{"id":{"repo_id":"edinburgh","oai_identifier":"oai:era.ed.ac.uk:1842/44811"},"canonical_url":"https://search.dev.ndltd.org/etd/edinburgh/oai:era.ed.ac.uk:1842/44811","repository":{"repo_id":"edinburgh","name":"University of Edinburgh","base_url":"https://era.ed.ac.uk/server/oai/request"},"display":{"title":"Vascular contributors to cognitive impairment and dementia: insights from existing data","abstract":"Cognitive impairment and dementia pose a significant and growing public health challenge, yet progress in developing effective interventions to prevent dementia or slow cognitive decline has been limited. Among potential targets, vascular risk factors have emerged as particularly promising. Given the prolonged preclinical phase of dementia and its gradual progression, longitudinal studies are essential not only to track disease trajectories over time but also to identify individuals at risk as early as possible for potential recruitment into future interventions. Despite their importance, long-term follow-up in cohort studies faces significant challenges, including high costs and participant attrition. One promising solution is the use of existing data sources from cohort studies, clinical trial datasets, and routinely collected health records, which provide a cost-effective and efficient means of studying vascular contributions to cognitive dysfunction. In this thesis, I demonstrate how leveraging data from completed clinical trials and routinely collected health records can yield valuable insights into vascular contributors to cognitive impairment and dementia, as well as improve understanding of prognosis in individuals with a vascular component to their dementia. Chapter one introduces the core concepts of this thesis, providing the background and rationale for the five research studies within. Chapter two describes the datasets used: the COGWHEEL dataset, consisting of seven clinical trials of vascular intervention, and the WARBLER and DISCOVER datasets, both derived from Scottish routine clinical health records. This chapter also outlines the advantages and limitations of utilising such existing data sources. Chapters three and four examine the impact of cerebrovascular disease on cognition. First, I investigate the relationship between symptomatic cerebrovascular disease and cognition and find that stroke is associated with around 18 years of cognitive ageing, while transient ischaemic attack is associated with 3 years of ageing. I then turn to asymptomatic cerebrovascular disease, finding that individuals with small vessel disease or ‘silent’ stroke have a 55% increased risk of developing dementia compared to those without covert cerebrovascular disease. Chapters five and six explore the role of cardiovascular risk factors in cognitive dysfunction using clinical trial data. Chapter five examines the association between fasting plasma glucose levels and cognitive impairment, revealing a U-shaped association with small effect sizes. Chapter six expands on this by investigating the impact of visit-to-visit variability in glucose levels and additional parameters - blood pressure, heart rate, cholesterol, triglycerides, and weight - on cognitive performance. I find that greater variability in these measures is associated with poorer cognitive performance, with evidence of a cumulative effect, where individuals with more instances of high variability exhibit worse cognition. However, the effect sizes are weak and unlikely to have clinical utility. In chapter seven, I use health records to investigate the prognosis of people who have a vascular component to their dementia. I build upon the findings of the four preceding studies - which aimed to identify clinically meaningful vascular contributors - and define vascular contribution to dementia using three different methods: (1) clinically defined using ICD-10 codes for vascular dementia; (2) defined by the presence of overt or covert cerebrovascular disease on brain scan reports; and (3) defined by the presence of an ICD-10 code for prior stroke or TIA. Results indicate that individuals with a vascular contribution to dementia have a higher risk of death, stroke, epilepsy, fractures, and hospitalisation compared to those without vascular contributors. Finally, chapter eight summarises the key findings, discusses their broader implications, and outlines potential directions for future research.","abstract_html":"Cognitive impairment and dementia pose a significant and growing public health challenge, yet progress in developing effective interventions to prevent dementia or slow cognitive decline has been limited. Among potential targets, vascular risk factors have emerged as particularly promising. Given the prolonged preclinical phase of dementia and its gradual progression, longitudinal studies are essential not only to track disease trajectories over time but also to identify individuals at risk as early as possible for potential recruitment into future interventions. Despite their importance, long-term follow-up in cohort studies faces significant challenges, including high costs and participant attrition. One promising solution is the use of existing data sources from cohort studies, clinical trial datasets, and routinely collected health records, which provide a cost-effective and efficient means of studying vascular contributions to cognitive dysfunction. In this thesis, I demonstrate how leveraging data from completed clinical trials and routinely collected health records can yield valuable insights into vascular contributors to cognitive impairment and dementia, as well as improve understanding of prognosis in individuals with a vascular component to their dementia. Chapter one introduces the core concepts of this thesis, providing the background and rationale for the five research studies within. Chapter two describes the datasets used: the COGWHEEL dataset, consisting of seven clinical trials of vascular intervention, and the WARBLER and DISCOVER datasets, both derived from Scottish routine clinical health records. This chapter also outlines the advantages and limitations of utilising such existing data sources. Chapters three and four examine the impact of cerebrovascular disease on cognition. First, I investigate the relationship between symptomatic cerebrovascular disease and cognition and find that stroke