Related Experiment Video
Updated: Dec 13, 2025
Utility of Dissociated Intrinsic Hand Muscle Atrophy in the Diagnosis of Amyotrophic Lateral Sclerosis
Published on: March 4, 2014
Machine Learning Confirms Nonlinear Relationship between Severity of Peripheral Arterial Disease, Functional
Zulfiqar Qutrio Baloch1, Syed Ali Raza2, Rahul Pathak3
1Department of Cardiology, Michigan State University/Sparrow Hospital, 1215 E Michigan Ave, Lansing, MI 48912, USA.
Background:
Peripheral arterial disease (PAD) involves arterial blockages in the body, except those serving the heart and brain. We explore the relationship of functional limitation and PAD symptoms obtained from a quality-of-life questionnaire about the severity of the disease. We used a supervised artificial intelligence-based method of data analyses known as machine learning (ML) to demonstrate a nonlinear relationship between symptoms and functional limitation amongst patients with and without PAD.
Objectives:
This paper will demonstrate the use of machine learning to explore the relationship between functional limitation and symptom severity to PAD severity.
Methods:
We performed supervised machine learning and graphical analysis, analyzing 703 patients from an administrative database with data comprising the toe-brachial index (TBI), baseline demographics and symptom score(s) derived from a modified vascular quality-of-life questionnaire, calf circumference in centimeters and a six-minute walk (distance in meters).
Results:
Graphical analysis upon categorizing patients into critical limb ischemia (CLI), severe PAD, moderate PAD and no PAD demonstrated a decrease in walking distance as symptoms worsened and the relationship appeared nonlinear. A supervised ML ensemble (random forest, neural network, generalized linear model) found symptom score, calf circumference (cm), age in years, and six-minute walk (distance in meters) to be important variables to predict PAD. Graphical analysis of a six-minute walk distance against each of the other variables categorized by PAD status showed nonlinear relationships. For low symptom scores, a six-minute walk test (6MWT) demonstrated high specificity for PAD.
Conclusions:
PAD patients with the greatest functional limitation may sometimes be asymptomatic. Patients without PAD show no relationship between functional limitation and symptoms. Machine learning allows exploration of nonlinear relationships. A simple linear model alone would have overlooked or considered such a nonlinear relationship unimportant.
More Related Videos
14:52Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication
Published on: December 11, 2013
07:25Predicting Amputation using Local Circulating Mononuclear Progenitor Cells in Angioplasty-treated Patients with Critical Limb Ischemia
Published on: September 22, 2020
Related Concept Videos
01:21Peripheral Arterial Disease II: Clinical Manifestations and Diagnostic Evaluation
01:26Peripheral Artery Disease IV: Nursing Management
01:30Peripheral Artery Disease I: Introduction
01:27Atherosclerosis II: Clinical Manifestations and Diagnostic Tests
01:27Peripheral Artery Disease III: Interprofessional Care
01:27Assessment of the Cardiovascular System III: Palpation
Jugular Venous Pressure (JVP) Measurement
Position the patient at a thirty- to forty-five-degree angle or in a semi-fowler's position. Look for the highest point of pulsation in the internal jugular vein and measure the vertical distance to the angle of Loius or sternal angle. A normal JVP is 3-4 cm above...