The relationship between real world ambulatory activity and falls in incident Parkinson's disease: Influence of classification scheme

Translation, cross-cultural adaptation, and measurement properties of the Traditional Chinese version of the Fear of Falling Avoidance Behavior Questionnaire in Taiwanese community-dwelling adults

PURPOSE

This study aimed to translate the Fear of Falling Avoidance Behavior Questionnaire (FFABQ) into Traditional Chinese (FFABQ-TC) and to evaluate the psychometric properties of FFABQ-TC in Taiwanese adults.

METHODS

We translated and culturally adapted the FFABQ into Traditional Chinese, ensuring linguistic accuracy and cultural relevance. A total of 230 Taiwanese community-dwelling adults participated in the study. Test-retest reliability was assessed in 30 participants, while 200 participants were included in the validity analysis. Known-groups validity was investigated by comparing the FFABQ-TC scores between fallers and non-fallers. Convergent validity was examined by correlating FFABQ-TC scores with Activities-specific Balance Confidence Scale (ABC), Geriatric Fear of Falling Measure (GFFM), and Timed-Up-and-Go (TUG) test.

RESULTS

The FFABQ-TC demonstrated excellent test-retest reliability (Intraclass Correlation Coefficient = 0.884) and excellent internal consistency (Cronbach's alpha = 0.930). Known-groups analysis revealed that FFABQ-TC significantly differentiated between fallers and non-fallers. Convergent validity was examined and showed significant correlations of FFABQ-TC with the ABC, the GFFM, and TUG.

CONCLUSION

The psychometric properties of FFABQ-TC was established in Taiwanese adults for assessing FOF-related avoidance behaviors. The translated and adapted FFABQ-TC is a reliable and valid clinical tool for evaluating fall risk in this population.

Exploring Context Allows Us to Better Understand Physical Activity in People with and Without Parkinson's Who Have Fallen: A Mixed Methods Study

Background: Falls are a frequent and serious problem for older adults, especially for those living with Parkinson's. The relationship between falls and physical activity is complex, and people often restrict activity following a fall. Exercise is an important aspect of reducing further risk of a fall and a key component of the management of Parkinson's. The aim of this study was to understand the types of activity they are engaged in, the environments in which they take place, and the experience of people with and without Parkinson's who have fallen. Method: Seventeen people with Parkinson's and thirteen older adults who had experienced at least one fall in the previous year were recruited to this mixed methods study. Activity levels were captured over one week using accelerometers and body-worn cameras, allowing the type and location of activity to be recorded and analysed. This information informed an interview. Results: Findings showed that although both groups often achieved up to 10,000 steps per day, this was in very short bouts of activity. Sedentary activity, such as watching television, dominated the findings. Participants were aware of the benefits of being active but described many barriers to achieving the level of activity they would like to.

Vascular disease and risk of fall-related injuries in Parkinson's disease: A nationwide cohort study in Sweden

INTRODUCTION

Parkinson's disease (PD) patients are prone to fall and fall-related injuries (FI). Vascular disease is common in PD and is positively associated with falls in elderly. We aimed to evaluate the association of vascular disease with FI risk in PD.

METHODS

A nationwide cohort study of patients with primary PD diagnosis in Sweden was performed using Swedish national registers. Patients with and without vascular disease were followed from PD diagnosis until subsequent FI or 2013-12-31. The association of vascular disease with FI risk was estimated as hazard ratio (HR) and 95 % confidence interval (CI) by Cox regression using attained age as underlying timescale.

RESULTS

We identified 2734 and 6979 incident FI from 8025 PD patients with and 20,543 without vascular disease, respectively. Overall, vascular disease associated positively with subsequent FI, which was mainly driven by the significant risk elevation within the first 6 months following vascular disease (HR < 0.5year [95 % CI] for PD diagnosed ≤75 years is 1.61 [1.39-1.87] and for PD diagnosed >75 years is 1.48 [1.32-1.65]). Thereafter, the association attenuated to null before it rebounded five years after exposure in PD diagnosed ≤75 years (HR > 5year = 1.26, 95 % CI: 1.10-1.45); whereas for PD diagnosed >75 years, it dropped remarkably and remained non-significant 6 months after exposure. When vascular disease was restricted to stroke, we saw a similar temporal pattern except that the short-term HRs among younger patients were stronger, lasted longer, and declined continuously without rebound.