is associated with around 18 years of cognitive ageing, while transient ischaemic attack is associated with 3 years of ageing. I then turn to asymptomatic cerebrovascular disease, finding that individuals with small vessel disease or ‘silent’ stroke have a 55% increased risk of developing dementia compared to those without covert cerebrovascular disease. Chapters five and six explore the role of cardiovascular risk factors in cognitive dysfunction using clinical trial data. Chapter five examines the association between fasting plasma glucose levels and cognitive impairment, revealing a U-shaped association with small effect sizes. Chapter six expands on this by investigating the impact of visit-to-visit variability in glucose levels and additional parameters - blood pressure, heart rate, cholesterol, triglycerides, and weight - on cognitive performance. I find that greater variability in these measures is associated with poorer cognitive performance, with evidence of a cumulative effect, where individuals with more instances of high variability exhibit worse cognition. However, the effect sizes are weak and unlikely to have clinical utility. In chapter seven, I use health records to investigate the prognosis of people who have a vascular component to their dementia. I build upon the findings of the four preceding studies - which aimed to identify clinically meaningful vascular contributors - and define vascular contribution to dementia using three different methods: (1) clinically defined using ICD-10 codes for vascular dementia; (2) defined by the presence of overt or covert cerebrovascular disease on brain scan reports; and (3) defined by the presence of an ICD-10 code for prior stroke or TIA. Results indicate that individuals with a vascular contribution to dementia have a higher risk of death, stroke, epilepsy, fractures, and hospitalisation compared to those without vascular contributors. Finally, chapter eight summarises the key findings, discusses their broader implications, and outlines potential directions for future research.","abstract_has_math":false,"creators":["Sherlock, Laura"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Whiteley, William","Muniz Terrera, Graciela"],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-06-23","date_published":"2026-06-23","updated_at":"2026-07-24T02:14:22Z","subjects":["Vascular Contributors","Cognitive Impairment","Dementia","Existing datasets","Longitudinal Studies","Risk Factors","blood pressure","cholesterol levels"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://github.com/LauraMSherlock/Thesis_code_lists","https://doi.org/10.7488/era/7325"],"render_values":[{"text":"https://github.com/LauraMSherlock/Thesis_code_lists","href":"https://github.com/LauraMSherlock/Thesis_code_lists","code":true},{"text":"https://doi.org/10.7488/era/7325","href":"https://doi.org/10.7488/era/7325","code":true}]}]},"links":{"outbound_url":"https://era.ed.ac.uk/handle/1842/44811","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Whiteley, William","Muniz Terrera, Graciela"]},{"key":"dc:creator","label":"Author","values":["Sherlock, Laura"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-06-23T13:00:03Z"]},{"key":"dc:date.issued","label":"Date","values":["2026-06-23"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["PhD Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Vascular Contributors","Cognitive Impairment","Dementia","Existing datasets","Longitudinal Studies","Risk Factors","blood pressure","cholesterol levels"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://era.ed.ac.uk/handle/1842/44811","https://github.com/LauraMSherlock/Thesis_code_lists","https://doi.org/10.7488/era/7325"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Cognitive impairment and dementia pose a significant and growing public health challenge, yet progress in developing effective interventions to prevent dementia or slow cognitive decline has been limited. Among potential targets, vascular risk factors have emerged as particularly promising. Given the prolonged preclinical phase of dementia and its gradual progression, longitudinal studies are essential not only to track disease trajectories over time but also to identify individuals at risk as early as possible for potential recruitment into future interventions. Despite their importance, long-term follow-up in cohort studies faces significant challenges, including high costs and participant attrition. One promising solution is the use of existing data sources from cohort studies, clinical trial datasets, and routinely collected health records, which provide a cost-effective and efficient means of studying vascular contributions to cognitive dysfunction. In this thesis, I demonstrate how leveraging data from completed clinical trials and routinely collected health records can yield valuable insights into vascular contributors to cognitive impairment and dementia, as well as improve understanding of prognosis in individuals with a vascular component to their dementia. Chapter one introduces the core concepts of this thesis, providing the background and rationale for the five research studies within. Chapter two describes the datasets used: the COGWHEEL dataset, consisting of seven clinical trials of vascular intervention, and the WARBLER and DISCOVER datasets, both derived from Scottish routine clinical health records. This chapter also outlines the advantages and limitations of utilising such existing data sources. Chapters three and four examine the impact of cerebrovascular disease on cognition. First, I investigate the relationship between symptomatic cerebrovascular disease and cognition and find that stroke is associated with around 18 years of cognitive ageing, while transient ischaemic attack is associated with 3 years of ageing. I then turn to asymptomatic cerebrovascular disease, finding that individuals with small vessel disease or ‘silent’ stroke have a 55% increased risk of developing dementia compared to those without covert cerebrovascular disease. Chapters five and six explore the role of cardiovascular risk factors in cognitive dysfunction using clinical trial data. Chapter five examines the association between fasting plasma glucose levels and cognitive impairment, revealing a U-shaped association with small effect sizes. Chapter six expands on this by