Integrating Pedal Power Variables as Predictors of Iliac Artery Flow Limitation in Cycling: A Pilot Study

Flow Limitation of Iliac Artery (FLIA) is a complex pathology that leads to reduced performance and even withdrawal from cycling. The identification of FLIA through performance loss has been studied by analyzing Power Output (PO) data, providing positive discriminatory markers. In the current era of data availability and the integration of predictive performance models in cycling, the study of discriminatory variables for the potential presence of FLIA is emerging as a useful process for integration and evaluation by performance staff. A 33-year-old male cyclist participated in the study, where external PO developed on the pedals was measured second by second during a Graded Exercise Test (GXT), along with the variables Left-Right Balance (L-R Balance) and Pedal Smoothness (PS). Using the second by second (SBS) data, a Student’s t test between variables and a predictive capacity analysis of FLIA were conducted via a Receiver Operating Characteristic (ROC) curve. Significant differences were found in PO (p < 0.000; 95% CI [-12.45, -5.53]), L-R Balance (p < 0.000; 95% CI [-14.86, -12.81]), and PS (p = 0.009; 95% CI [0.11, 0.78]) between the affected and unaffected limb. The ROC analysis showed Areas Under the Curve (AUC) ranging from 0.928 to 0.959, with sensitivity values between 0.88-0.92 and specificity between 0.80-0.84, indicating a high predictive capacity for the studied variables. The logistic model combination of variables showed higher sensitivity and specificity values of 0.90 and 0.92 respectively. The implementation of SBS PO analysis models in cycling could be useful for decision making in the possible presence of FLIA, allowing for the setting of individual thresholds using the discriminatory variables in the study to detect the potential presence of FLIA at an early stage.

Authors

Institutions

Publication Details

Journal
Journal Of Science & Cycling
Published
2026-11-01
Primary Topic
Peripheral Artery Disease Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrating Pedal Power Variables as Predictors of Iliac Artery Flow Limitation in Cycling: A Pilot Study

Jesus
1 links
Journal Of Science & Cycling
Peripheral Artery Disease Management
article

Integrating Pedal Power Variables as Predictors of Iliac Artery Flow Limitation in Cycling: A Pilot Study

Jesus
article en

Abstract

Flow Limitation of Iliac Artery (FLIA) is a complex pathology that leads to reduced performance and even withdrawal from cycling. The identification of FLIA through performance loss has been studied by analyzing Power Output (PO) data, providing positive discriminatory markers. In the current era of data availability and the integration of predictive performance models in cycling, the study of discriminatory variables for the potential presence of FLIA is emerging as a useful process for integration and evaluation by performance staff. A 33-year-old male cyclist participated in the study, where external PO developed on the pedals was measured second by second during a Graded Exercise Test (GXT), along with the variables Left-Right Balance (L-R Balance) and Pedal Smoothness (PS). Using the second by second (SBS) data, a Student’s t test between variables and a predictive capacity analysis of FLIA were conducted via a Receiver Operating Characteristic (ROC) curve. Significant differences were found in PO (p < 0.000; 95% CI [-12.45, -5.53]), L-R Balance (p < 0.000; 95% CI [-14.86, -12.81]), and PS (p = 0.009; 95% CI [0.11, 0.78]) between the affected and unaffected limb. The ROC analysis showed Areas Under the Curve (AUC) ranging from 0.928 to 0.959, with sensitivity values between 0.88-0.92 and specificity between 0.80-0.84, indicating a high predictive capacity for the studied variables. The logistic model combination of variables showed higher sensitivity and specificity values of 0.90 and 0.92 respectively. The implementation of SBS PO analysis models in cycling could be useful for decision making in the possible presence of FLIA, allowing for the setting of individual thresholds using the discriminatory variables in the study to detect the potential presence of FLIA at an early stage.

Journal Of Science & Cycling
University of the Basque Country (ES)
Good health and well-being
Openalex Percentile: Top 10%
Peripheral Artery Disease Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon