive between September 2020 and March 2021, with follow-up data up to 24-months post-infection, were analysed. Persistent PCC was defined in two ways, as PCC at (a) 3, 6, 12 and 24 months post-infection (N = 943) or (b) 6, 12 and 24 months post-infection (N = 2373). Prediction models were developed using logistic regression; performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping; the final model was adjusted for overfitting. Results While 24.7% (233/943) of CYP met the PCC definition 3 months post-infection, only 7.2% (68/943) continued to meet the PCC definition at all three subsequent timepoints, i.e. at 6, 12 and 24 months. The final models predicting risk of persistent PCC (at 3, 6, 12 and 24 months and at 6, 12 and 24 months) contained sex (female), history of asthma, allergy problems, learning difficulties at school and family history of ongoing COVID-19 problems, with additional variables (e.g. older age at infection and region of residence) in the model predicting PCC at 6, 12 and 24 months. Internal validation showed minimal overfitting of models with good calibration and discrimination measures (optimism-adjusted calibration slope: 1.064–1.142; C-statistic: 0.724–0.755). Conclusions To our knowledge, these are the only prediction models estimating the risk of CYP persistently meeting the PCC definition up to 24 months post-infection. The models could be used to triage CYP after infection. CYP with factors predicting longer-term symptomology, may benefit from earlier support.

Abstract Our previous study in children and young people (CYP) at 3- and 6-months post-infection showed that 12–16% of those infected with the Omicron (B.1.1.529) variant of SARS-CoV-2 met the research definition of Long Covid, with no differences between first-positive and reinfected CYP. The primary objective of the current study is to explore the impact of the Omicron variant of SARS-CoV-2 infection on young people 12 months post infection. 345 CYP aged 11–17 years with a first laboratory-confirmed infection with the Omicron variant and 360 CYP reinfected with the Omicron variant completed an online questionnaire assessing demographics, symptoms, and their impact shortly after testing and again at 3-, 6-and 12-months post-testing. Vaccination status was determined from information held at UKHSA. Comparisons between groups were made using chi-squared, Mann–Whitney U, and Kruskal–Wallis tests. The most common symptoms in first-positive and reinfected CYP 12-months post-testing were tiredness (35.7 and 33.6% respectively) and sleeping difficulties (27.5 and 28.3% respectively). Symptom profiles, severity and impact were similar in the two infection status groups. Overall, by 12-months, 17.4% of first-positives and 21.9% of reinfected CYP fulfilled the research consensus Long Covid definition (p = 0.13). 12-months post Omicron infection, there is little difference between first-positive and reinfected CYP with respect to symptom profiles and impact. Clinicians may not therefore need to consider number of infections and type of variant when developing treatment plans. Further studies are needed to assess causality of reported symptoms up to 12-months after SARS-CoV-2 infection.

Abstract Background To update and internally validate a model to predict children and young people (CYP) most likely to experience long COVID (i.e. at least one impairing symptom) 3 months after SARS-CoV-2 PCR testing and to determine whether the impact of predictors differed by SARS-CoV-2 status. Methods Data from a nationally matched cohort of SARS-CoV-2 test-positive and test-negative CYP aged 11–17 years was used. The main outcome measure, long COVID, was defined as one or more impairing symptoms 3 months after PCR testing. Potential pre-specified predictors included SARS-CoV-2 status, sex, age, ethnicity, deprivation, quality of life/functioning (five EQ-5D-Y items), physical and mental health and loneliness (prior to testing) and number of symptoms at testing. The model was developed using logistic regression; performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping and the final model was adjusted for overfitting. Results A total of 7139 (3246 test-positives, 3893 test-negatives) completing a questionnaire 3 months post-test were included. 25.2% (817/3246) of SARS-CoV-2 PCR-positives and 18.5% (719/3893) of SARS-CoV-2 PCR-negatives had one or more impairing symptoms 3 months post-test. The final model contained SARS-CoV-2 status, number of symptoms at testing, sex, age, ethnicity, physical and mental health, loneliness and four EQ-5D-Y items before testing. Internal validation showed minimal overfitting with excellent calibration and discrimination measures (optimism-adjusted calibration slope: 0.96575; C-statistic: 0.83130). Conclusions We updated a risk prediction equation to identify those most at risk of long COVID 3 months after a SARS-CoV-2 PCR test which could serve as a useful triage and management tool for CYP during the ongoing pandemic. External validation is required before large-scale implementation.