CONCLUSIONS

Fall prevention is crucial to PD patients immediately after a vascular event.

Use of a Robotic Walking Device for Home and Community Mobility in Parkinson Disease: A Randomized Controlled Trial

BACKGROUND/PURPOSE

Gait impairments in Parkinson disease (PD) contribute to decreased quality of life. This randomized controlled trial examined immediate- and longer-term effects of a single joint robotic exoskeleton device (EXOD), the Honda Walking Assist device, on gait.

METHODS

Participants (n = 45) with PD (Hoehn and Yahr stages 1-3) were randomized to a robotic-assisted gait training (RAGT) group (n = 23) or control (CON) group (n = 22). The RAGT group was tested with and without the EXOD at baseline and then received supervised in-home and community training with the EXOD twice weekly for 8 weeks. The CON group received no interventions. Outcome measures included gait speed (primary), gait endurance (6-minute walk test), perceived ease of walking, and questionnaires and logs assessing performance of daily activities, freezing of gait, and daily activity levels.

RESULTS

Forty participants completed the study. No significant immediate impact of EXOD usage on participants' gait measures was found. Differences in gait speed and secondary outcome measures postintervention were not significantly different between the RAGT and CON groups. Participants with greater disease severity (worse baseline motor scores) had greater improvements in stride length during unassisted walking after the intervention than those with lower severity (mean difference: 3.22, 95% confidence interval: 0.05-6.40; P = 0.04).

DISCUSSION AND CONCLUSIONS

All RAGT participants could use the EXOD safely. The RAGT treatment used in this mostly low impairment population of people with PD may be ineffective and/or was insufficiently dosed to see a positive treatment effect. Our findings suggest that RAGT interventions in PD may be more effective in individuals with greater motor impairments.

Fall experiences from the perspectives of people with osteoarthritis: in their own words

PURPOSE

To explore real-life experiences of people with osteoarthritis (OA) to increase understanding of how they perceive contributing factors to falls, circumstances at time of falls, and consequences of falls.

MATERIALS AND METHODS

Four focus groups of 3-7 people with OA from the Chicago, IL, USA, and neighboring areas were conducted remotely via web-based videoconferencing. Inclusion criteria included history of falls in previous 12 months and hip and/or knee OA. Focus group transcripts were coded and analyzed using a modified grounded theory approach to identify themes.

RESULTS

Focus group participants (n = 17) described experiences associated with fall-related events that resulted in the identification of four themes: (1) perception of falls and fall risks can be influenced by OA symptoms, (2) ability to remember circumstances of falls are influenced by consequences, (3) behaviors and attitudes that address OA symptoms and avoidance of falls are similar and (4) OA symptoms and falls have common psychological impacts on lives.

CONCLUSION

Our study highlights how people with OA define falls, perceive contributing factors to falls, and describe general and OA-related factors that contributed to their fall experiences. The shared experiences contributed to the creation of themes that represented various aspects of the circumstances and impact of falls. Consideration for the identified themes may enhance recording and reporting of falls, contribute to development of improved fall risk assessment tools, and prioritize research into the biopsychosocial effects of falls in people with OA.IMPLICATIONS FOR REHABILITATIONInformation about circumstances of a fall such as location, activity, and symptoms of osteoarthritis may be beneficial in creating tailored fall prevention training and education.Falls are a common problem for people with lower limb osteoarthritis that can lead to negative changes in activity and quality of life.The psychological impact of osteoarthritis symptoms may be contributing to fear of falling and decrease participation in daily activities.Awareness of the perceptions people with osteoarthritis have about their symptoms may provide educational and training opportunities to address the benefits of different therapeutic treatments.Awareness of perceptions people with osteoarthritis have about their risk of falling may provide educational and training opportunities to address the benefits of different therapeutic treatments.

