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The hip-spine relationship is a critical consideration in total hip arthroplasty (THA) procedures. While THA is generally successful in patient, complications such as instability and dislocation can arise. These issues are significantly influenced by the alignment of implant components and the overall balance of the spine and pelvis, known as spinopelvic balance. Patients with alteration of those parameters, in particular rigid spines, often due to fusion surgery, face a higher risk of THA complications, with an emphasis on complications in instability, impingement and dislocation. For these reasons, over the years, computer modelling and simulation techniques have been developed to support clinicians in the different steps of surgery. The aim of the current review is to present current knowledge on hip-spine relationship to serve as a common platform of discussion among clinicians and engineers. The offered overview aims to update the reader on the main critical aspects of the issue, from both a theoretical and practical perspective, and to be a valuable introductory tool for those approaching this problem for the first time. [ABSTRACT FROM AUTHOR]

Tuberculosis is one of the leading causes of death in several developing countries and a public health emergency of international concern. In Silico Trials can be used to support innovation in the context of drug development reducing the duration and the cost of the clinical experimentations, a particularly desirable goal for diseases such as tuberculosis. The agent-based Universal Immune System Simulator was used to develop an In Silico Trials environment that can predict the dose–response of new therapeutic vaccines against pulmonary tuberculosis, supporting the optimal design of clinical trials. But before such in silico methodology can be used in the evaluation of new treatments, it is mandatory to assess the credibility of this predictive model. This study presents a risk-informed credibility assessment plan inspired by the ASME V&V 40‐2018 technical standard. Based on the selected context of use and regulatory impact of the technology, a detailed risk analysis is described together with the definition of all the verification and validation activities and related acceptability criteria. The work provides an example of the first steps required for the regulatory evaluation of an agent-based model used in the context of drug development. [ABSTRACT FROM AUTHOR]

The optimal neuromuscular control (muscle activation strategy that minimises the consumption of metabolic energy) during level walking is very close to that which minimises the force transmitted through the joints of the lower limbs. Thus, any suboptimal control involves an overloading of the joints. Some total knee replacement patients adopt suboptimal control strategies during level walking; this is particularly true for patients with co-morbidities that cause neuromotor control degeneration, such as Parkinson's Disease (PD). The increase of joint loading increases the risk of implant failure, as reported in one study in PD patients (5.44% of failures at 9 years follow-up). One failure mode that is directly affected by joint loading is massive wear of the prosthetic articular surface. In this study we used a validated patient-specific biomechanical model to estimate how a severely suboptimal control could increase the wear rate of total knee replacements. Whereas autopsy-retrieved implants from non-PD patients typically show average polyethylene wear of 17 mm3 per year, our simulations suggested that a severely suboptimal control could cause a wear rate as high as of 69 mm3 per year. Assuming the risk of implant failure due to massive wear increase linearly with the wear rate, a severely suboptimal control could increase the risk associated to that failure mode from 0.1% to 0.5%. Based on these results, such increase would not be not sufficient to justify alone the higher incidence rate of revision in patients affected by Parkinson's Disease, suggesting that other failure modes may be involved. [ABSTRACT FROM AUTHOR]