Long COVID and the mental and physical health of children and young people: national matched cohort study protocol (the CLoCk study).

Abstract

INTRODUCTION: There is uncertainty surrounding the diagnosis, prevalence, phenotype, duration and treatment of Long COVID. This study aims to (A) describe the clinical phenotype of post-COVID symptomatology in children and young people (CYP) with laboratory-confirmed SARS-CoV-2 infection compared with test-negative controls, (B) produce an operational definition of Long COVID in CYP, and (C) establish its prevalence in CYP. METHODS AND ANALYSIS: A cohort study of SARS-CoV-2-positive CYP aged 11-17 years compared with age, sex and geographically matched SARS-CoV-2 test-negative CYP. CYP aged 11-17 testing positive and negative for SARS-CoV-2 infection will be identified and contacted 3, 6, 12 and 24 months after the test date. Consenting CYP will complete an online questionnaire. We initially planned to recruit 3000 test positives and 3000 test negatives but have since extended our target. Data visualisation techniques will be used to examine trajectories over time for symptoms and variables measured repeatedly, separately by original test status. Summary measures of fatigue and mental health dimensions will be generated using dimension reduction methods such as latent variables/latent class/principal component analysis methods. Cross-tabulation of collected and derived variables against test status and discriminant analysis will help operationalise preliminary definitions of Long COVID. ETHICS AND DISSEMINATION: Research Ethics Committee approval granted. Data will be stored in secure Public Health England servers or University College London's Data Safe Haven. Risks of harm will be minimised by providing information on where to seek support. Results will be published on a preprint server followed by journal publication, with reuse of articles under a CC BY licence. Data will be published with protection against identification when there are small frequencies involved. TRIAL REGISTRATION NUMBER: ISRCTN34804192; Pre-results.