Effectiveness of rehabilitative interventions beginning within the first month of stroke onset in improving lower extremity-related outcomes: a systematic review and network meta-analysis

Reviews about early interventions, which are important in stroke rehabilitation due to significant neural plasticity, are relatively less. This study objective was to investigate the effectiveness of different interventions started within one-month post-stroke in improving lower extremity-related outcomes as compared to conventional rehabilitation and the corresponding effectiveness ranking. Cochrane Library, Ovid, PubMed, and Scopus were searched for articles dated up to 18 March 2022. Randomised controlled trials were included if they evaluated the effectiveness of two or more different non-drug, non-invasive, and non-surgical interventions which were started within one-month post-stroke on lower extremity-related outcomes. Network meta-analysis revealed that transcranial direct current stimulation, repetitive transcranial magnetic stimulation, mirror therapy, cycling, transcutaneous auricular vagus nerve stimulation, neuromuscular electrical stimulation (NMES), combination of robot and NMES, and thermal stimulation were significantly more effective in improving lower extremity motor function than conventional rehabilitation. In improving mobility, mirror therapy, cycling, and thermal stimulation were significantly more effective. In enhancing balance, physio ball, transcutaneous electrical nerve stimulation, cycling, thermal stimulation, and robot showed significantly higher effectiveness. Thermal stimulation scored the highest effectiveness ranking in improving lower extremity motor function and mobility whereas robot and backward walking achieved the highest effectiveness ranking in improving balance and gait speed respectively

The efficacy of trunk training treatment intensities on trunk control of stroke patients: a systematic review, meta-analysis and meta-regression

This study aims to assess the efficacy of trunk training treatment intensities on trunk control of stroke patients with the Trunk Impairment Scale (TIS) score. A structured literature search was performed in several databases from the first indexed article until December 2022, including PubMed, Web of Science, PEDro, Cochrane Library, and Scopus. In addition, the study selection was investigated following the PRISMA guideline. Only randomised controlled trials that examined the trunk training effectiveness on trunk control (measured by the TIS after stroke) were included. A total of 25 trials with 976 stroke patients were evaluated. Meanwhile, seven studies were classified as high bias risk. Irrespective of the training mode and methodology quality, the large effects favored trunk training compared to the control group. The sensitivity analysis revealed a large effect in favour of trunk training on trunk control [SMD = 1.16 (95% CI: 0.93-1.39); p<0.00001, I2 = 80%]. Subsequently, the most effective trunk training treatment duration was 10 hours of core stability exercise for trunk control improvement [SMD = 3.20 (95% CI: 2.25- 4.15)]. The meta-regression analysis demonstrated no strong evidence of trunk training treatment intensities on the effect sizes. Trunk training was effective in trunk rehabilitation. Nonetheless, specific trunk training was required for different stroke phases. Interestingly, the effect size was meaningfully enlarged by adding 15 minutes of core stability exercise to the conventional therapy (five sessions per week over eight weeks of intervention). This result was useful in determining the number of sessions for effective trunk rehabilitatio

The application of digital volume correlation (DVC) to evaluate strain predictions generated by finite element models of the osteoarthritic humeral head

Continuum-level finite element models (FEMs) of the humerus offer the ability to evaluate joint replacement designs preclinically; however, experimental validation of these models is critical to ensure accuracy. The objective of the current study was to quantify experimental full-field strain magnitudes within osteoarthritic (OA) humeral heads by combining mechanical loading with volumetric microCT imaging and digital volume correlation (DVC). The experimental data was used to evaluate the accuracy of corresponding FEMs. Six OA humeral head osteotomies were harvested from patients being treated with total shoulder arthroplasty and mechanical testing was performed within a microCT scanner. MicroCT images (33.5 µm isotropic voxels) were obtained in a pre- and post-loaded state and BoneDVC was used to quantify full-field experimental strains (≈ 1 mm nodal spacing, accuracy = 351 µstrain, precision = 518 µstrain). Continuum-level FEMs with two types of boundary conditions (BCs) were simulated: DVC-driven and force-driven. Accuracy of the FEMs was found to be sensitive to the BC simulated with better agreement found with the use of DVC-driven BCs (slope = 0.83, r2 = 0.80) compared to force-driven BCs (slope = 0.22, r2 = 0.12). This study quantified mechanical strain distributions within OA trabecular bone and demonstrated the importance of BCs to ensure the accuracy of predictions generated by corresponding FEMs

Topological optimization in hip prosthesis design

With particular interest on total hip arthroplasty (THA), optimization of orthopedic prostheses is employed in this work to minimize the probability of implant failure or maximize prosthesis reliability. This goal is often identified with the reduction of stress concentrations at the interface between bone and these devices. However, aseptic loosening of the implant is mainly influenced by bone resorption phenomena revealed in some regions of the femur when a prosthesis is introduced. As a consequence, bone resorption appears due to stress shielding, that is to say the decrease of the stress level in the implanted femur caused by the significant load carrying of the prosthesis due to its higher stiffness. A maximum stiffness topological optimization-based (TO) strategy is utilized for non-linear static finite element (FE) analyses of the femur–implant assembly, with the goal of reducing stress shielding in the femur and to furnish guidelines for re-designing hip prostheses. This is accomplished by employing an extreme accuracy for both the three-dimensional reconstruction of the femur geometry and the material properties maps assigned as explicit functions of the local densities