Female National Collegiate Athletic Association Division-I athlete injury prediction by vertical countermovement jump force-time metrics

(Verletzungsvorhersage für weibliche Division-I-Athleten des nationalen Collegesportverbandes anhand von Kraft-Zeit-Metriken für Countermovement Sprünge)

Vertical countermovement jump (CMJ) assessments on force plates have been purported to screen for musculoskeletal injury risk (MSKI) but with little scientific support. Thus, this study aimed to identify associations and noncontact lower-body injury predictability with CMJ force-time metrics in female athletes. The study entailed a retrospective analysis of routine injury and performance monitoring from 155 female National Collegiate Athletics Association Division I athletes. Noncontact lower-body injuries included in analysis were confirmed by medical staff, occurred during competition or training, resulted in time loss from training, and occurred within 3 months following CMJ testing (2 maximal effort, no arm swing, jumps on dual force plates). A total of 44 injuries occurred within 3 months following CMJ baseline testing and resulted in an average of 24.5 missed days from training. Those who sustained an injury were more likely to sustain another injury (15 of 44 injuries [33.1%]; odds ratio = 3.05 [95% CI = 1.31-6.99]). For every 1-unit increase from the mean in eccentric mean power and minimum eccentric force, there was a decrease in odds of sustaining a MSKI. Despite high overall model accuracy (85.6%), the receiving operating characteristic area under the curve (65.9%) was unacceptable and the true positive rate (recall) was 0.0%. Thus, no injuries in the testing data set were correctly classified by the logistic regression model with CMJ force-time metrics as predictors. Baseline CMJ assessment may not be useful for noncontact lower-body musculoskeletal injury screening or predictability in National Collegiate Athletics Association female athletes.
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Bibliographische Detailangaben
Schlagworte:
Notationen:Biowissenschaften und Sportmedizin
Tagging:Countermovement-Sprung maschinelles Lernen
Veröffentlicht in:The Journal of Strength and Conditioning Research
Sprache:Englisch
Veröffentlicht: 2024
Online-Zugang:https://doi.org/10.1519/JSC.0000000000004758
Jahrgang:38
Heft:4
Seiten:783-786
Dokumentenarten:Artikel
Level:hoch