Efficacy of Specific Trunk Exercises in the Balance Dysfunction of Patients with Parkinson's Disease: A Systematic Review and Meta-Analysis

Parkinson's disease (PD) is a neurodegenerative pathology classified as a movement disorder. Physical exercise within a physiotherapy program is an important element to improve postural stability, balance and mobility in order to reduce falls in people with PD. The aim of this work was to determine the efficacy of specific balance and trunk mobility exercises, as well as their benefits for and effects on patients with idiopathic PD. A systematic review and meta-analysis was conducted according to PRISMA standards. The search was performed in five databases: Cochrane Library, SciELO, PEDro, Scopus and PubMed, in February 2022 with the following descriptors: Parkinson's disease, trunk, exercise, therapy and physical therapy. The inclusion criteria were randomized controlled trials (RCTs) over the last ten years. A meta-analysis on static and dynamic balance was conducted with the software Review Manager. Nine articles met the objectives and inclusion criteria, with a total of 240 participants. The trials had moderate methodological quality according to the PEDro scale. The studies included differed with regard to intervention protocol and outcome measures. Finally, eight studies were included in a quantitative analysis in which it was shown that trunk-specific exercises interventions did not significantly improve static balance (SMD = -0.10, 95% CI = -0.29, 0.08; p = 0.28) or dynamic balance (SMD = 0.64 95% CI = -0.24, 1.52; p = 0.15). However, significant differences were found in static balance measured subjectively using the Berg Balance Scale (SMD = -0.52, 95% CI = -1.01, -0.02; p = 0.04). Although some differences were not significant, the studies included in this systematic review consider that specific trunk exercises or balance training combined with muscle strengthening in patients with idiopathic PD should be a complement to pharmacological treatment for improving balance dysfunction and postural instability, preventing falls and promoting wellness.

Enhancing Free-Living Fall Risk Assessment: Contextualizing Mobility Based IMU Data

Fall risk assessment needs contemporary approaches based on habitual data. Currently, inertial measurement unit (IMU)-based wearables are used to inform free-living spatio-temporal gait characteristics to inform mobility assessment. Typically, a fluctuation of those characteristics will infer an increased fall risk. However, current approaches with IMUs alone remain limited, as there are no contextual data to comprehensively determine if underlying mechanistic (intrinsic) or environmental (extrinsic) factors impact mobility and, therefore, fall risk. Here, a case study is used to explore and discuss how contemporary video-based wearables could be used to supplement arising mobility-based IMU gait data to better inform habitual fall risk assessment. A single stroke survivor was recruited, and he conducted a series of mobility tasks in a lab and beyond while wearing video-based glasses and a single IMU. The latter generated topical gait characteristics that were discussed according to current research practices. Although current IMU-based approaches are beginning to provide habitual data, they remain limited. Given the plethora of extrinsic factors that may influence mobility-based gait, there is a need to corroborate IMUs with video data to comprehensively inform fall risk assessment. Use of artificial intelligence (AI)-based computer vision approaches could drastically aid the processing of video data in a timely and ethical manner. Many off-the-shelf AI tools exist to aid this current need and provide a means to automate contextual analysis to better inform mobility from IMU gait data for an individualized and contemporary approach to habitual fall risk assessment.

Multimodal Mobility Assessment Predicts Fall Frequency and Severity in Cerebellar Ataxia

This cohort study aims to evaluate the predictive validity of multimodal clinical assessment and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with cerebellar ataxia (CA).Occurrence, severity, and consequences of falling were prospectively assessed for 6 months in 93 patients with hereditary (N = 36) and sporadic or secondary (N = 57) forms of CA and 63 healthy controls. Participants completed a multimodal clinical and functional fall risk assessment, in-laboratory gait examination, and a 2-week inertial sensor-based daily mobility monitoring. Multivariate logistic regression analyses were performed to evaluate the predictive capacity of all clinical and in- and off-laboratory mobility measures with respect to fall (1) status (non-faller vs. faller), (2) frequency (occasional vs. frequent falls), and (3) severity (benign vs. injurious fall) of patients. 64% of patients experienced one or recurrent falls and 65% of these severe fall-related injuries during prospective assessment. Mobility impairments in patients corresponded to a mild-to-moderate ataxic gait disorder. Patients' fall status and frequency could be reliably predicted (78% and 81% accuracy, respectively), primarily based on their retrospective fall status. Clinical scoring of ataxic symptoms and in- and off-laboratory gait and mobility measures improved classification and provided unique information for the prediction of fall severity (84% accuracy).These results encourage a stepwise approach for fall risk assessment in patients with CA: fall history-taking readily and reliably informs the clinician about patients' general fall risk. Clinical scoring and instrument-based mobility measures provide further in-depth information on the risk of recurrent and injurious falling.

Predictors of Falls with Injuries in People with Parkinson's Disease

Background

Falls are frequent in Parkinson's disease (PD), but there is lack of information about predictors of injurious falls.

Objectives

To determine predictors of falls with injuries in people with PD; to compare circumstances and consequences of falls in single and recurrent fallers.

