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Classifiers of anterior cruciate ligament status in female and male adolescents using return-to-activity criteria

Girard, Céline I. ; Romanchuk, Nicholas J. ; Del Bel, Michael J. ; Carsen, Sasha ; Chan, Adrian D.C. and Benoit, Daniel L. LU (2024) In Knee Surgery, Sports Traumatology, Arthroscopy 33(5). p.1633-1644
Abstract

Purpose: A lack of standardization exists for functional tasks in return-to-activity (RTA) guidelines for adolescents with anterior cruciate ligament injury (ACLi). Identifying the variables that discern ACLi status among adolescents is a first step in the creation of such guidelines following surgical reconstruction. This study investigated the use of classification models to discern ACLi status of adolescents with and without injury using spatiotemporal variables from functional tasks typically used in RTA guidelines for adults. Methods: Sixty-four adolescents with ACLi and 70 uninjured adolescents completed single-limb hops, lunges, squats, countermovement jumps and drop-vertical jumps. Jumping distances, heights, and depths were... (More)

Purpose: A lack of standardization exists for functional tasks in return-to-activity (RTA) guidelines for adolescents with anterior cruciate ligament injury (ACLi). Identifying the variables that discern ACLi status among adolescents is a first step in the creation of such guidelines following surgical reconstruction. This study investigated the use of classification models to discern ACLi status of adolescents with and without injury using spatiotemporal variables from functional tasks typically used in RTA guidelines for adults. Methods: Sixty-four adolescents with ACLi and 70 uninjured adolescents completed single-limb hops, lunges, squats, countermovement jumps and drop-vertical jumps. Jumping distances, heights, and depths were collected. Decision trees (DTs) were used to classify ACLi status and were evaluated using the F-measure (F1), kappa statistic (ĸ) and area under the precision–recall curve (PRC). Independent t tests and effect sizes were calculated for each important classifier of the DT models. Results: A five-variable model classified ACLi status with an accuracy of 67.5% (F1 = 0.6842; ĸ = 0.350; PRC = 0.491) with sex as a classifier. Significant differences were found in three of the four spatiotemporal variables (p ≤ 0.002). Separate models then classified ACLi status in males and females with an accuracy of 53.3% (F1 = 0.5882; ĸ = 0.0541; PRC = 0.476) and 76.9% (F1 = 0.7692; ĸ = 0.541; PRC = 0.528), respectively, with significant differences for all variables (p ≤ 0.013). Conclusions: Among the DT models, females were better able to classify ACLi status compared to males, highlighting the importance of sex-specific rehabilitation guidelines for adolescents. Level of Evidence: Level III.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
functional ability, machine learning, paediatric, sex difference, single limb hop, spatiotemporal measure
in
Knee Surgery, Sports Traumatology, Arthroscopy
volume
33
issue
5
pages
1633 - 1644
publisher
Springer
external identifiers
  • scopus:85205302099
ISSN
0942-2056
DOI
10.1002/ksa.12462
language
English
LU publication?
yes
additional info
Publisher Copyright: © 2024 The Author(s). Knee Surgery, Sports Traumatology, Arthroscopy published by John Wiley & Sons Ltd on behalf of European Society of Sports Traumatology, Knee Surgery and Arthroscopy.
id
6acb6309-3dd9-4a70-bc3c-c880d4601b3e
date added to LUP
2025-04-28 14:06:20
date last changed
2025-04-28 15:11:06
@article{6acb6309-3dd9-4a70-bc3c-c880d4601b3e,
  abstract     = {{<p>Purpose: A lack of standardization exists for functional tasks in return-to-activity (RTA) guidelines for adolescents with anterior cruciate ligament injury (ACLi). Identifying the variables that discern ACLi status among adolescents is a first step in the creation of such guidelines following surgical reconstruction. This study investigated the use of classification models to discern ACLi status of adolescents with and without injury using spatiotemporal variables from functional tasks typically used in RTA guidelines for adults. Methods: Sixty-four adolescents with ACLi and 70 uninjured adolescents completed single-limb hops, lunges, squats, countermovement jumps and drop-vertical jumps. Jumping distances, heights, and depths were collected. Decision trees (DTs) were used to classify ACLi status and were evaluated using the F-measure (F<sub>1</sub>), kappa statistic (ĸ) and area under the precision–recall curve (PRC). Independent t tests and effect sizes were calculated for each important classifier of the DT models. Results: A five-variable model classified ACLi status with an accuracy of 67.5% (F<sub>1</sub> = 0.6842; ĸ = 0.350; PRC = 0.491) with sex as a classifier. Significant differences were found in three of the four spatiotemporal variables (p ≤ 0.002). Separate models then classified ACLi status in males and females with an accuracy of 53.3% (F<sub>1</sub> = 0.5882; ĸ = 0.0541; PRC = 0.476) and 76.9% (F<sub>1</sub> = 0.7692; ĸ = 0.541; PRC = 0.528), respectively, with significant differences for all variables (p ≤ 0.013). Conclusions: Among the DT models, females were better able to classify ACLi status compared to males, highlighting the importance of sex-specific rehabilitation guidelines for adolescents. Level of Evidence: Level III.</p>}},
  author       = {{Girard, Céline I. and Romanchuk, Nicholas J. and Del Bel, Michael J. and Carsen, Sasha and Chan, Adrian D.C. and Benoit, Daniel L.}},
  issn         = {{0942-2056}},
  keywords     = {{functional ability; machine learning; paediatric; sex difference; single limb hop; spatiotemporal measure}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{1633--1644}},
  publisher    = {{Springer}},
  series       = {{Knee Surgery, Sports Traumatology, Arthroscopy}},
  title        = {{Classifiers of anterior cruciate ligament status in female and male adolescents using return-to-activity criteria}},
  url          = {{http://dx.doi.org/10.1002/ksa.12462}},
  doi          = {{10.1002/ksa.12462}},
  volume       = {{33}},
  year         = {{2024}},
}