Osteoarthritis and cartilage · 2019
Patient characteristics affect hip contact forces during gait.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
De Pieri E, Lunn D E, Chapman G J, Rasmussen K P, Ferguson S J, Redmond A C
Аннотация
OBJECTIVE: To examine hip contact force (HCF), calculated through multibody modelling, in a large total hip replacement (THR) cohort stratified by patient characteristics such as body mass index (BMI), age and function.
METHOD: 132 THR patients undertook one motion capture session of gait analysis at a self-selected walking speed. HCFs were then calculated using the AnyBody Modelling System. Patients were stratified into three BMI groups, five age groups, and finally three functional groups determined by their self-selected gait speed. By means of statistical parametric mapping (SPM), statistical analyses of the 1-dimensional time series were performed to separately evaluate the influence of age, BMI and functionality on HCF.
RESULTS: The mean predicted HCFs were comparable to HCFs measured with instrumented prostheses reported in the literature. The SPM analysis revealed a statistically significant positive linear correlation between BMI and HCF, indicating that obese patients are more likely to experience higher HCF during most of the stance phase, while a statistically significant negative correlation with age was found only during the late swing-phase. Patients with higher functional ability exhibited significantly increased peak HCF, while patients with lower functional ability demonstrated lower HCFs overall and a pathological flattening of the typical double hump force profile.
CONCLUSION: HCFs experienced at the bearing surface are highly dependent on patient characteristics. BMI and functional ability were determined to have the biggest influence on contact forces. Current preclinical testing standards do not reflect this.
METHOD: 132 THR patients undertook one motion capture session of gait analysis at a self-selected walking speed. HCFs were then calculated using the AnyBody Modelling System. Patients were stratified into three BMI groups, five age groups, and finally three functional groups determined by their self-selected gait speed. By means of statistical parametric mapping (SPM), statistical analyses of the 1-dimensional time series were performed to separately evaluate the influence of age, BMI and functionality on HCF.
RESULTS: The mean predicted HCFs were comparable to HCFs measured with instrumented prostheses reported in the literature. The SPM analysis revealed a statistically significant positive linear correlation between BMI and HCF, indicating that obese patients are more likely to experience higher HCF during most of the stance phase, while a statistically significant negative correlation with age was found only during the late swing-phase. Patients with higher functional ability exhibited significantly increased peak HCF, while patients with lower functional ability demonstrated lower HCFs overall and a pathological flattening of the typical double hump force profile.
CONCLUSION: HCFs experienced at the bearing surface are highly dependent on patient characteristics. BMI and functional ability were determined to have the biggest influence on contact forces. Current preclinical testing standards do not reflect this.