Methods

Participants (n = 225) were assessed by disease-specific, self-report, and balance measures, and followed-up for 12 months with a diary to record falls, their circumstances, and injuries. Univariate and multivariate analyses were performed. Circumstances and consequences of falls presented by single and recurrent fallers were compared.

Results

A total of 805 falls were analyzed, 107 (13%) were falls with injuries. Multivariate logistic regression model revealed that greater PD duration and higher balance confidence were protective factors; better balance during gait, outdoor falls, and falls related to extrinsic factors were risk factors for falls with injuries, when compared to falls with no injuries. Multivariate multinomial regression model revealed that, when compared to zero fall, past falls and daily levodopa equivalent dose were predictors of falls with injuries; these predictors together with disability were predictors of falls with no injuries. Single falls (n = 27; 3%) were more common outdoors because of extrinsic factors, whereas recurrent falls (n = 778; 97%) were more common indoors because of intrinsic factors. Single falls led to more injuries than recurrent falls (P < 0.05).

Conclusions

Different predictors of falls with injuries were obtained when different outcomes were compared. It should be noted that falls with injuries might be influenced by fall-related activities and environmental factors. Single and recurrent falls differed on circumstances and consequences.

Axial impairment and falls in Parkinson’s disease: 15 years of subthalamic deep brain stimulation

In this retrospective study, we longitudinally analyzed axial impairment and falls in people with Parkinson’s disease (PD) and subthalamic nucleus deep brain stimulation (STN-DBS). Axial scores and falling frequency were examined at baseline, and 1, 10, and 15 years after surgery. Preoperative demographic and clinical data, including PD duration and severity, phenotype, motor and cognitive scales, medications, and vascular changes on neuroimaging were examined as possible risk factors through Kaplan–Meier and Cox regression analyses. Of 302 individuals examined before and at 1 year after surgery, 102 and 57 were available also at 10 and 15 years of follow-up, respectively. Axial scores were similar at baseline and at 1 year but worsened at 10 and 15 years. The prevalence rate of frequent fallers progressively increased from baseline to 15 years. Preoperative axial scores, frontal dysfunction and age at PD onset were risk factors for axial impairment progression after surgery. Axial scores, akinetic/rigid phenotype, age at disease onset and disease duration at surgery predicted frequent falls. Overall, axial signs progressively worsened over the long-term period following STN-DBS, likely related to the progression of PD, especially in a subgroup of subjects with specific risk factors.

Interventions for preventing falls in Parkinson's disease

BACKGROUND

Most people with Parkinson's disease (PD) experience at least one fall during the course of their disease. Several interventions designed to reduce falls have been studied. An up-to-date synthesis of evidence for interventions to reduce falls in people with PD will assist with informed decisions regarding fall-prevention interventions for people with PD.

OBJECTIVES

To assess the effects of interventions designed to reduce falls in people with PD.

SEARCH METHODS

CENTRAL, MEDLINE, Embase, four other databases and two trials registers were searched on 16 July 2020, together with reference checking, citation searching and contact with study authors to identify additional studies. We also conducted a top-up search on 13 October 2021.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) of interventions that aimed to reduce falls in people with PD and reported the effect on falls. We excluded interventions that aimed to reduce falls due to syncope.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane Review procedures. Primary outcomes were rate of falls and number of people who fell at least once. Secondary outcomes were the number of people sustaining one or more fall-related fractures, quality of life, adverse events and economic outcomes. The certainty of the evidence was assessed using GRADE.

