Predictive model for long COVID in children 3 months after a SARS-CoV-2 PCR test.

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.

Physical and mental health 3 months after SARS-CoV-2 infection (long COVID) among adolescents in England (CLoCk): a national matched cohort study.

BACKGROUND: We describe post-COVID symptomatology in a non-hospitalised, national sample of adolescents aged 11-17 years with PCR-confirmed SARS-CoV-2 infection compared with matched adolescents with negative PCR status. METHODS: In this national cohort study, adolescents aged 11-17 years from the Public Health England database who tested positive for SARS-CoV-2 between January and March, 2021, were matched by month of test, age, sex, and geographical region to adolescents who tested negative. 3 months after testing, a subsample of adolescents were contacted to complete a detailed questionnaire, which collected data on demographics and their physical and mental health at the time of PCR testing (retrospectively) and at the time of completing the questionnaire (prospectively). We compared symptoms between the test-postive and test-negative groups, and used latent class analysis to assess whether and how physical symptoms at baseline and at 3 months clustered among participants. This study is registered with the ISRCTN registry (ISRCTN 34804192). FINDINGS: 23 048 adolescents who tested positive and 27 798 adolescents who tested negative between Jan 1, 2021, and March 31, 2021, were contacted, and 6804 adolescents (3065 who tested positive and 3739 who tested negative) completed the questionnaire (response rate 13·4%). At PCR testing, 1084 (35·4%) who tested positive and 309 (8·3%) who tested negative were symptomatic and 936 (30·5%) from the test-positive group and 231 (6·2%) from the test-negative group had three or more symptoms. 3 months after testing, 2038 (66·5%) who tested positive and 1993 (53·3%) who tested negative had any symptoms, and 928 (30·3%) from the test-positive group and 603 (16·2%) from the test-negative group had three or more symptoms. At 3 months after testing, the most common symptoms among the test-positive group were tiredness (1196 [39·0%]), headache (710 [23·2%]), and shortness of breath (717 [23·4%]), and among the test-negative group were tiredness (911 [24·4%]), headache (530 [14·2%]), and other (unspecified; 590 [15·8%]). Latent class analysis identified two classes, characterised by few or multiple symptoms. The estimated probability of being in the multiple symptom class was 29·6% (95% CI 27·4-31·7) for the test-positive group and 19·3% (17·7-21·0) for the test-negative group (risk ratio 1·53; 95% CI 1·35-1·70). The multiple symptoms class was more frequent among those with positive PCR results than negative results, in girls than boys, in adolescents aged 15-17 years than those aged 11-14 years, and in those with lower pretest physical and mental health. INTERPRETATION: Adolescents who tested positive for SARS-CoV-2 had similar symptoms to those who tested negative, but had a higher prevalence of single and, particularly, multiple symptoms at the time of PCR testing and 3 months later. Clinicians should consider multiple symptoms that affect functioning and recognise different clusters of symptoms. The multiple and varied symptoms show that a multicomponent intervention will be required, and that mental and physical health symptoms occur concurrently, reflecting their close relationship. FUNDING: UK Department of Health and Social Care, in their capacity as the National Institute for Health Research, and UK Research and Innovation.

Factors associated with excess all-cause mortality in the first wave of the COVID-19 pandemic in the UK: A time series analysis using the Clinical Practice Research Datalink.

BACKGROUND: Excess mortality captures the total effect of the Coronavirus Disease 2019 (COVID-19) pandemic on mortality and is not affected by misspecification of cause of death. We aimed to describe how health and demographic factors were associated with excess mortality during, compared to before, the pandemic. METHODS AND FINDINGS: We analysed a time series dataset including 9,635,613 adults (≥40 years old) registered at United Kingdom general practices contributing to the Clinical Practice Research Datalink. We extracted weekly numbers of deaths and numbers at risk between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during Wave 1 of the UK pandemic (5 March to 27 May 2020) compared to the prepandemic period was estimated using seasonally adjusted negative binomial regression models. Relative rates (RRs) of death for a range of factors were estimated before and during Wave 1 by including interaction terms. We found that all-cause mortality increased by 43% (95% CI 40% to 47%) during Wave 1 compared with prepandemic. Changes to the RR of death associated with most sociodemographic and clinical characteristics were small during Wave 1 compared with prepandemic. However, the mortality RR associated with dementia markedly increased (RR for dementia versus no dementia prepandemic: 3.5, 95% CI 3.4 to 3.5; RR during Wave 1: 5.1, 4.9 to 5.3); a similar pattern was seen for learning disabilities (RR prepandemic: 3.6, 3.4 to 3.5; during Wave 1: 4.8, 4.4 to 5.3), for black or South Asian ethnicity compared to white, and for London compared to other regions. Relative risks for morbidities were stable in multiple sensitivity analyses. However, a limitation of the study is that we cannot assume that the risks observed during Wave 1 would apply to other waves due to changes in population behaviour, virus transmission, and risk perception. CONCLUSIONS: The first wave of the UK COVID-19 pandemic appeared to amplify baseline mortality risk to approximately the same relative degree for most population subgroups. However, disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.