Mechanisms underpinning the peak knee flexion moment increase over 2-years following arthroscopic partial meniscectomy

Hall, Michelle; Wrigley, Tim V.; Metcalf, Ben; Hinman, Rana S; Cicuttini, Flavia Maria; Dempsey, Alasdair R.; Mills, Peter; Lloyd, David G.; Bennell, Kim L

doi:10.1016/j.clinbiomech.2015.09.006

Cited by 11 publications

(4 citation statements)

References 29 publications

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“…The vKRF represents an equal and opposite vertical force acting between the tibia and femur, without accounting for muscle forces (12). Finally, although gait speed and measures of body size do not directly reflect joint loading, these are main effectors of the vertical ground reaction force (13), a primary determinant of the KAM, KFM, and vKRF (12,14,15).…”

Section: Introductionmentioning

confidence: 99%

Association of Machine Learning–Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis

Brisson

Gatti

Damm

et al. 2021

Arthritis & Rheumatology

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Objective The relationship between in vivo knee load predictions and longitudinal cartilage changes has not been investigated. We undertook this study to develop an equation to predict the medial tibiofemoral contact force (MCF) peak during walking in persons with instrumented knee implants, and to apply this equation to determine the relationship between the predicted MCF peak and cartilage loss in patients with knee osteoarthritis (OA). Methods In adults with knee OA (39 women, 8 men; mean ± SD age 61.1 ± 6.8 years), baseline biomechanical gait analyses were performed, and annualized change in medial tibial cartilage volume (mm3/year) over 2.5 years was determined using magnetic resonance imaging. In a separate sample of patients with force‐measuring tibial prostheses (3 women, 6 men; mean ± SD age 70.3 ± 5.2 years), gait data plus in vivo knee loads were used to develop an equation to predict the MCF peak using machine learning. This equation was then applied to the knee OA group, and the relationship between the predicted MCF peak and annualized cartilage volume change was determined. Results The MCF peak was best predicted using gait speed, the knee adduction moment peak, and the vertical knee reaction force peak (root mean square error 132.88N; R2 = 0.81, P < 0.001). In participants with knee OA, the predicted MCF peak was related to cartilage volume change (R2 = 0.35, β = −0.119, P < 0.001). Conclusion Machine learning was used to develop a novel equation for predicting the MCF peak from external biomechanical parameters. The predicted MCF peak was positively related to medial tibial cartilage volume loss in patients with knee OA.

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Section: Introductionmentioning

confidence: 99%

Association of Machine Learning–Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis

Brisson

Gatti

Damm

et al. 2021

Arthritis & Rheumatology

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“…In addition, extent of meniscal resection is known to be proportionally correlated with increased tibiofemoral contact pressures of up to 80% to 90%, and directly affects knee biomechanics and kinematics. [19][20][21][22][23] Extent of meniscal resection may also modulate functional outcomes by altering knee kinematics, including increased knee adduction, flexion, and extension moments, [24][25][26] as well as knee extensor strength. [27][28][29] Conclusions Roughly 1 in 2 runners return to their preoperative running frequency after undergoing APM.…”

Section: Limitationsmentioning

confidence: 99%

Up to One-Half of Runners Return to Running One Year After Arthroscopic Partial Meniscectomy

Sayegh

Dib²,

Lowenstein³

et al. 2022

Arthroscopy, Sports Medicine, and Rehabilitation

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“…In 1948, Fairbank[ 8 ] reported the clinical outcomes of 107 patients after total meniscectomies and found degenerative knee changes in most of them. From then, several other studies demonstrated the detrimental effects of total meniscectomies on knee joint[ 9 - 13 ]. These studies significantly changed the treatment approach of meniscus tears.…”

Section: Introductionmentioning

confidence: 99%

Meniscus tears treatment: The good, the bad and the ugly-patterns classification and practical guide

R¹,

Russo²,

Palco³

et al. 2023

World J Orthop

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Over the years, several studies demonstrated the crucial role of knee menisci in joint biomechanics. As a result, save the meniscus has become the new imperative nowadays, and more and more studies addressed this topic. The huge amount of data on this topic may create confusion in those who want to approach this surgery. The aim of this review is to provide a practical guide for treatment of meniscus tears, including an overview of technical aspects, outcomes in the literature and personal tips. Taking inspiration from a famous movie directed by Sergio Leone in 1966, the authors classified meniscus tears in three categories: The good, the bad and the ugly lesions. The inclusion in each group was determined by the lesion pattern, its biomechanical effects on knee joint, the technical challenge, and prognosis. This classification is not intended to substitute the currently proposed classifications on meniscus tears but aims at offering a reader-friendly narrative review of an otherwise difficult topic. Furthermore, the authors provide a concise premise to deal with some aspects of menisci phylogeny, anatomy and biomechanics.

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Mechanisms underpinning the peak knee flexion moment increase over 2-years following arthroscopic partial meniscectomy

Cited by 11 publications

References 29 publications

Association of Machine Learning–Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis

Association of Machine Learning–Based Predictions of Medial Knee Contact Force With Cartilage Loss Over 2.5 Years in Knee Osteoarthritis

Up to One-Half of Runners Return to Running One Year After Arthroscopic Partial Meniscectomy

Meniscus tears treatment: The good, the bad and the ugly-patterns classification and practical guide

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