2023 ISAKOS Biennial Congress ePoster
Can Motion Analysis Detect Patients At Risk Of First Anterior Cruciate Ligament Injury: A Systematic Review
Ahmed Al-Asmar, Montreal, quebec CANADA
Sami Chergui, MD, Saint-Bruno-De-Montarville CANADA
Brandon Hall, Ile Bizard, Quebec CANADA
Felix Mailloux, MDCM Candidate, Class of 2025, Montreal, Québec CANADA
Thierry Pauyo, MD, FRCSC, Montreal, QC CANADA
McGill University, Montréal, Québec, CANADA
FDA Status Not Applicable
Summary
A systematic review comprehending 14 studies and over 3000 participants was performed in order to review the anterior cruciate ligament (ACL) first-injury risk factors that motion analysis can detect.
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Abstract
Introduction
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Approximately 250 000 anterior cruciate ligament (ACL) injuries occur annually in the United States alone [1]. There have been several attempts to develop screening tools to allow clinicians to detect patients at higher risk of first ACL injury [2]. The aims of this study are to (1) assess if motion analysis can detect risk factors associated with non-contact ACL injuries, and (2) survey the most common ACL injury mechanisms in pediatric patients.
METHODS-
In this systematic review, a search of Embase and Medline databases (from their starting date until the 17th of February, 2022) was performed to identify 544 articles reporting on the application of 2-dimensional (2D) or 3-dimensional (3D) motion analysis, or any of the other subtypes of motion analysis and capture systems that assess participant biomechanics. Studies that examined animal-based models and previously ACL injured participants without appropriate stratification between first and previous ACL injuries were excluded. Extracted variables from included studies were demographic data, movement executed by participants, biomechanical variables measured using motion analysis, ACL injury risk factor(s) proposed in each study, and whether the study used marker or marker-less motion analysis. Critical appraisal of studies was conducted using the National Heart, Lung, and Blood Institute (NHLBI) quality assessment tool. Results were reported using descriptive statistics.
RESULTS-
Of 544 search results, 12 prospective studies were included. Total number of participants was 3690 (85.80% female, 14.20% male). Mean age was 17.95 (3.31) years and participant follow-up time ranged from 12 to 96 months. 3D motion analysis was used in seven studies, 2D in three studies, and the Landing Error Scoring System (LESS) in two studies. Marker-less motion analysis was utilized in two studies and the number of markers used in the rest of the studies ranged from six to 44. Movements executed by participants included a drop-jump maneuver in 9 studies, cutting maneuver in two studies, single-leg squats in one study, and decelerating maneuver in one study. Proposed ACL injury risk factors included increased dynamic knee valgus in vertical drop jump (VDJ) maneuver, increased medial knee displacement during the contact phase of a VDJ maneuver (OR, 1.40; 95% CI, 1.12- 1.74), increased internal knee rotation angle at initial contact (IC) of a side-cutting (SC) maneuver (RR,1.12; 95% CI, 1.07–1.18), decreased hip flexion at IC of a SC maneuver (RR, 0.61; 95% CI, 0.39–0.99), and decreased peak knee flexion angle at IC of a VDJ task (HR for 10 degree increase in knee flexion angle: 0.55; 95 % CI 0.34 to 0.88).
CONCLUSION-
Many motion analysis systems show promise for detecting non-contact ACL injury risk factors. Taking into consideration anticipation-, fatigue-, and maturation-induced biomechanical changes would advance our understanding of first ACL injury risk factors.