Development and Validation of a Web Calculator for Predicting the Risk of Lower Limb Varicose Veins

Abstract

The aims of the present study were to develop and validate a predictive model for lower limb Varicose Veins, and to visualize the results using a web calculator for assessing the probability of patients developing Lower Limb Varicose Veins. A convenience sampling method was employed to select 421 patients from December 2023 to April 2024 at the health check-up center and vascular surgery outpatient clinic of a tertiary hospital in Xuzhou City. Based on the results of univariate and logistic regression analysis, a prediction model was constructed using logistic regression in machine learning and internally validated. The results were visually presented through a web calculator. This prediction model was developed based on variables such as gender, age, body mass index, standing time, exercise, education level, smoking, and family history. All tested indicators showed that the model has reliable discrimination and calibration. For clinical medical personnel, the web calculator prediction model can quickly and accurately identify patients with lower limb varicose veins, providing reference for developing personalized intervention measures. Furthermore, the web calculator provides a convenient and practical screening tool for primary healthcare providers and the public.

Reporting Method

This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.