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Completed RESEARCH NIHR Open Data-Funded Portfolio

Characterisation, determinants, mechanisms and consequences of the long-term effects of COVID-19: providing the evidence base for health care services

£95.93M GBP

Funder National Institute for Health and Care Research
Recipient Organization University College London
Country United Kingdom
Start Date Mar 01, 2021
End Date Nov 30, 2025
Duration 1,735 days
Number of Grantees 2
Roles Principal Investigator; Award Holder
Data Source NIHR Open Data-Funded Portfolio
Grant ID COV-LT-0009
Grant Description

Long-term health consequences of C-19 (long-COVID) occur frequently.

Most infections are not hospitalised; population studies are the place to understand individual and societal challenges of long-COVID. We will address the following questions: How do we define and diagnose the sub-phenotypes of long-COVID? What are the predictors of long-COVID, and what are the mechanisms of the sub-phenotypes?

What are the long-term health (physical and mental), and socioeconomic consequences? What factors enhance recovery? What is the level of GP adherence to NICE diagnosis and management guidelines? Can a pop-up tool in medical records enhance adherence?

We have an established consortium of experts and platforms uniting linked national primary care registries and population cohorts.

The national coverage of primary care registries captures all individuals presenting to their GP, with linked prescribing, consulting, referral and outcome data. Many with long-COVID do not seek care. Population cohorts, with repeat C-19 related questionnaires, overcome this limitation.

Further, the standardised pre-pandemic health data enables dissection of the effects of infection versus progression of co-morbidity. Questionnaires will identify long-COVID cases across cohorts.

A subgroup of 200 cases will be matched to three sets of controls (C-19 +, long-COVID-), (C-19-, long-COVID+), and (C-19-, long-COVID-).

They will wear a device capturing exercise capacity, heart rate and respiration, and complete regular online questionnaires on mental health and cognition. They will attend clinic for imaging to assess target organ damage. Qualitative work with people with long-COVID will inform diagnostic criteria and understanding of the lived experience.

Parallel analysis of cohorts and registries will address each question.

With NICE, we will quantify adherence to diagnostic and management guidelines in GP records, and pilot a pop-up intervention to enhance adherence.

Our findings will enhance diagnostic criteria, identify pathways for bespoke sub-phenotype intervention, and inform plans for health service delivery.

All Grantees

University College London

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