Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-25 @ 1:18 AM
Ignite Modification Date:
2025-12-25 @ 1:18 AM
NCT ID:
NCT04454593
Brief Summary:
This study evaluates whether the patellar axial radiograph of lateral patellar curvature angle （LPCA）with knee flexion at 30 ° can be used as a new diagnostic surrogate of lateral patellar compression syndrome（LPCS）. We believe that the new index LPCA has high sensitivity and specificity in initial diagnosis of LPCS using axial patellar radiograph with knee flexion at 30 ° , and has high application value.
Detailed Description:
Background: A well-established reference is lacking for diagnosing lateral patellar compression syndrome (LPCS), and this diagnosis currently depends on clinicians' subjective judgment and several examination results. X-rays are primarily used to diagnose LPCS, but they have low detection rates of patellar tilt using the congruence angle (CA) and patellar tilting angle (PTA).
Purpose: To investigate whether patellar axial radiography of the lateral patellar curvature angle (LPCA) of knee in 30° flexion can diagnose LPCS.
Methods: We enrolled 87 patients between 2016 and 2019 and divided them as per diagnosis into three groups of 29 each: LPCS, patellar dislocation (PD, control), and meniscus tear (MT, negative control) groups. A senior radiologist and the chief physician of sports medicine examined their patellar axial radiographs of the knee in 30° flexion using a computer imaging system, measuring LPCA, PTA, and CA. Univariate analysis of variance and Kruskal-Wallis H test were used to compare measurement data with normal distribution and non-normal distribution, respectively. Bonferroni correction was used to analyze different indicators for different groups. The area under the curve (AUC) was calculated to verify the value of LPCA in initial diagnosis of LPCS.
Study:
NCT04454593
Study Brief:
Protocol Section:
NCT04454593