The long-term effect of comprehensive geriatric care on gait after hip fracture: the Trondheim Hip Fracture Trial--a randomised controlled trial.

SUMMARY: At present, most hip fracture patients are treated in orthopaedic wards. This study showed that a relatively short hospital intervention based on principles of comprehensive geriatric assessment resulted in safer and more efficient gait as long as 1 year following the fracture as compared to conventional orthopaedic treatment. INTRODUCTION: Hip fracture patients are frail, and the fracture is usually followed by substantial decline in gait function. Few studies have assessed gait characteristics other than gait speed and knowledge about the effect of early intervention on long-term gait outcome is sparse. The purpose of this study was to evaluate the long-term effect of pre- and post-surgery Comprehensive Geriatric Care (CGC) on ability to walk, self-reported mobility and gait characteristics in hip fracture patients. METHODS: Two armed, parallel group randomised controlled trial comparing CGC to conventional Orthopaedic Care (OC) in pre- and early post-surgery phase. Hip fracture patients (n = 397), community-dwelling, age >70 years and able to walk at time of the fracture were included. Spatial and temporal gait characteristics were collected using an instrumented walkway (GAITRite® system) 4 and 12 months post-surgery. RESULTS: Participants who received CGC had significantly higher gait speed, less asymmetry, better gait control and more efficient gait patterns, more participants were able to walk and participants reported better mobility 4 and 12 months following the fracture as compared to participants receiving OC. CONCLUSIONS: Pre- and post-surgery CGC showed an effect on gait as long as 1 year after hip fracture. These findings underscore the importance of targeting the vulnerability of these patients at an early stage to prevent gait decline in the long run. As presently, most hip fracture patients are treated in orthopaedic wards with larger focus on the fracture than on frailty, these results are important to inform new models for hip fracture care.

Fall detection with body-worn sensors : a systematic review.

BACKGROUND AND AIMS: Falls among older people remain a major public health challenge. Body-worn sensors are needed to improve the understanding of the underlying mechanisms and kinematics of falls. The aim of this systematic review is to assemble, extract and critically discuss the information available in published studies, as well as the characteristics of these investigations (fall documentation and technical characteristics). METHODS: The searching of publically accessible electronic literature databases for articles on fall detection with body-worn sensors identified a collection of 96 records (33 journal articles, 60 conference proceedings and 3 project reports) published between 1998 and 2012. These publications were analysed by two independent expert reviewers. Information was extracted into a custom-built data form and processed using SPSS (SPSS Inc., Chicago, IL, USA). RESULTS: The main findings were the lack of agreement between the methodology and documentation protocols (study, fall reporting and technical characteristics) used in the studies, as well as a substantial lack of real-world fall recordings. A methodological pitfall identified in most articles was the lack of an established fall definition. The types of sensors and their technical specifications varied considerably between studies. CONCLUSION: Limited methodological agreement between sensor-based fall detection studies using body-worn sensors was identified. Published evidence-based support for commercially available fall detection devices is still lacking. A worldwide research group consensus is needed to address fundamental issues such as incident verification, the establishment of guidelines for fall reporting and the development of a common fall definition.

Development of a standard fall data format for signals from body-worn sensors : the FARSEEING consensus.

Objective measurement of real-world fall events by using body-worn sensor devices can improve the understanding of falls in older people and enable new technology to prevent, predict, and automatically recognize falls. However, these events are rare and hence challenging to capture. The FARSEEING (FAll Repository for the design of Smart and sElf-adapaive Environments prolonging INdependent livinG) consortium and associated partners strongly argue that a sufficient dataset of real-world falls can only be acquired through a collaboration of many research groups. Therefore, the major aim of the FARSEEING project is to build a meta-database of real-world falls. To establish this meta-database, standardization of data is necessary to make it possible to combine different sources for analysis and to guarantee data quality. A consensus process was started in January 2012 to propose a standard fall data format, involving 40 experts from different countries and different disciplines working in the field of fall recording and fall prevention. During a web-based Delphi process, possible variables to describe participants, falls, and fall signals were collected and rated by the experts. The summarized results were presented and finally discussed during a workshop at the 20th Conference of the International Society of Posture and Gait Research 2012, in Trondheim, Norway. The consensus includes recommendations for a fall definition, fall reporting (including fall reporting frequency, and fall reporting variables), a minimum clinical dataset, a sensor configuration, and variables to describe the signal characteristics.

Proposal for a multiphase fall model based on real-world fall recordings with body-fixed sensors.

Falls are by far the leading cause of fractures and accidents in the home environment. The current Cochrane reviews and other systematic reviews report on more than 200 intervention studies about fall prevention. A recent meta-analysis has summarized the most important risk factors of accidental falls. However, falls and fall-related injuries remain a major challenge. One novel approach to recognize, analyze, and work better toward preventing falls could be the differentiation of the fall event into separate phases. This might aid in reconsidering ways to design preventive efforts and diagnostic approaches. From a conceptual point of view, falls can be separated into a pre-fall phase, a falling phase, an impact phase, a resting phase, and a recovery phase. Patient and external observers are often unable to give detailed comments concerning these phases. With new technological developments, it is now at least partly possible to examine the phases of falls separately and to generate new hypotheses.The article describes the practicality and the limitations of this approach using body-fixed sensor technology. The features of the different phases are outlined with selected real-world fall signals.

Temporal and kinematic variables for real-world falls harvested from lumbar sensors in the elderly population.

Automatic fall detection will reduce the consequences of falls in the elderly and promote independent living, ensuring people can confidently live safely at home. Inertial sensor technology can distinguish falls from normal activities. However, <;7% of studies have used fall data recorded from elderly people in real life. The FARSEEING project has compiled a database of real life falls from elderly people, to gain new knowledge about fall events. We have extracted temporal and kinematic parameters to further improve the development of fall detection algorithms. A total of 100 real-world falls were analysed. Subjects with a known fall history were recruited, inertial sensors were attached to L5 and a fall report, following a fall, was used to extract the fall signal. This data-set was examined, and variables were extracted that include upper and lower impact peak values, posture angle change during the fall and time of occurrence. These extracted parameters, can be used to inform the design of fall-detection algorithms for real-world falls detection in the elderly.

Effect of physical exercise on muscle mass and strength in cancer patients during treatment--a systematic review.

Cancer treatment and its side effects may cause muscle wasting. Physical exercise has the potential to increase muscle mass and strength and to improve physical function in cancer patients undergoing treatment. A systematic review was conducted to study the effect of physical exercise (aerobic, resistance or a combination of both) on muscle mass and strength in cancer patients with different type and stage of cancer disease. Electronic searches were performed up to January 11th 2012, identifying 16 randomised controlled trials for final data synthesis. The studies demonstrated that aerobic and resistance exercise improves upper and lower body muscle strength more than usual care. Few studies have assessed the effect of exercise on muscle mass. Most studies were performed in patients with early stage breast or prostate cancer. Evidence on the effect of physical exercise on muscle strength and mass in cancer patients with advanced disease is lacking. More exercise studies in patients with advanced cancer and at risk of cancer cachexia are warranted.