Transient ischaemic attack (TIA) and ischaemic stroke is a heterogeneous disease with more than 150 known causes including different cardiac, arterial, hemodynamic and other systemic abnormalities. TIA and ischaemic stroke of different aetiology have been suggested to have different risk factor profiles, clinical manifestations and prognoses. Therefore categorization of patients into classes congruent with the aetiology is the key to both understanding and managing stroke. Such categorization requires assembling stroke features to create categories based on similarities and is known as aetiological classification. Accurate aetiological classification is indispensable in epidemiological and genetic studies and in clinical trials. However, all current stroke classification systems have limitations. Perhaps the most important limitation of all current stroke classification systems is that about one-third of TIA and ischaemic stroke are of undetermined aetiology despite standard diagnostic work-up, potentially undermining primary and secondary stroke prevention. Therefore, better understanding of stroke aetiology will help to improve the classification of TIA and ischaemic stroke hence ultimately improving the prevention strategy. The aim of my thesis has been to compare characteristics of currently used aetiological classification systems, to explore the underlying causes for TIA and ischaemic stroke of undetermined aetiology, and to study aetiological classification related aspects of TIA and ischaemic stroke, including risk factors, imaging characteristics, plasma biomarkers and prognoses. I have collected, collated and analysed data from the first ten years of the Oxford Vascular study (OXVASC), which is an ongoing prospective, population-based incidence study of vascular disease in all territories in Oxfordshire, UK. The study population comprises approximately 92,728 individuals registered with nine general practices and uses multiple overlapping “hot” and “cold” methods to identify all patients with acute vascular events. There are several clinically relevant findings in this thesis which address areas that could be improved for better aetiological classification of TIA and ischaemic stroke. First, I have validated the aetiological classification of TIA. Second, I have found that compared to the widely used TOAST aetiological classification system, the stringent requirements for adequate investigation in recently developed classification systems do not add subtype-specific information to reliably reduce the assignment to the undetermined subtype. Third, I have shown that neither occult atheroma nor traditional risk factors appear to account for undetermined TIA and ischaemic stroke. However, previous migraine may have a particular role in the aetiology of undetermined TIA and ischaemic stroke. Fourth, I have shown that compared to cases of non-small vessel disease, small vessel disease cases have higher long-term average systolic and diastolic blood pressure but less long-term blood pressure variability. Fifth, I have shown that in contrast to cases of small vessel disease, white matter changes on brain imaging are not independently associated with non-small vessel subtypes. Sixth, I have shown that applying haemostatic and inflammatory markers in stroke aetiological work-up would appear to have little potential to add very limited information regarding the specific underlying cause of different aetiological subtypes. Finally, I have highlighted the large clinical burden of TIA and ischaemic stroke of undetermined aetiology by showing that compared to cases of determined aetiology, undetermined TIA and ischaemic stroke appears to have non-benign short- and long-term prognoses.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:635300 |
| Date | January 2014 |
| Creators | Li, Linxin |
| Contributors | Rothwell, Peter |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:ac676d1b-a9a6-4ef8-93d2-28eb696cc36d |
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