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后足着地跑步者中与髌股关节疼痛相关的生物力学、人体测量学和人口统计学因素的相互作用:一种分类与回归树方法。

Interaction of Biomechanical, Anthropometric, and Demographic Factors Associated with Patellofemoral Pain in Rearfoot Strike Runners: A Classification and Regression Tree Approach.

作者信息

de Souza Júnior José Roberto, Gaudette Logan Walter, Johnson Caleb D, Matheus João Paulo Chieregato, Lemos Thiago Vilela, Davis Irene S, Tenforde Adam S

机构信息

Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital/Harvard Medical School, Boston, MA, USA.

Graduate Program of Sciences and Technologies in Health, University of Brasília, Brasília, DF, Brazil.

出版信息

Sports Med Open. 2024 Jan 8;10(1):5. doi: 10.1186/s40798-023-00671-8.

Abstract

BACKGROUND

Patellofemoral pain (PFP) is among the most common injuries in runners. While multiple risk factors for patellofemoral pain have been investigated, the interactions of variables contributing to this condition have not been explored. This study aimed to classify runners with patellofemoral pain using a combination of factors including biomechanical, anthropometric, and demographic factors through a Classification and Regression Tree analysis.

RESULTS

Thirty-eight runners with PFP and 38 healthy controls (CON) were selected with mean (standard deviation) age 33 (16) years old and body mass index 22.3 (2.6) kg/m. Each ran at self-selected speed, but no between-group difference was identified (PFP = 2.54 (0.2) m/s x CON = 2.55 (0.1) m/s, P = .660). Runners with patellofemoral pain had different patterns of interactions involving braking ground reaction force impulse, contact time, vertical average loading rate, and age. The classification and regression tree model classified 84.2% of runners with patellofemoral pain, and 78.9% of healthy controls. The prevalence ratios ranged from 0.06 (95% confidence interval: 0.02-0.23) to 9.86 (95% confidence interval: 1.16-83.34). The strongest model identified runners with patellofemoral pain as having higher braking ground reaction force impulse, lower contact times, higher vertical average loading rate, and older age. The receiver operating characteristic curve demonstrated high accuracy at 0.83 (95% confidence interval: 0.74-0.93; standard error: 0.04; P < .001).

CONCLUSIONS

The classification and regression tree model identified an influence of multiple factors associated with patellofemoral pain in runners. Future studies may clarify whether addressing modifiable biomechanical factors may address this form of injury.

摘要

背景

髌股疼痛(PFP)是跑步者中最常见的损伤之一。虽然已经对髌股疼痛的多种风险因素进行了研究,但尚未探讨导致这种情况的变量之间的相互作用。本研究旨在通过分类与回归树分析,结合生物力学、人体测量学和人口统计学因素,对患有髌股疼痛的跑步者进行分类。

结果

选取了38名患有髌股疼痛的跑步者和38名健康对照者(CON),平均(标准差)年龄为33(16)岁,体重指数为22.3(2.6)kg/m²。每组均以自定速度跑步,但未发现组间差异(髌股疼痛组=2.54(0.2)m/s,对照组=2.55(0.1)m/s,P = 0.660)。患有髌股疼痛的跑步者在制动地面反作用力冲量、接触时间、垂直平均负荷率和年龄方面存在不同的相互作用模式。分类与回归树模型对84.2%的髌股疼痛跑步者和78.9%的健康对照者进行了分类。患病率比值范围为0.06(95%置信区间:0.02 - 0.23)至9.86(95%置信区间:1.16 - 83.34)。最强的模型将患有髌股疼痛的跑步者识别为具有更高的制动地面反作用力冲量、更低的接触时间、更高的垂直平均负荷率和更大的年龄。受试者工作特征曲线显示准确率较高,为0.83(95%置信区间:0.74 - 0.93;标准误差:0.04;P < 0.001)。

结论

分类与回归树模型确定了与跑步者髌股疼痛相关的多种因素的影响。未来的研究可能会阐明解决可改变的生物力学因素是否可以解决这种形式的损伤。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dda2/10774254/41c8dfb25ba1/40798_2023_671_Fig1_HTML.jpg

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