Objectives (1) To investigate the psychometric properties of a patient-reported numerical rating scale (NRS) for evaluating functional disability in osteoarthritis (OA), in comparison with the WOMAC function scale and with a physician-reported function NRS; (2) to estimate the patient acceptable symptomatic state (PASS) and the minimal clinically important improvement (MCII) values for treatment with non-steroidal anti-inflammatory drugs (NSAIDs). Methods Data were extracted from a prospective multicentre study involving 1186 patients with knee or hip OA. The psychometric properties assessed were feasibility: percentage of responses, floor and ceiling effects; construct validity by examining the correlations with classically used OA outcomes measures; responsiveness by comparing the results of before and 1 month after treatment with NSAIDs using standardised response mean (SRM) and effect size (ES). The MCII and PASS values of each function scale were calculated by an anchoring method. Results No floor or ceiling effect was observed. High correlations were observed as expected between the patient NRS and WOMAC function, pain visual analogue scale and patient global assessment. The responsiveness was moderate to large, with SRM and ES ranging from 0.6 (hip OA) to 0.9 (knee OA) and higher than that of the WOMAC function scale. The PASS was close to 3 for the NRS scales. The MCII appears to be the change that makes the OA functional disability decrease from baseline to the PASS. Conclusion The patient-reported NRS demonstrated good psychometric properties, similar to the WOMAC function scale and can be regarded as a promising tool in therapeutic evaluation and decision-making in OA.

Locomotion assistive devices equipped with a microprocessor can potentially automatically adapt their behavior when the user is transitioning from one locomotion mode to another. Many developments in the field have come from machine learning driven controllers on locomotion assistive devices that recognize/predict the current locomotion mode or the upcoming one. This review synthesizes the machine learning algorithms designed to recognize or to predict a locomotion mode in order to automatically adapt the behavior of a locomotion assistive device. A systematic review was conducted on the Web of Science and MEDLINE databases (as well as in the retrieved papers) to identify articles published between 1 January 2000 to 31 July 2020. This systematic review is reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and is registered on Prospero (CRD42020149352). Study characteristics, sensors and algorithms used, accuracy and robustness were also summarized. In total, 1343 records were identified and 58 studies were included in this review. The experimental condition which was most often investigated was level ground walking along with stair and ramp ascent/descent activities. The machine learning algorithms implemented in the included studies reached global mean accuracies of around 90%. However, the robustness of those algorithms seems to be more broadly evaluated, notably, in everyday life. We also propose some guidelines for homogenizing future reports.

Background: Even though it has been suggested that antiretroviral therapy has an impact on severe hypovitaminosis D (SHD) in HIV infected patients, it could be speculated that the different levels of residual inflammation on HAART (Highly Active Anti Retroviral Therapy) could contribute to SHD and aggravate bone catabolism in these patients. Methods: A cross-sectional study was carried out in an unselected cohort of 263 HIV infected outpatients consulting during Spring 2010. Clinical examinations were performed and medical history, food habits, sun exposure and addictions were collected. Fasting blood samples were taken for immunological, virological, inflammation, endocrine and bone markers evaluations. Results: Ninety-five (36%) patients had SHD. In univariate analysis, a significant and positive association was found between SHD and IL6 (p = 0.001), hsCRP (p = 0.04), increased serum C-Telopeptides X (CTX) (p = 0.005) and Parathyroid Hormon (PTH) (p < 0.0001) levels. In multivariate analysis, SHD deficiency correlated significantly with increased IL-6, high serum CTX levels, lower mean daily exposure to the sun, current or past smoking, hepatitis C, and functional status (falls), but not with the time spent on the current HAART (by specific drug or overall). Conclusions: SHD is frequent and correlates with inflammation in HIV infected patients. Since SHD is also associated with falls and increased bone catabolism, it may be of interest to take into account not only the type of antiretroviral therapy but also the residual inflammation on HAART in order to assess functional and bone risks. This finding also suggests that vitamin D supplementation may be beneficial in these HIV-infected patients.