Prediction of ACL-tear by lower limbs muscle strength and flexibility: a prospective cohort study in 95 female soccer players

ABSTRACT

The aims of the study were to build models using logistic regression analysis of flexibility and strength tests to prospectively predict risk factors for anterior cruciate ligament tear (ACL-tear) in female soccer (FS) players, and to determine training cut-off for risk factors of the predictive model built. A prospective cohort study of 95 female players (aged 14–33 years) was conducted. Age, anthropometric data, soccer history, lower limb range of motion (ROM) and hip maximal isometric strength (MIS) were measured. At the prospective follow-up after 12 months, 7.4% of the players had developed an ACL-tear. The model showed a significant relationship (χ²(93) = 30.531, p < 0.001) between the ACL-tear and the predictor variables (leg length, HAD-NH [hip adduction] MIS, asymmetric ROM [ankle dorsiflexion with knee extended (AD-KE) and with knee flexed (AD-KF), and HE (hip extension)], hip ROM [HIR (internal rotation) and HAB (abduction)]). The Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) for model fit were 30.24 and 51.79, respectively. The value R² showed good model fit, 76.5% for Nagelkerke´s R², 71.4% for McFadden´s R² and 67.5% for Tjur´s R². For the screening test, cut-off for leg length of ≥0.40 m, for HIR ROM of ≤44º and for asymmetry of HE ROM of ≥5° were set, which have an acceptable (AUC ≥ 0.755) discriminatory ability for the development of ACL-tear.

KEYWORDS:

• Knee injury
• soccer
• prediction model
• ROM-SPORT battery
• prevention

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data associated with the paper are not publicly available but are available from the corresponding author on reasonable request.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15438627.2023.2280554

Additional information

Funding

This study is part of the project “El Fútbol Femenino Importa: Identificación del Riesgo de Lesión a través de la Inteligencia Artificial” (I+D+I/PID2020-115886RB-I00), funded by the Spanish Ministry of Science and Innovation, the State Research Agency (AEI) and the European Regional Development Fund (ERDF) (MCIN/AEI/10.13039/501100011033). Francisco Ayala was supported by a Ramón y Cajal Postdoctoral Fellowship from the Spanish Ministry of Science and Innovation (RYC2019-028383-I). This work was supported by the Fundación Séneca—Agencia de Ciencia y Tecnología de la Región de Murcia (Regional Program for Mobility, Collaboration, and Knowledge Exchange) under the Jiménez de la Espada Mobility Grant 21735/EE/22 (P.S.B.) during the research visit to the University of Wisconsin-Parkside between April and August 2023.