MAIN RESULTS

This review includes 32 studies with 3370 participants randomised. We included 25 studies of exercise interventions (2700 participants), three studies of medication interventions (242 participants), one study of fall-prevention education (53 participants) and three studies of exercise plus education (375 participants). Overall, participants in the exercise trials and the exercise plus education trials had mild to moderate PD, while participants in the medication trials included those with more advanced disease. All studies had a high or unclear risk of bias in one or more items. Illustrative risks demonstrating the absolute impact of each intervention are presented in the summary of findings tables. Twelve studies compared exercise (all types) with a control intervention (an intervention not thought to reduce falls, such as usual care or sham exercise) in people with mild to moderate PD. Exercise probably reduces the rate of falls by 26% (rate ratio (RaR) 0.74, 95% confidence interval (CI) 0.63 to 0.87; 1456 participants, 12 studies; moderate-certainty evidence). Exercise probably slightly reduces the number of people experiencing one or more falls by 10% (risk ratio (RR) 0.90, 95% CI 0.80 to 1.00; 932 participants, 9 studies; moderate-certainty evidence).  We are uncertain whether exercise makes little or no difference to the number of people experiencing one or more fall-related fractures (RR 0.57, 95% CI 0.28 to 1.17; 989 participants, 5 studies; very low-certainty evidence). Exercise may slightly improve health-related quality of life immediately following the intervention (standardised mean difference (SMD) -0.17, 95% CI -0.36 to 0.01; 951 participants, 5 studies; low-certainty evidence). We are uncertain whether exercise has an effect on adverse events or whether exercise is a cost-effective intervention for fall prevention. Three studies trialled a cholinesterase inhibitor (rivastigmine or donepezil). Cholinesterase inhibitors may reduce the rate of falls by 50% (RaR 0.50, 95% CI 0.44 to 0.58; 229 participants, 3 studies; low-certainty evidence). However, we are uncertain if this medication makes little or no difference to the number of people experiencing one or more falls (RR 1.01, 95% CI 0.90 to 1.14230 participants, 3 studies) and to health-related quality of life (EQ5D Thermometer mean difference (MD) 3.00, 95% CI -3.06 to 9.06; very low-certainty evidence). Cholinesterase inhibitors may increase the rate of non fall-related adverse events by 60% (RaR 1.60, 95% CI 1.28 to 2.01; 175 participants, 2 studies; low-certainty evidence). Most adverse events were mild and transient in nature.  No data was available regarding the cost-effectiveness of medication for fall prevention. We are uncertain of the effect of education compared to a control intervention on the number of people who fell at least once (RR 10.89, 95% CI 1.26 to 94.03; 53 participants, 1 study; very low-certainty evidence), and no data were available for the other outcomes of interest for this comparisonWe are also uncertain (very low-certainty evidence) whether exercise combined with education makes little or no difference to the number of falls (RaR 0.46, 95% CI 0.12 to 1.85; 320 participants, 2 studies), the number of people sustaining fall-related fractures (RR 1.45, 95% CI 0.40 to 5.32,320 participants, 2 studies), or health-related quality of life (PDQ39 MD 0.05, 95% CI -3.12 to 3.23, 305 participants, 2 studies). Exercise plus education may make little or no difference to the number of people experiencing one or more falls (RR 0.89, 95% CI 0.75 to 1.07; 352 participants, 3 studies; low-certainty evidence). We are uncertain whether exercise combined with education has an effect on adverse events or is a cost-effective intervention for fall prevention.  AUTHORS' CONCLUSIONS: Exercise interventions probably reduce the rate of falls, and probably slightly reduce the number of people falling in people with mild to moderate PD.  Cholinesterase inhibitors may reduce the rate of falls, but we are uncertain if they have an effect on the number of people falling. The decision to use these medications needs to be balanced against the risk of non fall-related adverse events, though these adverse events were predominantly mild or transient in nature. Further research in the form of large, high-quality RCTs are required to determine the relative impact of different types of exercise and different levels of supervision on falls, and how this could be influenced by disease severity. Further work is also needed to increase the certainty of the effects of medication and further explore falls prevention education interventions both delivered alone and in combination with exercise.

A theoretical framework for addressing fear of falling avoidance behavior in Parkinson's disease

Postural instability in Parkinson's disease (PD) is associated with several downstream consequences that ultimately lead to a greater risk of falling. Among the prominent downstream consequences is fear of falling (FOF), which is both common and problematic in PD. It can lead to a vicious cycle of FOF avoidance behavior that results in more sedentary behavior, physical deconditioning, and weakening of already impaired balance systems. This, in turn, may make the person with PD more susceptible to a future fall even with benign daily tasks. While FOF activity avoidance can be adaptive (appropriate), it can also be maladaptive (inappropriate or exaggerated). When this adaptive and maladaptive FOF avoidance behavior is contextualized to gait/balance performance, it provides a theoretical framework that can be used by clinicians to match patterns of behavior to a concordant treatment approach. In the theoretical framework proposed in this perspective, four different patterns related to FOF avoidance behavior and gait/balance performance are suggested: appropriate avoiders, appropriate non-avoiders, inappropriate avoiders, and inappropriate non-avoiders. For each of the four FOF avoidance behavior patterns, this paper also provides suggested treatment focuses, approaches and recommendations.

