Effects of anteriorly-loaded treadmill walking on dynamic gait stability in young adults

BackgroundAnteriorly-loaded walking is common in many occupations and may increase fall risk. Dynamic gait stability, defined by the Feasible Stability Region (FSR) theory, quantifies the kinematic relationship between the body’s center of mass (COM) and base of support (BOS). FSR-based dynamic gait stability has been used to evaluate the fall risk.Research questionHow does front load carriage affect dynamic gait stability, step length, and trunk angle among young adults during treadmill walking?MethodsIn this between-subject design study, 30 healthy young adults were evenly randomized into three load groups (0%, 10%, or 20% of body weight). Participants carried their assigned load while walking on a treadmill at a speed of 1.2 m/s. Body kinematics were collected during treadmill walking. Dynamic gait stability (the primary variable) was calculated for two gait events: touchdown and liftoff. Step length and trunk angle were measured as secondary variables. One-way analysis of variance was conducted to detect any group-related differences for all variables. Post-hoc analysis with Bonferroni correction was performed when main group differences were found.ResultsNo significant differences but medium to large effect sizes were found between groups for dynamic gait stability at touchdown (p = 0.194, η² = 0.114) and liftoff (p = 0.122, η² = 0.139). Trunk angle significantly increased (indicating backward lean) with the front load at touchdown (p < 0.001, η² = 0.648) and liftoff (p < 0.001, η² = 0.543). No significant between-group difference was found related to the step length (p = 0.344, η² = 0.076).SignificanceCarrying a front load during walking significantly alters the trunk orientation and may change the COM-BOS kinematic relationship and, therefore, fall risk. The findings could inform the design of future studies focusing on the impact of anterior load carriage on fall risk during different locomotion.     

Anatomically contoured large femoral heads can reduce iliopsoas impingement: A cadaver verification study

While use of large heads in total hip arthroplasty (THA) continues to grow, concerns have been raised regarding anterior hip pain resulting from impingement of the prosthetic head against soft-tissues like the iliopsoas. To address these concerns, a new anatomically contoured head (ACH) was developed. In this study cadaver tests were utilized to show that iliopsoas impingement/tenting caused by conventional heads is significantly relieved with the more rounded and reduced distal profile of the ACH. Thus, the ACH implant may be able to decrease the risk of soft-tissue impingement with conventional heads, particularly in the smaller hip.     

髌周去神经化预防全膝关节置换术后膝前疼痛

目的　依据髌周解剖学特点，探讨全膝关节置换术（total knee arthroplasty，TKA）中应用髌周电灼去神经化的临床效果。 方法　纳入82名诊断为骨性关节炎的患者（91膝），予行双侧或单侧不置换髌骨的TKA，按随机对照原则将病人分为两组，共有41名实验组患者（45膝）在TKA中接受了髌周去神经化处理，41名对照组患者（46膝）未做该处理。手术主刀为同一骨科医师，均使用相同的膝关节假体系统。主要评价项目包括膝关节KSS评分、Western Ontario and McMaster Universities（WOMAC）、Feller髌骨评分及VAS评分。 结果　82名患者术后均获随访，平均随访时间为12个月，两组病人的膝关节KSS评分、WOMAC、Feller髌骨评分及VAS评分均无显著统计学差异（P>0.05）。 结论　在TKA中行髌周电灼去神经化，不能显著改善病人的预后。     

Impact of sampling rate on statistical significance for single subject fMRI connectivity analysis

A typical time series in functional magnetic resonance imaging (fMRI) exhibits autocorrelation, that is, the samples of the time series are dependent. In addition, temporal filtering, one of the crucial steps in preprocessing of functional magnetic resonance images, induces its own autocorrelation. While performing connectivity analysis in fMRI, the impact of the autocorrelation is largely ignored. Recently, autocorrelation has been addressed by variance correction approaches, which are sensitive to the sampling rate. In this article, we aim to investigate the impact of the sampling rate on the variance correction approaches. Toward this end, we first derived a generalized expression for the variance of the sample Pearson correlation coefficient (SPCC) in terms of the sampling rate and the filter cutoff frequency, in addition to the autocorrelation and cross‐covariance functions of the time series. Through simulations, we illustrated the importance of the variance correction for a fixed sampling rate. Using the real resting state fMRI data sets, we demonstrated that the data sets with higher sampling rates were more prone to false positives, in agreement with the existing empirical reports. We further demonstrated with single subject results that for the data sets with higher sampling rates, the variance correction strategy restored the integrity of true connectivity.