| Literature DB >> 35887637 |
Hui Yin Lim1,2,3,4,5, Louise M Burrell5, Rowena Brook1,2, Harshal H Nandurkar3, Geoffrey Donnan6, Prahlad Ho1,2,3,4.
Abstract
Cardiovascular disease remains the leading cause of death in the era of modern medicine despite major advancements in this field. Current available clinical surrogate markers and blood tests do not adequately predict individual risk of cardiovascular disease. A more precise and sophisticated tool that can reliably predict the thrombosis and bleeding risks at an individual level is required in order for clinicians to confidently recommend early interventions with a favorable risk-benefit profile. Critical to the development of this tool is the assessment and understanding of Virchow's triad and its complex interactions between hypercoagulability, endothelial dysfunction and vessel flow, a fundamental concept to the development of thrombosis. This review explores the pathophysiology of cardiovascular disease stemming from the triad of factors and how individualized risk assessment can be improved through the multimodal use of tools such as global coagulation assays, endothelial biomarkers and vessel flow assessment.Entities:
Keywords: Virchow’s triad; cardiovascular disease; endothelial markers; global coagulation assays; risk assessment
Year: 2022 PMID: 35887637 PMCID: PMC9323107 DOI: 10.3390/jpm12071140
Source DB: PubMed Journal: J Pers Med ISSN: 2075-4426
A summary of some of the available primary prevention risk calculators.
| Australian Absolute CVD Risk Calculator [ | ASCVD Risk Estimator Plus [ | Framingham General CVD Risk Score [ | SCORE2 [ | QRISK3 [ | |
|---|---|---|---|---|---|
| Year | 2012 | 2013 | 2008 | 2021 | 2018 |
| Components | |||||
| Race | √ | √ | |||
| Gender | √ | √ | √ | √ | √ |
| Age | √ | √ | √ | √ | √ |
| Total cholesterol | √ | √ | √ | √ | √ |
| HDL | √ | √ | √ | √ | √ |
| LDL | √ | √ | |||
| Systolic blood pressure | √ | √ | √ | √ | √ |
| Diastolic blood pressure | √ | ||||
| Anti-hypertensives | √ | √ | √ | ||
| Diabetes | √ | √ | √ | √ | |
| Smoking | √ | √ | √ | √ | √ |
| Location | √ | √ | |||
| Others | ECG LVH | Statin | Family history, body mass index, chronic kidney disease, SLE, migraine, atypical antipsychotics, corticosteroids, mental illness, erectile dysfunction | ||
| Age range (years) | 35–74 | 40–79 | >30 | 40–69 | 25–84 |
| Risk projection | 5-year risk | 10-year risk | 10-year risk | 10-year risk | 10-year risk |
| Endpoints assessed | MI | Nonfatal MI | CHD death | CHD death | CHD death |
| Webpage |
AHA American College of Cardiology/American Heart Association; CHD coronary heart disease; CVD cardiovascular disease; ECG electrocardiography; LVH left ventricular hypertrophy; MI myocardial infarction; SLE systemic lupus erythematous; TIA transient ischemic attack.
Figure 1Some of the key biomarkers used in the assessment of the various components of Virchow’s triad. (Abbreviations: ACE2 angiotensin converting enzyme 2; TFPI tissue factor pathway inhibitor; hsCRP high-sensitivity C-reactive protein; HbA1c glycated hemoglobin).
Figure 2A simplified coagulation cascade highlighting the key pathways examined by some of the available global coagulation assays (highlighted boxes) (Abbreviations: TFPI tissue factor pathway inhibitor; PAI-1 plasminogen activator inhibitor-1; tPA tissue plasminogen activator).
Figure 3A simplified diagram of some of the endothelial biomarkers available to measure endothelial function (Abbreviations: HbA1c glycated hemoglobin; CHIP clonal hematopoiesis of indeterminate potential; NO nitric oxide; vWF von Willebrand factor; TF tissue factor, PAI-1 plasminogen-activator-inhibitor-1; AT antithrombin; tPA tissue plasminogen activator; CAMs cellular adhesion molecules; CRP C-reactive protein; ACE2 angiotensin converting enzyme 2; ROS reactive oxygen species; TXA2 thromboxane A2; apoB apolipoprotein B; PCSK-9 proprotein convertase subtilisin/kexin type 9; Lp-PLA2 lipoprotein-associated phospholipase A2; CIMT carotid intima media thickness).