Background Little is known about the prevalence and natural trajectory of post-COVID symptoms in young people, despite very high numbers of young people having acute COVID. To date, there has been no prospective follow-up to establish the pattern of symptoms over a 6-month time period. Methods A non-hospitalised, national sample of 3,395 (1,737 SARS-COV-2 Negative;1,658 SARS-COV-2 Positive at baseline) children and young people (CYP) aged 11–17 completed questionnaires 3 and 6 months after PCR-confirmed SARS-CoV-2 infection between January and March 2021 and were compared with age, sex and geographically-matched test-negative CYP. Results Three months after a positive SARS-CoV-2 PCR test, 11 of the 21 most common symptoms reported by >10% of CYP had reduced. There was a further decline at 6 months. By 3 and 6 months the prevalence of chills, fever, myalgia, cough and sore throat of CYP who tested positive for SARS-CoV-2 reduced from 10–25% at testing to Conclusions In CYP, the prevalence of specific symptoms reported at time of PCR-testing declined with time. Similar patterns were observed among test-positives and test-negatives and new symptoms were reported six months post-test for both groups suggesting that symptoms are unlikely to exclusively be a specific consequence of SARS-COV-2 infection. Many CYP experienced unwanted symptoms that warrant investigation and potential intervention.

Background: Post-COVID services have been set up in England to treat children with ongoing symptoms of Long COVID. To date, the characteristics of children seeking treatment from these services has not been described. Purpose: (1) to describe the characteristics of children aged 11–17 referred to the Pan-London Post-COVID service and (2) to compare characteristics of these children with those taking part in the United Kingdom’s largest research study of Long COVID in children (CLoCk). Design: Data from 95 children seeking treatment from the Post-COVID service between May 2021 and August 2022 were included in the study. Their demographic characteristics, symptom burden and the impact of infection are described and compared to children from CLoCk. Results: A high proportion of children from the Post-COVID service and CLoCk reported experiencing health problems prior to the pandemic. Almost all Post-COVID service children met the research Delphi definition of Long COVID (94.6%), having multiple symptoms that impacted their lives. Symptoms were notably more severe than the participants in CLoCk. Conclusions: This study describes the characteristics of children seeking treatment for Long COVID compared to those identified in the largest longitudinal observational study to date. Post-COVID service children have more symptoms and are more severely affected by their symptoms following infection with COVID-19 than children in the CLoCk study. Research to understand predisposing factors for severity and prognostic indicators is essential to prevent this debilitating condition. Evaluation of short- and long-term outcomes of interventions by clinical services can help direct future therapy for this group.

Background: Although 99% of children and young people have been exposed to SARS-CoV-2, the long-term prevalence of post-COVID-19 symptoms in young people is unclear. The aim of this study is to describe symptom profiles 12 months after SARS-CoV-2 testing. Method: A matched cohort study of a national sample of 20,202 children and young people who took a SARS-CoV-2 PCR test between September 2020 and March 2021. Results: 12 months post-index-test, there was a difference in the number of symptoms reported by initial negatives who never tested positive (NN) compared to the other three groups who had at least one positive test (p < 0.001). Similarly, 10.2% of the NN group described five-plus symptoms at 12 months compared to 15.9–24.0% in the other three groups who had at least one positive test. The most common symptoms were tiredness, sleeping difficulties, shortness of breath, and headaches for all four groups. For all these symptoms, the initial test positives with subsequent reports of re-infection had higher prevalences than other positive groups (p < 0.001). Symptom profiles, mental health, well-being, fatigue, and quality of life did not vary by vaccination status. Conclusions: Following the pandemic, many young people, particularly those that have had multiple SARS-CoV-2 positive tests, experience a range of symptoms that warrant consideration and potential investigation and intervention.

Summary: Background: Delayed diagnosis and treatment of sight threatening diabetic retinopathy (STDR) is a common cause of visual impairment in people with Type 2 diabetes. Therefore, systematic regular retinal screening is recommended, but global coverage of such services is challenging. We aimed to develop and validate predictive models for STDR to identify ‘at-risk’ population for retinal screening. Methods: Models were developed using datasets obtained from general practices in inner London, United Kingdom (UK) on adults with type 2 Diabetes during the period 2007–2017. Three models were developed using Cox regression and model performance was assessed using C statistic, calibration slope and observed to expected ratio measures. Models were externally validated in cohorts from Wales, UK and India. Findings: A total of 40,334 people were included in the model development phase of which 1427 (3·54%) people developed STDR. Age, gender, diabetes duration, antidiabetic medication history, glycated haemoglobin (HbA1c), and history of retinopathy were included as predictors in the Model 1, Model 2 excluded retinopathy status, and Model 3 further excluded HbA1c. All three models attained strong discrimination performance in the model development dataset with C statistics ranging from 0·778 to 0·832, and in the external validation datasets (C statistic 0·685 – 0·823) with calibration slopes closer to 1 following re-calibration of the baseline survival. Interpretation: We have developed new risk prediction equations to identify those at risk of STDR in people with type 2 diabetes in any resource-setting so that they can be screened and treated early. Future testing, and piloting is required before implementation. Funding: This study was funded by the GCRF UKRI (MR/P207881/1) and supported by the NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology.

