Developing survey weights to ensure representativeness in a national, matched cohort study: results from the Children and young people with Long Covid (CLoCk) study. (preprint)

Background: Findings from studies assessing Long Covid in children and young people (CYP) need to be viewed 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 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 was used 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.

Developing a model for predicting impairing physical symptoms in children 3 months after a SARS-CoV-2 PCR-test: The CLoCk Study (preprint)

Abstract Importance: Predictive models can help identify SARS-CoV-2 patients at greatest risk of post-COVID sequelae and direct them towards appropriate care. Objective: To develop and internally validate a model to predict children and young people most likely to experience at least one impairing physical symptom 3 months after a SARS-CoV-2 PCR-test and to determine whether the impact of these predictors differed by SARS-CoV-2 infection status. Design: Potential pre-specified predictors included: SARS-CoV-2 status, sex, age, ethnicity, deprivation, quality of life/functioning (5 EQ-5D-Y items), physical and mental health, and loneliness (all prior to SARS-CoV-2 testing), and number of physical symptoms at testing. Logistic regression was used to develop the model. Model performance was assessed using calibration and discrimination measures; internal validation was performed via bootstrapping; the final model was adjusted for overfitting. Setting: National cohort study of SARS-CoV-2 PCR-positive and PCR-negative participants matched according to age, sex, and geographical area. Participants: Children and young people aged 11-17 years who were tested for SARS-CoV-2 infection in England, January to March 2021. Main outcome measure: one or more physical symptom 3 months after initial PCR-testing which affected physical, mental or social well-being and interfered with daily living. Results: A total of 50,836 children and young people were approached; 7,096 (3,227 test-positives, 3,869 test-negatives) who completed a questionnaire 3 months after their PCR-test were included. 39.6% (1,279/3,227) of SAR-CoV-2 PCR-positives and 30.6% (1,184/3,869) of SAR-CoV-2 PCR-negatives had at least one impairing physical symptom 3 months post-test. The final model contained predictors: SARS-COV-2 status, number of symptoms at testing, sex, age, ethnicity, self-rated physical and mental health, feelings of loneliness and four EQ-5D-Y items before testing. Internal validation showed minimal overfitting with excellent calibration and discrimination measures (optimism adjusted calibration slope:0.97527; C-statistic:0.83640). Conclusions and relevance: We developed a risk prediction equation to identify those most at risk of experiencing at least one impairing physical symptom 3 months after a SARS-CoV-2 PCR-test which could serve as a useful triage and management tool for children and young people during the ongoing pandemic. External validation is required before large-scale implementation.