Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice

Genome Analysis of the Meat Starter Culture Bacterium Staphylococcus carnosus TM300▿ †

The Staphylococcus carnosus genome has the highest GC content of all sequenced staphylococcal genomes, with 34.6%, and therefore represents a species that is set apart from S. aureus, S. epidermidis, S. saprophyticus, and S. haemolyticus. With only 2.56 Mbp, the genome belongs to a family of smaller staphylococcal genomes, and the ori and ter regions are asymmetrically arranged with the replichores I (1.05 Mbp) and II (1.5 Mbp). The events leading up to this asymmetry probably occurred not that long ago in evolution, as there was not enough time to approach the natural tendency of a physical balance. Unlike the genomes of pathogenic species, the TM300 genome does not contain mobile elements such as plasmids, insertion sequences, transposons, or STAR elements; also, the number of repeat sequences is markedly decreased, suggesting a comparatively high stability of the genome. While most S. aureus genomes contain several prophages and genomic islands, the TM300 genome contains only one prophage, ΦTM300, and one genomic island, νSCA1, which is characterized by a mosaic structure mainly composed of species-specific genes. Most of the metabolic core pathways are present in the genome. Some open reading frames are truncated, which reflects the nutrient-rich environment of the meat starter culture, making some functions dispensable. The genome is well equipped with all functions necessary for the starter culture, such as nitrate/nitrite reduction, various sugar degradation pathways, two catalases, and nine osmoprotection systems. The genome lacks most of the toxins typical of S. aureus as well as genes involved in biofilm formation, underscoring the nonpathogenic status

Predicting advanced balance ability and mobility with an instrumented timed up and go test

Extensive test batteries are often needed to obtain a comprehensive picture of a person\u2019s functional status. Many test batteries are not suitable for active and healthy adults due to ceiling effects, or require a lot of space, time, and training. The Community Balance and Mobility Scale (CBMS) is considered a gold standard for this population, but the test is complex, as well as time-and resource intensive. There is a strong need for a faster, yet sensitive and robust test of physical function in seniors. We sought to investigate whether an instrumented Timed Up and Go (iTUG) could predict the CBMS score in 60 outpatients and healthy community-dwelling seniors, where features of the iTUG were predictive, and how the prediction of CBMS with the iTUG compared to standard clinical tests. A partial least squares regression analysis was used to identify latent components explaining variation in CBMS total score. The model with iTUG features was able to predict the CBMS total score with an accuracy of 85.2% (84.9\u201385.5%), while standard clinical tests predicted 82.5% (82.2\u201382.8%) of the score. These findings suggest that a fast and easily administered iTUG could be used to predict CBMS score, providing a valuable tool for research and clinical care