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IntroductionIndividuals with COVID-19 frequently experience symptoms and impaired quality of life beyond 4–12 weeks, commonly referred to as Long COVID. Whether Long COVID is one or several distinct syndromes is unknown. Establishing the evidence base for appropriate therapies is needed. We aim to evaluate the symptom burden and underlying pathophysiology of Long COVID syndromes in non-hospitalised individuals and evaluate potential therapies.Methods and analysisA cohort of 4000 non-hospitalised individuals with a past COVID-19 diagnosis and 1000 matched controls will be selected from anonymised primary care records from the Clinical Practice Research Datalink, and invited by their general practitioners to participate on a digital platform (Atom5). Individuals will report symptoms, quality of life, work capability and patient-reported outcome measures. Data will be collected monthly for 1 year.Statistical clustering methods will be used to identify distinct Long COVID-19 symptom clusters. Individuals from the four most prevalent clusters and two control groups will be invited to participate in the BioWear substudy which will further phenotype Long COVID symptom clusters by measurement of immunological parameters and actigraphy.We will review existing evidence on interventions for postviral syndromes and Long COVID to map and prioritise interventions for each newly characterised Long COVID syndrome. Recommendations will be made using the cumulative evidence in an expert consensus workshop. A virtual supportive intervention will be coproduced with patients and health service providers for future evaluation.Individuals with lived experience of Long COVID will be involved throughout this programme through a patient and public involvement group.Ethics and disseminationEthical approval was obtained from the Solihull Research Ethics Committee, West Midlands (21/WM/0203). Research findings will be presented at international conferences, in peer-reviewed journals, to Long COVID patient support groups and to policymakers.Trial registration number1567490.

IntroductionIndividuals with COVID-19 frequently experience symptoms and impaired quality of life beyond 4-12 weeks, commonly referred to as Long COVID. Whether Long COVID is one or several distinct syndromes is unknown. Establishing the evidence base for appropriate therapies is needed. We aim to evaluate the symptom burden and underlying pathophysiology of Long COVID syndromes in non-hospitalised individuals and evaluate potential therapies.Methods and analysisA cohort of 4000 non-hospitalised individuals with a past COVID-19 diagnosis and 1000 matched controls will be selected from anonymised primary care records from the Clinical Practice Research Datalink (CPRD) and invited by their general practitioners to participate on a digital platform (Atom5™). Individuals will report symptoms, quality of life, work capability, and patient reported outcome measures. Data will be collected monthly for one year.Statistical clustering methods will be used to identify distinct Long COVID symptom clusters. Individuals from the four most prevalent clusters and two control groups will be invited to participate in the BioWear sub-study which will further phenotype Long COVID symptom clusters by measurement of immunological parameters and actigraphy.We will review existing evidence on interventions for post-viral syndromes and Long COVID to map and prioritise interventions for each newly characterised Long COVID syndrome. Recommendations will be made using the cumulated evidence in an expert consensus workshop. A virtual supportive intervention will be coproduced with patients and health service providers for future evaluation.Individuals with lived experience of Long COVID will be involved throughout this programme through a patient and public involvement group.Ethics and disseminationEthical approval was obtained from the Solihull Research Ethics Committee, West Midlands (21/WM/0203). The study is registered on the ISRCTN Registry (1567490). Research findings will be presented at international conferences, in peer-reviewed journals, to Long COVID patient support groups and to policymakers.Article SummaryStrengths and limitations of the studyThe study will generate a nationally representative cohort of individuals with Long COVID recruited from primary care.We will recruit controls matched on a wide range of demographic and clinical factors to assess differences in symptoms between people with Long COVID and similar individuals without a history of COVID-19.We will use a newly developed electronic patient reported outcome measure (Symptom Burden Questionnaire™) for Long COVID to comprehensively assess a wide range of symptoms highlighted by existing literature, patients, and clinicians.Immunological, proteomic, genetic, and wearable data captured in the study will allow deep phenotyping of Long COVID syndromes to help better target therapies.A limitation is that a significant proportion of non-hospitalised individuals affected by COVID-19 in the first wave of the pandemic will lack confirmatory testing and will be excluded from recruitment to the study.

BackgroundThere has been increasing public concern that COVID-19 vaccines cause menstrual cycle disturbances, yet there is currently limited data to evaluate the impact of vaccination on menstrual health. Our objectives were (1) to evaluate the prevalence of menstrual changes following vaccination against COVID-19, (2) to test potential risk factors for any such changes, and (3) to identify patterns of symptoms in participants’ written accounts.MethodsWe performed a secondary analysis of a retrospective online survey titled “The Covid-19 Pandemic and Women’s Reproductive Health”, conducted in March 2021 in the UK before widespread media attention regarding potential impacts of SARS-CoV-2 vaccination on menstruation. Participants were recruited via a Facebook ad campaign in the UK and eligibility criteria for survey completion were age greater than 18 years, having ever menstruated and currently living in the UK. In total, 26,710 people gave consent and completed the survey. For this analysis we selected 4,989 participants who were pre-menopausal and vaccinated. These participants were aged 28 to 43, predominantly from England (81%), of white background (95%) and not using hormonal contraception (58%).FindingsAmong pre-menopausal vaccinated individuals (n=4,989), 80% did not report any menstrual cycle changes up to 4 months after their first COVID-19 vaccine injection. Current use of combined oral contraceptives was associated with lower odds of reporting any changes by 48% (OR = 0.52, 95CI = [0.34 to 0.78], PPPPConclusionsFollowing vaccination for COVID-19, menstrual disturbance occurred in 20% of individuals in a UK sample. Out of 33 variables investigated, smoking and a previous history of SARS-CoV-2 infection were found to be risk factors while using oestradiol-containing contraceptives was found to be a protective factor. Diverse experiences were reported, from menstrual bleeding cessation to heavy menstrual bleeding.