Peripheral vascular disease (PVD) is a major global health problem, affecting 3-10% of the human population, and is characterized by a narrowing of blood vessels, commonly in the legs, and can develop into a painful condition known as critical limb ischemia (CLI). Currently, CLI can only be treated by surgically repairing or bypassing blocked blood vessels. Some patients may not be suitable candidates for surgical intervention, meaning amputation of the affected limb is the only option which leads to an increased risk of mortality. Several CLI risk assessment scores (Prevent III, Finnvasc, CRAB and ERICVA) have recently been proposed for patients with CLI. However, these predictive models may not be reliable and practical for routine clinical use. Therefore, a novel and practical predictive model is urgently needed.
This project is a collaborative, cross-sectional study that aims to determine if certain quantifiable parameters of a patient’s laboratory and clinical data (i.e. full blood count, lifestyle, medical condition and history, etc.) can be utilized as a suitable prognostic indicator of six-month and one-year mortality along with other morbidities including amputation. All admitted patients who present with CLI are administered a general health screening and subject to a full blood count. We aim to use statistical and logistic regression modeling to determine if certain quantifiable parameters can be used as clinical indicators/predictors of a patient’s prognostic outcome. This level of patient population stratification and clinical prediction modeling will be beneficial in facilitating patient management and intervention.
