Prediction model of isolated iliac and abdominal aneurysms

• Published in: European journal of clinical investigation Vol. 51; no. 7; pp. e13517 - n/a
• Main Authors: Lanzarone, Ettore, Finotello, Alice, Pane, Bianca, Pratesi, Giovanni, Palombo, Domenico, Conti, Michele, Spinella, Giovanni
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.07.2021
• Subjects: abdominal aortic aneurysm; Age Factors; Aged; Aged, 80 and over; Aneurysms; Aorta; Aortic Aneurysm, Abdominal - diagnostic imaging; Aortic Aneurysm, Abdominal - epidemiology; Aortic aneurysms; Body mass; Body Mass Index; Body size; Cardiovascular diseases; cardiovascular risk factors; Diabetes; Diabetes mellitus; Diabetes Mellitus - epidemiology; Dyslipidemia; Dyslipidemias - epidemiology; Evaluation; Female; Genetics; Health risks; Heart Diseases - epidemiology; Humans; Hypertension; Hypertension - epidemiology; Iliac Aneurysm - diagnostic imaging; Iliac Aneurysm - epidemiology; Incidence; isolated iliac aneurysm; Logistic Models; logistic regression prediction; Male; Mass Screening; Middle Aged; Prediction models; Regression models; Risk analysis; Risk Assessment; Risk factors; screening; Statistical analysis; Ultrasonography; screening; cardiovascular risk factors; isolated iliac aneurysm; logistic regression prediction; abdominal aortic aneurysm
• ISSN: 0014-2972; 1365-2362; 1365-2362
• DOI: 10.1111/eci.13517

Objectives We analyse the cardiovascular risk factors in patients undergoing screening for Isolated Iliac Aneurysm (IIA) and Abdominal Aortic Aneurysm (AAA) and propose a logistic regression model to indicate patients at risk of IIA and/or AAA. Methods A screening programme was carried out to identify the presence of aneurysm based on Duplex scan examination. Cardiovascular risk factors information was collected from each subject. A descriptive analysis for the incidence of IIA and AAA stratified by age and sex was carried out to evaluate factors incidence. A logistic regression model was developed to predict the probability of developing an aneurysm based on the observed risk factor levels. A threshold probability of aneurysm risk for a datum patient was also identified to effectively direct screening protocols to patients most at risk. Results A cohort of 10 842 patients was evaluated: 1.52% affected by IIA, 2.69% by AAA and 3.90% by at least one. Risk factors analysis showed that: IIA was correlated with cardiological status, diabetes, cardiovascular disease family history, and dyslipidaemia; AAA was correlated with cardiological status, body mass index, hypertension, and dyslipidaemia; diabetes and dyslipidaemia were the most relevant factors with at least one aneurysm. The prediction tool based on the logistic regression and the threshold probability predict the presence of IIA and AAA in 69.7% and 83.8% of cases, under k‐fold cross‐validation. Conclusions The proposed regression model can represent a valid aid to predict IIA and AAA presence and to select patients to be screened.