Search

To study the direction and biomechanical consequences of hip center of rotation (HCOR) migration in Crowe type III and VI hips after total hip arthroplasty, post-operative radiographs and CT scans of several unilaterally affected hips were evaluated. Using a three-dimensional model of the human hip, the HCOR was moved in all directions, and joint reaction force (JRF) and abductor muscle force (AMF) were calculated for single-leg stance configuration. Comparing to the normal side, HCOR had displaced medially and inferiorly by an average of 23.4% and 20.8%, respectively, of the normal femoral head diameter. Significant decreases in JRF (13%) and AMF (46.13%) were observed in a presumptive case with that amount of displacement. Isolated inferior displacement had a small, increasing effect on these forces. In Crowe type III and IV hips, the HCOR migrates inferiorly and medially after THA, resulting in a decrease in JRF, AMF, and abductor muscle contraction force.

article i nfo Article history: Received 6 February 2013 Accepted 15 April 2013 A biomechanical computer-based model was developed to simulate the influence of patellar thickness on passive knee flexion after arthroplasty. Using the computer model of a single-radius, PCL-sacrificing knee prosthesis, a range of patella-implant composite thicknesses was simulated. The biomechanical model was then replicated using two cadaveric knees. A patellar-thickness range of 15 mm was applied to each of the knees. Knee flexion was found to decrease exponentially with increased patellar thickness in both the biomechanical and experimental studies. Importantly, this flexion loss followed an exponential pattern with higher patellar thicknesses in both studies. In order to avoid adverse biomechanical and functional consequences, it is recommended to restore patellar thickness to that of the native knee during total knee arthroplasty.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic since early 2020. The coronavirus disease 2019 (COVID-19) has already caused more than three million deaths worldwide and affected people's physical and mental health. COVID-19 patients with mild symptoms are generally required to self-isolate and monitor for symptoms at least for 14 days in the case the disease turns towards severe complications. In this work, we overviewed the impact of COVID-19 on the patients' general health with a focus on their cardiovascular, respiratory and mental health, and investigated several existing patient monitoring systems. We addressed the limitations of these systems and proposed a wearable telehealth solution for monitoring a set of physiological parameters that are critical for COVID-19 patients such as body temperature, heart rate, heart rate variability, blood oxygen saturation, respiratory rate, blood pressure, and cough. This physiological information can be further combined to potentially estimate the lung function using artificial intelligence (AI) and sensor fusion techniques. The prototype, which includes the hardware and a smartphone app, showed promising results with performance comparable to or better than similar commercial devices, thus potentially making the proposed system an ideal wearable solution for long-term monitoring of COVID-19 patients and other chronic diseases.

The aim of survival analysis in healthcare is to estimate the probability of occurrence of an event, such as a patient's death in an intensive care unit (ICU). Recent developments in deep neural networks (DNNs) for survival analysis show the superiority of these models in comparison with other well-known models in survival analysis applications. Ensuring the reliability and explainability of deep survival models deployed in healthcare is a necessity. Since DNN models often behave like a black box, their predictions might not be easily trusted by clinicians, especially when predictions are contrary to a physician's opinion. A deep survival model that explains and justifies its decision-making process could potentially gain the trust of clinicians. In this research, we propose the reverse survival model (RSM) framework that provides detailed insights into the decision-making process of survival models. For each patient of interest, RSM can extract similar patients from a dataset and rank them based on the most relevant features that deep survival models rely on for their predictions.

Addressing acetabular deficiency during arthroplasty of dysplastic hips is challenging. We assessed outcomes of a protocol for choosing either impaction or structural graft for this purpose.This retrospective study included 59 patients (71 hips) with a dysplastic hip and over 30% uncoverage that underwent cementless total hip arthroplasty. Morselized impaction grafting was performed for hips where initial stability of the acetabular cup was achieved. In others, a shelf graft was inserted before implantation of the acetabular cup. Outcomes were assessed at a minimum follow-up of 4 years.Fifty-seven (80.3%) hips underwent impaction grafting and 14 (19.7%) received a structural graft. Mean age at surgery was 48.1 ± 13.5 (18-68) years for impaction and 48.6 ± 14 (24-70) years for shelf grafts. Mean increase in Harris Hip Score was 51.5 ± 9.3 and 50 ± 11.2 for the impaction and structural groups, respectively, at a mean follow-up of 92 (49-136) months (P = .6). Heterotopic ossification occurred in 16 patients in the impaction group vs none in the structural group (P = .004). Radiologically, mean percentages of cup coverage provided by the graft were 47.8 ± 10.9% and 48.9 ± 13.3% in the impaction and structural groups, respectively (P = .75). All but one of shelf grafts united to host bone and all impaction grafts incorporated. There was one case of cup loosening in the structural graft group.Most dysplastic acetabula with over 30% defect can be addressed using a cementless cup and impaction grafting, with good results in the midterm. In about 20% of cases, initial press-fit is not attainable and structural support-like shelf graft becomes necessary.IV.