Pabna Medical College Journal Open access || Peer reviewed || Medical research
ISSN : 2958-7794 (Print) ISSN : 3005-6675 (Online)
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Original Articles

The “Lelli’s Test”: a Screening Clinical Test for the Diagnosis of Anterior Cruciate Ligament Injury

*Ali MM¹, Naharin NE², Hossain SME³, Manjur M⁴, Islam MN⁵, Masur MAA⁶, Khatun MF⁷

Abstract

Background :

The anterior cruciate ligament (ACL) is a key stabilizer of the knee, contributing to both rotational and anteroposterior stability. ACL injury is a major knee joint pathology. Common clinical tests used for diagnosis include the anterior drawer test, Lachman’s test, and pivot shift test. This study evaluated the accuracy of Lelli’s test in detecting ACL tears and compared it with MRI findings.

Methods :

This study included 100 patients attending the outpatient department of Orthopedics, Combined Military Hospital (CMH), Bogura, from February 2022 to February 2023. Patients aged 20–60 years presenting with knee symptoms such as pain, locking, or giving way were included. Detailed clinical examination for knee instability, including Lelli’s test, was performed using standard techniques and recorded. All patients underwent MRI of the knee, and results were compared to assess the reliability of Lelli’s test as a screening tool for ACL injury.

Results :

A total of 100 cases were included with a mean age of 35 ± 9 years. The majority were male (98%). Right knee involvement was most common (80%). Sports activities were the leading cause of injury (85%), and the most frequent symptom was giving way (82%).

Lelli’s test demonstrated a sensitivity of 94.18% (CI 70.93–94.57) and specificity of 93.33% (CI 79.85–97.17).

Conclusion :

Lelli’s test is a simple clinical tool with high sensitivity and specificity and can be effectively used as a screening method for ACL injury in both acute and chronic cases.

Keywords : Anterior cruciate ligament Anterior drawer test Lachman test Pivot shift test Lelli’s test

Content Type:
Original Contributions

Published in:
2022, Volume 1 | May, Issue - 1

Pages:
23-26

Publication Date:
2025-03-04



Software ID:
25

ISSN (Print) :
2958-7794

ISSN (Online) :
3005-6675

DOI:
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