Literature DB >> 9727339

Dynamic knee loads during gait predict proximal tibial bone distribution.

D E Hurwitz1, D R Sumner, T P Andriacchi, D A Sugar.   

Abstract

This study tested the validity of the prediction of dynamic knee loads based on gait measurements. The relationship between the predicted loads at the knee and the distribution of bone between the medial and lateral sides of the tibia was examined. The motion and external forces and moments at the knee were measured during gait and a statically determinate muscle model was used to predict the corresponding forces on the medial and lateral tibial plateaus. In particular, the relationship between the knee adduction moment during gait and the ratio or distribution of medial to lateral tibial bone mineral content was studied. Bone mineral content was measured with dual energy X-ray absorptiometry in four regions, two proximal regions 20 mm in height, one medial and one lateral and two distal regions 20 mm in height, one medial and one lateral. The best single predictor of the medial lateral ratio of proximal bone mineral content (bone distribution) was the adduction moment (R2=0.31, p=0.003). Adding weight (negative coefficient. p=0.0004) and the ratio of the average predicted peak force on the medial plateau to the predicted peak force on the lateral plateau (positive coefficient, p=0.0033) to the regression model significantly increased the ability to predict the proximal medial lateral bone distribution (R2=0.72, p=0.0001). Distally neither the subject characteristics nor the gait moments and predicted forces were significant predictors of the bone distribution. The lack of a correlation distally may be reflective of the forces being more evenly distributed further from the tibial plateau. While it has long been suggested that the adduction moment is the primary determinate of the distribution of load between the medial and lateral plateaus, this is the first evidence of its relationship to the underlying bone distribution.

Mesh:

Year:  1998        PMID: 9727339     DOI: 10.1016/s0021-9290(98)00028-1

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  51 in total

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