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基于临床的女性前交叉韧带损伤高风险预测工具的开发和验证。

Development and validation of a clinic-based prediction tool to identify female athletes at high risk for anterior cruciate ligament injury.

机构信息

Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio 45229, USA.

出版信息

Am J Sports Med. 2010 Oct;38(10):2025-33. doi: 10.1177/0363546510370933. Epub 2010 Jul 1.

Abstract

BACKGROUND

Prospective measures of high knee abduction moment (KAM) during landing identify female athletes at high risk for anterior cruciate ligament injury. Laboratory-based measurements demonstrate 90% accuracy in prediction of high KAM. Clinic-based prediction algorithms that employ correlates derived from laboratory-based measurements also demonstrate high accuracy for prediction of high KAM mechanics during landing.

HYPOTHESES

Clinic-based measures derived from highly predictive laboratory-based models are valid for the accurate prediction of high KAM status, and simultaneous measurements using laboratory-based and clinic-based techniques highly correlate.

STUDY DESIGN

Cohort study (diagnosis); Level of evidence, 2.

METHODS

One hundred female athletes (basketball, soccer, volleyball players) were tested using laboratory-based measures to confirm the validity of identified laboratory-based correlate variables to clinic-based measures included in a prediction algorithm to determine high KAM status. To analyze selected clinic-based surrogate predictors, another cohort of 20 female athletes was simultaneously tested with both clinic-based and laboratory-based measures.

RESULTS

The prediction model (odds ratio: 95% confidence interval), derived from laboratory-based surrogates including (1) knee valgus motion (1.59: 1.17-2.16 cm), (2) knee flexion range of motion (0.94: 0.89°-1.00°), (3) body mass (0.98: 0.94-1.03 kg), (4) tibia length (1.55: 1.20-2.07 cm), and (5) quadriceps-to-hamstrings ratio (1.70: 0.48%-6.0%), predicted high KAM status with 84% sensitivity and 67% specificity (P < .001). Clinic-based techniques that used a calibrated physician's scale, a standard measuring tape, standard camcorder, ImageJ software, and an isokinetic dynamometer showed high correlation (knee valgus motion, r = .87; knee flexion range of motion, r = .95; and tibia length, r = .98) to simultaneous laboratory-based measurements. Body mass and quadriceps-to-hamstrings ratio were included in both methodologies and therefore had r values of 1.0.

CONCLUSION

Clinically obtainable measures of increased knee valgus, knee flexion range of motion, body mass, tibia length, and quadriceps-to-hamstrings ratio predict high KAM status in female athletes with high sensitivity and specificity. Female athletes who demonstrate high KAM landing mechanics are at increased risk for anterior cruciate ligament injury and are more likely to benefit from neuromuscular training targeted to this risk factor. Use of the developed clinic-based assessment tool may facilitate high-risk athletes' entry into appropriate interventions that will have greater potential to reduce their injury risk.

摘要

背景

前瞻性测量高膝外展力矩(KAM)可识别高风险女性运动员的前交叉韧带损伤。基于实验室的测量可准确预测 90%的高 KAM。基于诊所的预测算法,采用来自基于实验室的测量的相关因素,也可准确预测着陆时的高 KAM 力学。

假设

基于实验室的高度预测模型得出的基于诊所的测量值可准确预测高 KAM 状态,并且基于实验室和基于诊所的技术同时进行的测量高度相关。

研究设计

队列研究(诊断);证据水平,2 级。

方法

100 名女运动员(篮球、足球、排球运动员)接受基于实验室的测量,以确认确定的实验室相关变量与包括在预测算法中的基于诊所的测量值的有效性,以确定高 KAM 状态。为了分析选定的基于诊所的替代预测指标,另一组 20 名女运动员同时接受基于诊所和基于实验室的测量。

结果

预测模型(优势比:95%置信区间),源自基于实验室的替代指标,包括(1)膝关节外翻运动(1.59:1.17-2.16cm),(2)膝关节屈曲运动范围(0.94:0.89°-1.00°),(3)体重(0.98:0.94-1.03kg),(4)胫骨长度(1.55:1.20-2.07cm)和(5)股四头肌-腘绳肌比(1.70:0.48%-6.0%),以 84%的敏感性和 67%的特异性(P<0.001)预测高 KAM 状态。使用校准医生秤、标准卷尺、标准摄像机、ImageJ 软件和等速测力计的基于诊所的技术显示出高度相关性(膝关节外翻运动,r=.87;膝关节屈曲运动范围,r=.95;胫骨长度,r=.98)与同时进行的基于实验室的测量。体重和股四头肌-腘绳肌比同时存在于两种方法中,因此 r 值为 1.0。

结论

临床上可获得的增加膝关节外翻、膝关节屈曲运动范围、体重、胫骨长度和股四头肌-腘绳肌比的测量值可预测女性运动员的高 KAM 状态,具有较高的敏感性和特异性。表现出高 KAM 着陆力学的女性运动员患前交叉韧带损伤的风险增加,并且更有可能受益于针对该风险因素的神经肌肉训练。使用开发的基于诊所的评估工具可能有助于高危运动员进入适当的干预措施,从而更有潜力降低他们的受伤风险。

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