investigating the impact of visit-to-visit variability in glucose levels and additional parameters - blood pressure, heart rate, cholesterol, triglycerides, and weight - on cognitive performance. I find that greater variability in these measures is associated with poorer cognitive performance, with evidence of a cumulative effect, where individuals with more instances of high variability exhibit worse cognition. However, the effect sizes are weak and unlikely to have clinical utility. In chapter seven, I use health records to investigate the prognosis of people who have a vascular component to their dementia. I build upon the findings of the four preceding studies - which aimed to identify clinically meaningful vascular contributors - and define vascular contribution to dementia using three different methods: (1) clinically defined using ICD-10 codes for vascular dementia; (2) defined by the presence of overt or covert cerebrovascular disease on brain scan reports; and (3) defined by the presence of an ICD-10 code for prior stroke or TIA. Results indicate that individuals with a vascular contribution to dementia have a higher risk of death, stroke, epilepsy, fractures, and hospitalisation compared to those without vascular contributors. Finally, chapter eight summarises the key findings, discusses their broader implications, and outlines potential directions for future research."]},{"key":"dc:title","label":"Title","values":["Vascular contributors to cognitive impairment and dementia: insights from existing data"]}]}],"canonical_facts":{"dc:contributor.advisor":["Whiteley, William","Muniz Terrera, Graciela"],"dc:creator":["Sherlock, Laura"],"dc:date.accessioned":["2026-06-23T13:00:03Z"],"dc:date.issued":["2026-06-23"],"dc:description.abstract":["Cognitive impairment and dementia pose a significant and growing public health challenge, yet progress in developing effective interventions to prevent dementia or slow cognitive decline has been limited. Among potential targets, vascular risk factors have emerged as particularly promising. Given the prolonged preclinical phase of dementia and its gradual progression, longitudinal studies are essential not only to track disease trajectories over time but also to identify individuals at risk as early as possible for potential recruitment into future interventions. Despite their importance, long-term follow-up in cohort studies faces significant challenges, including high costs and participant attrition. One promising solution is the use of existing data sources from cohort studies, clinical trial datasets, and routinely collected health records, which provide a cost-effective and efficient means of studying vascular contributions to cognitive dysfunction. In this thesis, I demonstrate how leveraging data from completed clinical trials and routinely collected health records can yield valuable insights into vascular contributors to cognitive impairment and dementia, as well as improve understanding of prognosis in individuals with a vascular component to their dementia. Chapter one introduces the core concepts of this thesis, providing the background and rationale for the five research studies within. Chapter two describes the datasets used: the COGWHEEL dataset, consisting of seven clinical trials of vascular intervention, and the WARBLER and DISCOVER datasets, both derived from Scottish routine clinical health records. This chapter also outlines the advantages and limitations of utilising such existing data sources. Chapters three and four examine the impact of cerebrovascular disease on cognition. First, I investigate the relationship between symptomatic cerebrovascular disease and cognition and find that stroke is associated with around 18 years of cognitive ageing, while transient ischaemic attack is associated with 3 years of ageing. I then turn to asymptomatic cerebrovascular disease, finding that individuals with small vessel disease or ‘silent’ stroke have a 55% increased risk of developing dementia compared to those without covert cerebrovascular disease. Chapters five and six explore the role of cardiovascular risk factors in cognitive dysfunction using clinical trial data. Chapter five examines the association between fasting plasma glucose levels and cognitive impairment, revealing a U-shaped association with small effect sizes. Chapter six expands on this by investigating the impact of visit-to-visit variability in glucose levels and additional parameters - blood pressure, heart rate, cholesterol, triglycerides, and weight - on cognitive performance. I find that greater variability in these measures is associated with poorer cognitive performance, with evidence of a cumulative effect, where individuals with more instances of high variability exhibit worse cognition. However, the effect sizes are weak and unlikely to have clinical utility. In chapter seven, I use health records to investigate the prognosis of people who have a vascular component to their dementia. I build upon the findings of the four preceding studies - which aimed to identify clinically meaningful vascular contributors - and define vascular contribution to dementia using three different methods: (1) clinically defined using ICD-10 codes for vascular dementia; (2) defined by the presence of overt or covert cerebrovascular disease on brain scan reports; and (3) defined by the presence of an ICD-10 code for prior stroke or TIA. Results indicate that individuals with a vascular contribution to dementia have a higher risk of death, stroke, epilepsy, fractures, and hospitalisation compared to those without vascular contributors. Finally, chapter eight summarises the key findings, discusses their broader implications, and outlines potential directions for future research."],"dc:identifier.uri":["https://era.ed.ac.uk/handle/1842/44811","https://github.com/LauraMSherlock/Thesis_code_lists","https://doi.org/10.7488/era/7325"],"dc:language.iso":["en"],"dc:subject":["Vascular Contributors","Cognitive Impairment","Dementia","Existing datasets","Longitudinal Studies","Risk Factors","blood pressure","cholesterol levels"],"dc:title":["Vascular contributors to cognitive impairment and dementia: insights from existing data"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral"],"dc:type.qualificationname":["PhD Doctor of Philosophy"]},"updated_at":"2026-07-24T02:14:22Z"}