Introduction: Peripheral arterial disease (PAD) and abdominal aortic aneurysm (AAA) are vascular conditions associated with significant morbidity and mortality, with 25% of AAA patients and 23% of PAD patients being at a high risk of developing cardiovascular disease. Cardiovascular risk management can reduce the risk of major adverse cardiovascular events in AAA patients from 43% to 14%. However, cardiovascular risk is not always adequately addressed in these patients. The VASCUL-AID-PRO study aims to deliver clinically relevant prediction models using artificial intelligence and machine learning of patient outcomes to enable personalized management of vascular disease. Method: VASCUL-AID-PRO is a multi-centre international prospective cross-sectional study aiming to include 500 AAA patients and 600 PAD patients across 6 European centres. The aim is to achieve a follow-up time up to 4 years. The study will include individuals aged 40-90 with either an abdominal aortic aneurysm (infrarenal, juxtarenal, pararenal, or suprarenal abdominal aortic aneurysm) or Fontaine stage 2 peripheral arterial disease. The VASCUL-AID-PRO study will gather a variety of data from all participants, including clinical data, blood and tissue samples, cardiovascular lab values, imaging data, electrocardiograms, data from wearables and quality of life. This data gathered will be used to further develop the multi model prediction models being developed on 5000 AAA and 6000 PAD patients included in the currently ongoing VASCUL-AID-RETRO study, with the aim of providing a clinically relevant prediction models of disease progression and other cardiovascular disease for AAA and PAD patients. Furthermore, the models developed in the VASCUL-AID studies will be internally validated using a subset of patients from the VASCUL-AID-PRO study. Ethical considerations: Ethical and legal considerations are paramount throughout the VASCUL-AID project. To address these concerns, an ELSI framework will be developed and integrated into all stages of the project. This framework will be continuously updated to ensure alignment with evolving ethical, legal, and social standards. This framework will specifically focus on patient safety, data handling, AI regulation and implementation, and potential biases associated with AI.
Study Type
OBSERVATIONAL
Enrollment
1,100
Development and internal validation of AI-driven tools to predict high or low risk disease progression in AAA and PAD.
The VASCUL-AID AI tools aim to predict AAA (rupture, mortality, cerebrovascular accident) and PAD (mortality, myocardial infarction, major amputation) progression, MACE and MALE. The internal validation is done by comparing the predicted disease progression, MACE, MALE and mortality rates with actual disease progression.
Time frame: From baseline to 4 years follow-up.
Accuracy of developed VASCUL-AID driven algorithms that classify AAA patients according to high or low risk disease progression.
Accuracy of developed VASCUL-AID AI-driven algorithms that classify AAA patients according to high or low risk disease progression and MACE. In addition, models will be developed on the other predefined outcomes from the core outcome set, these include: clinical success after an operation \[yes/no\], graft infection after an operation \[yes/no\], reintervention \[yes/no\], the AAA can be treated through endovascular treatment \[yes/no\], adherence to prescribed drugs \[yes/no\], secondary prevention, treatment options and complications.
Time frame: From baseline to 4 years follow-up
Accuracy of developed VASCUL-AID driven algorithms that classify PAD patients according to high or low risk disease progression.
Accuracy of developed VASCUL-AID AI-driven algorithms that classify PAD patients according to high or low risk disease progression, MALE and MACE. In addition, models will be developed on the other predefined outcomes from the core outcome set, these include: acute limb ischemia \[yes/no\], thromboembolic complications \[yes/no\], disease progression \[yes/no\], pain-free walking distance \[meters\], physical activity, smoking cessation, secondary prevention, treatment options and complications.
Time frame: From baseline to 4 years follow-up
Patient reported outcome measures for AAA and PAD.
Good communication by healthcare worker about diagnosis \[Questionnaires\].
Time frame: From baseline to 4 years follow-up.
Patient reported outcome measures for health-related quality of life.
Numeric (Pain) Rating Scale (0-10, no pain to most intense pain).
Time frame: From baseline to 4 year follow-up.
Patient reported outcome measures for health-related quality of life.
PROMIS Scale v1.2 - Global Health measure. Answer rank on a scale of 0-5, with the higher score being more preferred.
Time frame: From baseline to 4 year follow-up
Patient reported outcome measures for health-related quality of life.
EQ-5D-5L Euroqol questionnaire. The descriptive system comprises five dimensions: mobility, self-care, usual activities, pain/discomfort and anxiety/depression. Each dimension has 5 levels: no problems, slight problems, moderate problems, severe problems and extreme problems. The patient is asked to indicate his/her health state by ticking the box next to the most appropriate statement in each of the five dimensions. This decision results in a 1-digit number that expresses the level selected for that dimension. The digits for the five dimensions can be combined into a 5-digit number that describes the patient's health state.
Time frame: From baseline to 4 years follow-up.
Patient reported outcome measures for vascular quality of life for PAD.
Vascular Quality of Life Questionnaire (VascuQol) consists of 25 questions regarding the QoL in patients with vascular diseases, regarding activity level, symptoms, pain, emotion and social consequences. It uses a 7-point Likert scale, where a low score equels a severe sense of limitations.
Time frame: From baseline to 4 year follow-up
Patient reported outcome measures for AAA related quality of life.
AneurysmDQoL - Abdominal Aortic Aneurysm Quality of Life The AneurysmDQoL is a 24-item measure including two overview items designed for audit purposes which measure generic 'present QoL' and AAA-specific 'impact of AAA on QoL'. A further 22 items measure the impact of having an abdominal aortic aneurysm on specific aspects of life and the importance of these aspects of life for QoL. In addition the questionnaire includes a free-text item. This allows patients to comment on any other QoL domains not covered in the questionnaire.
Time frame: From baseline to 4 year follow-up.
Questions regarding medical status.
A custom list of questions developed to gather all changes in medical history of the patients.
Time frame: From baseline to 4 year follow-up
6-minute walking test questionnaire
The 6-minute walking test is a test in which patients are asked to walk for a duration of 6 minutes and then report the distance they have walked in that time and whether they experienced any complaints.
Time frame: From baseline to 4 year follow-up
Medication use questionnaire
Asks the patient to write down all active medication.
Time frame: From baseline to 4 year follow-up
Smoking cessation questionnaire
A custom list of questions asking patients about smoking cessation and how they are managing quitting.
Time frame: From baseline to 4 year follow-up.
Questionnaire regarding health-care provider communication.
This questionnaire scores how well the patient experienced contact with their health care provider. Each question is answered on a scale between strongly agree - strongly disagree.
Time frame: From baseline to 4 year follow-up.
Cost-effectiveness and Clinical Implementation Study
The project will include data collection of costs and Health-Related Quality of Life (HRQoL) prospectively. The economic analysis will be performed in accordance with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. An estimation of costs and HRQoL progression until MACE will be performed and descriptive statistics will be used to describe their respective evolution (up to 4 years). To describe the evolution and further estimate threshold where the implementation of VASCULAID within hospitals could be more efficient, the number of patients with at least one MACE during the follow-up period will be used to estimate the costs and HRQoL per event among the dedicated subgroup of population where HRQoL is collected. Only direct costs will be considered in the analysis. The result will be expressed in euros per patient (then distinguishing MACE vs free of MACE) over the follow-up. QALYs will be expressed per patients.
Time frame: baseline to 4 years follow-up
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