BackgroundIn September 2014, as part of a national initiative to increase access to liaison psychiatry services, the liaison psychiatry services at Bristol Royal Infirmary received new investment of £250 000 per annum, expanding its availability from 40 to 98 h per week. The long-term impact on patient outcomes and costs, of patients presenting to the emergency department with self-harm, is unknown.AimsTo assess the long-term impact of the investment on patient care outcomes and costs, of patients presenting to the emergency department with self-harm.MethodMonthly data for all self-harm emergency department attendances between 1 September 2011 and 30 September 2017 was modelled using Bayesian structural time series to estimate expected outcomes in the absence of expanded operating hours (the counterfactual). The difference between the observed and expected trends for each outcome were interpreted as the effects of the investment.ResultsOver the 3 years after service expansion, the mean number of self-harm attendances increased 13%. Median waiting time from arrival to psychosocial assessment was 2 h shorter (18.6% decrease, 95% Bayesian credible interval (BCI) −30.2% to −2.8%), there were 45 more referrals to other agencies (86.1% increase, 95% BCI 60.6% to 110.9%) and a small increase in the number of psychosocial assessments (11.7% increase, 95% BCI −3.4% to 28.5%) per month. Monthly mean net hospital costs were £34 more per episode (5.3% increase, 95% BCI −11.6% to 25.5%).ConclusionsDespite annual increases in emergency department attendances, investment was associated with reduced waiting times for psychosocial assessment and more referrals to other agencies, with only a small increase in cost per episode.

Abstract Background Findings from studies assessing Long Covid in children and young people (CYP) need to be assessed in light of their methodological limitations. For example, if non-response and/or attrition over time systematically differ by sub-groups of CYP, findings could be biased and any generalisation limited. The present study aimed to (i) construct survey weights for the Children and young people with Long Covid (CLoCk) study, and (ii) apply them to published CLoCk findings showing the prevalence of shortness of breath and tiredness increased over time from baseline to 12-months post-baseline in both SARS-CoV-2 Positive and Negative CYP. Methods Logistic regression models were fitted to compute the probability of (i) Responding given envisioned to take part, (ii) Responding timely given responded, and (iii) (Re)infection given timely response. Response, timely response and (re)infection weights were generated as the reciprocal of the corresponding probability, with an overall ‘envisioned population’ survey weight derived as the product of these weights. Survey weights were trimmed, and an interactive tool developed to re-calibrate target population survey weights to the general population using data from the 2021 UK Census. Results Flexible survey weights for the CLoCk study were successfully developed. In the illustrative example, re-weighted results (when accounting for selection in response, attrition, and (re)infection) were consistent with published findings. Conclusions Flexible survey weights to address potential bias and selection issues were created for and used in the CLoCk study. Previously reported prospective findings from CLoCk are generalisable to the wider population of CYP in England. This study highlights the importance of considering selection into a sample and attrition over time when considering generalisability of findings.

Introduction Diabetes is a major global public health burden. The objective of this study was to estimate the national and provincial-level prevalence of self-reported diabetes and establish the demographic risk factors of diabetes in Sri Lanka.Research design and methods A nationally representative sample of the population from all nine provinces in Sri Lanka was obtained from the cross-sectional Demographic and Health Survey 2016. Those aged 20 years and older were included in this study. Age, sex, ethnicity, religion, education level, marital status, sector of the resident (urban/rural/estate) and province of residence were included as potential exposures. The outcome was defined as self-reported diabetes.Results The age-adjusted national prevalence of self-reported diabetes was 10.60% (95% CI: 10.59% to 10.602%). Provinces with higher gross domestic product (GDP) per capita showed a higher prevalence of diabetes. The Western province with the highest GDP of 734 094 Sri Lankan rupee showed the highest prevalence of diabetes (13.3%; 95% CI: 13.32% to 13.34%) compared with 8.1% (95% CI: 8.54% to 8.58%) in the Northern province with lowest GDP (321 289 Sri Lankan rupee). Prevalence of diabetes was higher among residents living in urban areas (14.39%; 95% CI: 13.72% to 15.06%) compared with their counterpart. Other risk factors of self-reported diabetes included age, gender, ethnicity, education level and marital status with those aged 55–64 years, females, who belong to Moor ethnicity, had secondary or higher education, and divorced or widowed had higher risk of diabetes compared with their counterparts.Conclusions Sri Lanka has a high prevalence of self-reported diabetes and it differs by province, sector of residence, sex, education level, ethnicity, age and marital status. There is a need for risk stratifying adult Sri Lankan population to help target those at high risk of diabetes so that cost-effective approaches of screening, preventive and treatment options can be initiated.