We live in an ageing society. Stroke is the leading cause of complex disability in the UK, where it affects one in five men and one in six women by the age of 75. Problems with memory, learning and understanding contribute substantially to the disability experienced after stroke and are a major concern for patients and families. Patterns of these cognitive changes vary markedly between individuals and it is not clear why particular groups of patients develop dementia after stroke. One hypothesis is that other illnesses such as infections might play an important role, perhaps by causing inflammation in the nervous system. In this study, we aim to explore whether adult stroke survivors who experience serious infections such as pneumonia, urine and skin infections requiring antibiotic treatment are more likely to develop dementia than stroke survivors without these infections. To do this, we will use anonymised electronic health records from primary care linked to hospital records to compare dementia rates between different groups of individuals after stroke; those with and without common serious infections. Improved understanding of the effect of infections on dementia risk after stroke will help healthcare professionals to prevent and treat infections early to preserve cognitive function after stroke.
Cognitive problems contribute substantially to the disability experienced after stroke and result in a major health and societal burden. Both short- and long-term cognitive changes occur after stroke, but reasons for the development of post-stroke dementia remain unclear. Infections are hypothesised to play a role, perhaps acting through systemic inflammatory pathways that trigger a disordered microglial response in the aged brain. Here we aim to investigate the association between common serious infections and incident dementia in a population cohort of adult stroke survivors using electronic health records (EHR). Using routinely collected EHR data will increase power and generalisability of findings as well as overcoming some methodological difficulties that may hamper traditional cohort studies of post-stroke dementia such as ascertainment bias. We will carry out a multivariable Cox regression analysis to compare incidence rates of post-stroke dementia among stroke survivors exposed and unexposed to infections in time periods after stroke, controlling for potential socio-demographic and clinical confounding factors. In secondary analyses, we will investigate the effect of site, frequency, severity and timing of infections on dementia outcomes. Better understanding of these relationships will help to inform the development and targeting of interventions to prevent and treat infections after stroke and thereby preserve cognitive function.
Early post-stroke dementia (3 months to 1 year); Later post-stroke dementia (1 to 5 years).
Charlotte Warren-Gash - Chief Investigator - London School of Hygiene & Tropical Medicine ( LSHTM )
Charlotte Warren-Gash - Corresponding Applicant - London School of Hygiene & Tropical Medicine ( LSHTM )
Caroline Morton - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Harriet Forbes - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Liam Smeeth - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Neil Pearce - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
HES Admitted Patient Care;Practice Level Index of Multiple Deprivation