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基于继发稳定结构损伤负荷的ACL缺损旋转不稳表型探索性分类

Journal of ISAKOS : joint disorders & orthopaedic sports medicine · 2026-Aug-06
阅读数 0
Rivarola Horacio, Collazo Cristian, Palanconi Marcos, Meninato Marcos, Castro Alejandro Barros, Carrillo Carlos Peñaherrera et al.

简介

本研究基于300例ACL重建患者的回顾性队列,整合外侧半月板、腘肌半月板束、Segond骨折及全身韧带松弛等次级稳定结构损伤,构建旋转损伤负荷指数(RIBI),并通过层次聚类识别出四种旋转不稳表型:低负荷型(30.7%)、外侧半月板主导型(25.3%)、韧带松弛主导型(20.3%)和高旋转负荷型(23.7%)。RIBI每增加1分,高度轴移试验风险增加47%(…

英文摘要

INTRODUCTION: Anterior cruciate ligament (ACL) deficiency is traditionally viewed as a relatively homogeneous condition in which rotational instability is primarily attributed to ACL rupture severity and a limited number of clinical risk factors. However, growing evidence suggests that injury to secondary stabilizing structures may substantially influence rotational knee biomechanics. Whether ACL-deficient knees can be categorized into distinct rotational instability phenotypes based on cumulative secondary stabilizer injury burden remains unknown. METHODS: A retrospective cohort study was conducted in accordance with STROBE guidelines. Three hundred consecutive patients undergoing primary ACL reconstruction between 2018 and 2024 were included irrespective of injury chronicity. Patients were not stratified according to time from injury because the objective of the study was exploratory phenotype discovery rather than temporal characterization. Clinical, magnetic resonance imaging, and arthroscopic variables related to lateral secondary rotational stabilizers were recorded, including hypermobile lateral meniscus, popliteomeniscal fascicle injury, lateral meniscotibial injury, lateral meniscal radial or root tears, Segond fractures, generalized ligamentous laxity, and chondral lesions. Medial meniscal pathology was not incorporated into the predefined conceptual framework. An expert-derived Rotational Injury Burden Index (RIBI; range 0-13) was developed to quantify cumulative structural compromise. Logistic regression evaluated associations between injury burden and high-grade pivot shift. Hierarchical clustering, bootstrap validation, silhouette analysis, and K-means sensitivity analysis were used to identify and validate rotational instability phenotypes. RESULTS: The mean RIBI score was 4.8 ± 2.3. Increasing rotational injury burden was independently associated with high-grade pivot shift (adjusted OR 1.47; 95% CI 1.28-1.71; p < 0.001). Hierarchical clustering identified four reproducible phenotypes: Low-Burden ACL Phenotype (30.7%), Lateral Meniscal-Dominant Phenotype (25.3%), Hyperlaxity-Dominant Phenotype (20.3%), and High Rotational Burden Phenotype (23.7%). Cluster stability was high (bootstrap coefficient 0.82), and the four-cluster solution demonstrated satisfactory separation (silhouette coefficient 0.61). Meniscal pathology, particularly HLM and meniscotibial insufficiency, demonstrated strong associations with increasing rotational burden and instability severity. CONCLUSION: Within this cohort, ACL-deficient knees demonstrated reproducible patterns of secondary stabilizer injury that clustered into distinct rotational instability phenotypes. Increasing cumulative secondary stabilizer injury burden was independently associated with severe rotational instability. Beyond identifying patients with low or high cumulative injury burden, the proposed phenotype framework provides additional structural characterization by distinguishing intermediate-burden knees with different patterns of secondary stabilizer injury. LEVEL OF EVIDENCE: III, retrospective cohort study.

关键词

ACL deficiency hypermobile lateral meniscus machine learning meniscotibial injury phenotype classification pivot shift popliteomeniscal fascicles rotational injury burden rotational instability secondary stabilizers

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