Risk factors for dementia in the context of cardiovascular disease: A protocol of an overview of reviews

Brain, Jacob; Tully, Phillip J.; Turnbull, Deborah; Tang, Eugene; Greene, Leanne; Beach, Sarah; Siervo, Mario; Stephan, Blossom Christa Maree

doi:10.1371/journal.pone.0271611

Cited by 9 publications

(7 citation statements)

References 55 publications

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“…The models also showed poor discriminative performance. Overall, the results highlight the need to develop dementia risk models tailored to specific disease populations [ 116 , 117 ].…”

Section: Discussionmentioning

confidence: 99%

What’s new in dementia risk prediction modelling? An updated systematic review

Brain,

Kafadar,

Errington

et al. 2024

Dement Geriatr Cogn Disord Extra

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Introduction Identifying individuals at high risk of dementia is critical to optimized clinical care, formulating effective preventative strategies, and determining eligibility for clinical trials. Since our previous systematic reviews in 2010 and 2015, there has been a surge in dementia risk prediction modelling. The aim of this study is to update our previous reviews to explore, and critically review, new developments in dementia risk modelling. Methods MEDLINE, Embase, Scopus, and Web of Science were searched from March 2014 to June 2022. Studies were included if they were population or community-based cohorts (including electronic health record data), had developed a model for predicting late-life incident dementia and included model performance indices such as discrimination, calibration, or external validation. Results In total, 9,209 articles were identified from the electronic search, of which 74 met the inclusion criteria. We found a substantial increase in the number of new models published from 2014 (>50 new models), including an increase in the number of models developed using machine learning. Over 450 unique predictor (component) variables have been tested. Nineteen studies (26%) undertook external validation of newly developed or existing models, with mixed results. For the first time, models have also been developed in low- and middle-income countries (LMICs) and others validated in racial and ethnic minority groups. Conclusion The literature on dementia risk prediction modelling is rapidly evolving with new analytical developments and testing in LMICs. However, it is still challenging to make recommendations about which one model is the most suitable for routine use in a clinical setting. There is an urgent need to develop a suitable, robust, validated risk prediction model in the general population that can be widely implemented in clinical practice to improve dementia prevention.

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“…The models also showed poor discriminative performance. Overall, the results highlight the need to develop dementia risk models tailored to specific disease populations [ 116 , 117 ].…”

Section: Discussionmentioning

confidence: 99%

What’s new in dementia risk prediction modelling? An updated systematic review

Brain,

Kafadar,

Errington

et al. 2024

Dement Geriatr Cogn Disord Extra

View full text Add to dashboard Cite

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“…Fifth, quantitative measurements of blood pressure, glucose and cholesterol were not available and we could not take in account appropriate control of hypertension, diabetes mellitus and cholesterol. Finally, we could not adjust for factors such as, economic, health, lifestyle and education that could be also linked with dementia risk [51].…”

Section: Discussionmentioning

confidence: 99%

Association between Cardiovascular Diseases and Dementia among various age groups: A Population-Based Cohort Study in Older Adults

Boivin‐Proulx

Brouillette

Dorais³

et al. 2023

Preprint

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The link between cardiovascular (CV) risk factors or diseases and dementia is documented. There is conflicting evidence whether age moderates the association. We need to study this gap so that research and clinical initiatives target appropriate age groups. A cohort of 320,630 adult patients without dementia was built using Quebec healthcare databases (1998–2010). The CV risk factors were hypertension, diabetes and dyslipidemia, while diseases included stroke, myocardial infarction (MI), chronic heart failure (HF), and atrial fibrillation (AF). Dementia risk and CV risk factors or diseases were assessed using incidence rate ratios and Cox regression across age groups. The cohort presented by mainly female sex (67.7%) and mean age of 74.1 years. Incident rate of dementia increased with age, ranging from 4.1 to 93.5 per 1,000 person-years. Diabetes, stroke, HF and AF were significantly associated with dementia risk, hazard ratios ranged from 1.08 to 3.54. The strength of association decreased in advanced age for diabetes, stroke and HF. The results suggest that prevention of diabetes, stroke, HF and AF are crucial to mitigate dementia risk. The pathophysiology of dementia in younger and older populations seems to differ, with less impact of CV risk factors in advanced age.

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“…Again, the risk factors of dementia exhibit similar results by stratifying by sex across age-groups. Last, we could not adjust for factors such as, economic, health status, severity of disease, lifestyle and education that could be also linked with dementia risk 54 .…”

Section: Discussionmentioning

confidence: 99%

Association between cardiovascular diseases and dementia among various age groups: a population-based cohort study in older adults

Boivin-Proulx,

Brouillette,

Dorais

et al. 2023

Sci Rep

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The link between cardiovascular (CV) risk factors or diseases and dementia is documented. There is conflicting evidence whether age moderates the association. We need to study this gap so that research and clinical initiatives target appropriate age groups. A cohort of 320,630 adult patients without dementia was built using Quebec healthcare databases (1998–2010). The CV risk factors were hypertension, diabetes and dyslipidemia, while diseases included stroke, myocardial infarction (MI), chronic heart failure (HF), and atrial fibrillation (AF). Dementia risk and CV risk factors or diseases were assessed using incidence rate ratios and Cox regression across age groups. The cohort presented by mainly female sex (67.7%) and mean age of 74.1 years. Incident rate of dementia increased with age, ranging from 4.1 to 93.5 per 1000 person-years. Diabetes, stroke, HF and AF were significantly associated with dementia risk, hazard ratios ranged from 1.08 to 3.54. The strength of association decreased in advanced age for diabetes, stroke and HF. The results suggest that prevention of diabetes, stroke, HF and AF are crucial to mitigate dementia risk. The pathophysiology of dementia in younger and older populations seems to differ, with less impact of CV risk factors in advanced age.

show abstract

Risk factors for dementia in the context of cardiovascular disease: A protocol of an overview of reviews

Cited by 9 publications

References 55 publications

What’s new in dementia risk prediction modelling? An updated systematic review

What’s new in dementia risk prediction modelling? An updated systematic review

Association between Cardiovascular Diseases and Dementia among various age groups: A Population-Based Cohort Study in Older Adults

Association between cardiovascular diseases and dementia among various age groups: a population-based cohort study in older adults

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