Journal article
Guillain-Barré syndrome following SARS-CoV-2 vaccination in the UK: a prospective surveillance study
- Abstract:
- The acquired inflammatory neuropathies are remarkable for the potential to significantly reverse disability and prevent death because of a high degree of treatment responsiveness. This response is dependent on prompt and accurate diagnosis and careful monitoring to optimise outcome. A major challenge is the scarcity of tools, or biomarkers, to enable precise and timely diagnosis, gauge disease severity or reflect treatment response. This heterogeneous collection of nerve conditions includes individual disease entities which are very rare in the general population, and even disease-specific and highly sensitive biomarkers have a high false positive rate when applied to an unselected cohort. This highlights the importance of high quality diagnostics in the utility of other biomarker development. In this thesis I explore and develop novel biomarkers and assess and optimise interpretation of established clinical and serological biomarkers across the spectrum of acquired inflammatory neuropathies including Guillain-Barré syndrome, chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), multifocal motor neuropathy with conduction block (MMNCB) and POEMS (Polyneuropathy, Organomegaly, Endocrinopathy, Monoclonal protein and Skin changes syndrome). Infection and vaccination are established risk factors for some inflammatory neuropathies. The COVID-19 pandemic and global vaccination programmes present ubiquitous, novel potential inflammatory neuropathy risk factors. Rapid quantification of this unknown risk has immediate and universal relevance for public health services worldwide and is essential to clinical diagnostics at the bedside. Serological and imaging biomarkers are widely used to diagnose and monitor neurological diseases of the central nervous system, but very few are available for use by the peripheral nerve clinician to manage individuals with inflammatory neuropathies. Clinical outcome measures, including disability scales and impairment measures, are widely used measures of disease activity and treatment response in chronic inflammatory neuropathies. However, small variations occur between assessments, making it difficult to ascertain what constitutes meaningful change. This thesis aims to target the unmet needs in the diagnosis and management of the inflammatory neuropathies, using a range of existing and novel biomarkers to improve clinical care, and identifying emerging and latent risk factors modifying the pre-test likelihood of developing these conditions. A variety of research methods are used in this thesis to accomplish this, including epidemiological studies, serological biomarkers, imaging, and statistical methods such as latent class mixture modelling and Rasch analysis. Each chapter discusses a unique approach, intended to fill a knowledge gap in current neuropathy care. Methodology for each individual approach is discussed within the relevant chapter
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 719.1KB, Terms of use)
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- Publisher copy:
- 10.1136/bmjno-2022-000309
- Publication website:
- https://discovery.ucl.ac.uk/10203816/7/Keh_10203816_Thesis_sigs_removed.pdf
Authors
+ Medical Research Council
More from this funder
- Funder identifier:
- 10.13039/501100000265
- Grant:
- MR/V03 (UK MRC's Global Effort on COVID-19)
+ National Institute for Health Research
More from this funder
- Funder identifier:
- 10.13039/501100000272
- Grant:
- ACF-2020-07-003
- Publisher:
- BMJ Publishing Group
- Journal:
- BMJ Neurology Open More from this journal
- Volume:
- 4
- Issue:
- 2
- Pages:
- e000309-e000309
- Publication date:
- 2022-07-12
- Acceptance date:
- 2022-05-13
- DOI:
- EISSN:
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2632-6140
- ISSN:
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2632-6140
- Language:
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English
- Keywords:
- Pubs id:
-
1269643
- Local pid:
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pubs:1269643
- Source identifiers:
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W4285097340
- Deposit date:
-
2026-04-27
- ARK identifier:
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Terms of use
- Copyright date:
- 2022
- Licence:
- CC Attribution (CC BY)
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