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Construction and validation of a prediction model for complications of femoral artery access
Zhifei Feng1,2, Jiali Ding1,2, Zhangyi Liu1,2
1General Surgery, Yongchuan Hospital Affiliated with Chongqing Medical University, Chongqing, China.
Insights
This study identified key risk factors for femoral artery access complications, including vascular calcification and diabetes history. A validated nomogram model accurately predicts these risks, aiding clinical decision-making.
Area of Science:
- Vascular Surgery
- Interventional Cardiology
- Medical Informatics
Background:
- Femoral artery access is crucial for endovascular interventions.
- Complications at the puncture site can lead to significant patient morbidity.
- Predictive models are needed to identify patients at high risk.
Purpose of the Study:
- To identify independent risk factors for femoral artery access complications.
- To develop and validate a nomogram prediction model for these complications.
Main Methods:
- Retrospective analysis of 507 patients undergoing endovascular intervention via femoral artery access.
- Logistic regression analysis to identify risk factors.
- Nomogram construction and validation using ROC curve, Hosmer-Lemeshow test, and calibration curves.
Main Results:
- Vascular calcification, history of diabetes, platelet count, and puncture site-femoral head relationship were significant predictors.
- The nomogram achieved an AUC of 0.924, with 81.80% sensitivity and 95.20% specificity.
- The model demonstrated good calibration and predictive performance.
Conclusions:
- Platelet count, diabetes history, vascular calcification, and puncture site position are independent risk factors.
- The developed nomogram accurately predicts femoral artery access complications.
- This tool can aid in risk stratification and patient management.
Objective:
To analyze the risk factors for the complications of access and to construct and validate a nomogram prediction model for their occurrence.
Methods:
Patients undergoing endovascular intervention via femoral artery access between January 2020 and April 2025 were enrolled in the study. Related clinical data were retrospectively collected and analyzed. Patients were divided into complication (n = 19) and non-complication (n = 488) groups based on the occurrence of postoperative complications associated with femoral artery puncture site. The general cohort characteristics were compared between the two groups, and the risk factors for the postoperative complications were identified based on univariate and multivariate logistic regression analyses. A nomogram prediction model was constructed and its performance was evaluated using the area under the receiver operating characteristic (ROC) curve, the Hosmer-Lemeshow test, calibration curve, and decision curve analyses.
Results:
Four potential predictors were identified based on the multivariate logistic regression analysis results: vascular calcification [odds ratio (OR) = 7.952, 95% confidence interval (CI): 1.653-38.254], history of diabetes (OR = 18.793, 95% CI: 3.670-96.225), platelet count (OR = 0.980, 95% CI: 0.967-0.994), and positional relationship between the puncture point and femoral head (OR = 6.125, 95% CI: 1.048-35.800). The nomogram model incorporating these factors demonstrated strong performance, with an area under the ROC curve of 0.924 (95% confidence interval: 0.839-1.000), sensitivity of 81.80%, specificity of 95.20%, and overall accuracy of 94.70%.The Hosmer-Lemeshow test yielded χ 2 = 12.535 and P = 0.8184, indicating a good model fit. Calibration curves showed strong agreement between the nomogram predictions and observed outcomes. Both the ROC and decision curve analysis confirmed the nomogram's robust predictive performance.
Conclusions:
Platelet count, history of diabetes, vascular calcification, and positional relationship between the puncture point and the femoral head are independent risk factors for the complications of femoral artery access. The nomogram model established based on these indicators demonstrated a high accuracy in predicting the risk of complications.
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