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    Modulation of Inflammation in Intracerebral Haemorrhage

    Abid, Kamran

    [Thesis]. Manchester, UK: The University of Manchester; 2015.

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    Abstract

    Intracerebral Haemorrhage (ICH) exhibits the worst mortality and morbidity of any stroke subtype. There are no efficacious treatments for this condition and little improvement in patient outcome has been noted despite advancements in medical science over the previous three decades. Furthermore, current available data is increasingly obsolete as the population suffering the disease burden rapidly ages and develops co-morbidities. It is thought that future therapies for this condition may be able to target neuroinflammatory response triggered by the formation of brain haemorrhage however there is little published evidence that has examined this aspect of ICH pathophysiology.This study therefore examines the current prognosis of a large cohort of patients with ICH to determine the key factors which result in mortality. We find that patients treated at a specialist centre have a surprising and significantly improved survival advantage. Since clinical practice in the United Kindgom is widely influential, the second part of the study focuses on whether the optimal cases are currently being transferred to these centres. The next part of the study then uses MRI/PET brain imaging for the first time in patients with ICH to establish an important link between the processes of neuroinflammation and Blood-Brain-Barrier breakdown. Finally, the concluding part of the thesis presents functional and radiological data from a rat model of ICH in which the inflammatory cascade has been modulated by the use of an antagonist against IL-1. The thesis thus presents a novel and important contribution in our present understanding of the preclinical and clinical disease process.

    Bibliographic metadata

    Type of resource:
    Content type:
    Form of thesis:
    Type of submission:
    Degree type:
    Doctor of Philosophy
    Degree programme:
    PhD Neuroscience
    Publication date:
    Location:
    Manchester, UK
    Total pages:
    173
    Abstract:
    Intracerebral Haemorrhage (ICH) exhibits the worst mortality and morbidity of any stroke subtype. There are no efficacious treatments for this condition and little improvement in patient outcome has been noted despite advancements in medical science over the previous three decades. Furthermore, current available data is increasingly obsolete as the population suffering the disease burden rapidly ages and develops co-morbidities. It is thought that future therapies for this condition may be able to target neuroinflammatory response triggered by the formation of brain haemorrhage however there is little published evidence that has examined this aspect of ICH pathophysiology.This study therefore examines the current prognosis of a large cohort of patients with ICH to determine the key factors which result in mortality. We find that patients treated at a specialist centre have a surprising and significantly improved survival advantage. Since clinical practice in the United Kindgom is widely influential, the second part of the study focuses on whether the optimal cases are currently being transferred to these centres. The next part of the study then uses MRI/PET brain imaging for the first time in patients with ICH to establish an important link between the processes of neuroinflammation and Blood-Brain-Barrier breakdown. Finally, the concluding part of the thesis presents functional and radiological data from a rat model of ICH in which the inflammatory cascade has been modulated by the use of an antagonist against IL-1. The thesis thus presents a novel and important contribution in our present understanding of the preclinical and clinical disease process.
    Thesis main supervisor(s):
    Thesis co-supervisor(s):
    Language:
    en

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    University researcher(s):
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    Record metadata

    Manchester eScholar ID:
    uk-ac-man-scw:263939
    Created by:
    Abid, Kamran
    Created:
    6th May, 2015, 11:41:19
    Last modified by:
    Abid, Kamran
    Last modified:
    16th November, 2017, 12:37:47

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