Associations of objectively measured physical activity and sedentary behaviour with fall-related outcomes in older adults: a systematic review

BACKGROUND

Higher physical activity (PA) and lower sedentary behaviour (SB) are associated with better muscle strength, balance, and functional ability, which are imperative for avoiding falls. This systematic review aimed to describe the association between objectively measured PA and SB with falls, fear of falling, and fractures.

METHODS

Six databases were searched from inception to July 21, 2020 for articles reporting the association of objectively measured PA/SB with falls, fear of falling, and/or fractures in community-dwelling older adults ≥60 years old. Results were synthesized in effect-direction heat maps and albatross plots expressed as Pearson's correlation coefficients (R).

RESULTS

A total of 43 articles were included, representing 27,629 (range 26 to 5,545) community-dwelling older adults (mean [SD] age 76.6 [8.4] years, 47% female). Longitudinal associations were reported in 13 articles and cross-sectional associations in 30. Falls were reported in 11 articles, fear of falling in 18 and fractures in 2. Higher PA and lower SB were associated with less fear of falling (median [interquartile range] Rs = steps: -0.214 [0.249; -0.148], total PA: -0.240 [0.267; -0.144], and moderate-to-vigorous PA: -0.180 [0.382; -0.121]), but these associations did not extend to falls or fractures, which showed inconsistent effect directions.

CONCLUSION

Fear of falling is associated with less engagement in PA and more SB, thus indicating that it is a psychological barrier to an active lifestyle. Varying effect directions for associations between PA and SB with falls and fractures may provide evidence for non-linear associations and require further research considering details of the fall or fracture incident.

PROSPERO REGISTRATION NUMBER

CRD42018103910.

Fall prediction in neurological gait disorders: differential contributions from clinical assessment, gait analysis, and daily-life mobility monitoring

Objective

To evaluate the predictive validity of multimodal clinical assessment outcomes and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with different forms of neurological gait disorders.

Methods

The occurrence, severity, and consequences of falls were prospectively assessed for 6 months in 333 patients with early stage gait disorders due to vestibular, cerebellar, hypokinetic, vascular, functional, or other neurological diseases and 63 healthy controls. At inclusion, participants completed a comprehensive multimodal clinical and functional fall-risk assessment, an in-laboratory gait examination, and an inertial-sensor-based daily mobility monitoring for 14 days. Multivariate logistic regression analyses were performed to identify explanatory characteristics for predicting the (1) the fall status (non-faller vs. faller), (2) the fall frequency (occasional vs. frequent falls), and (3) the fall severity (benign vs. injurious fall) of patients.

Results

40% of patients experienced one or frequent falls and 21% severe fall-related injuries during prospective fall assessment. Fall status and frequency could be reliably predicted (accuracy of 78 and 91%, respectively) primarily based on patients' retrospective fall status. Instrumented-based gait and mobility measures further improved prediction and provided independent, unique information for predicting the severity of fall-related consequences.

Interpretation

Falls- and fall-related injuries are a relevant health problem already in early stage neurological gait disorders. Multivariate regression analysis encourages a stepwise approach for fall assessment in these patients: fall history taking readily informs the clinician about patients' general fall risk. In patients at risk of falling, instrument-based measures of gait and mobility provide critical information on the likelihood of severe fall-related injuries.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10504-x.

Fall risk assessment in the wild: A critical examination of wearable sensor use in free-living conditions

BACKGROUND

Despite advances in laboratory-based supervised fall risk assessment methods (FRAs), falls still remain a major public health problem. This can be due to the alteration of behavior in laboratory due to the awareness of being observed (i.e., Hawthorne effect), the multifactorial complex etiology of falls, and our limited understanding of human behaviour in natural environments, or in the' wild'. To address these imitations, a growing body of literature has focused on free-living wearable-sensor-based FRAs. The objective of this narrative literature review is to discuss papers investigating natural data collected by wearable sensors for a duration of at least 24 h to identify fall-prone older adults.

METHODS

Databases (Scopus, PubMed and Google Scholar) were searched for studies based on a rigorous search strategy.

RESULTS

Twenty-four journal papers were selected, in which inertial sensors were the only wearable system employed for FRA in the wild. Gait was the most-investigated activity; but sitting, standing, lying, transitions and gait events, such as turns and missteps, were also explored. A multitude of free-living fall predictors (FLFPs), e.g., the quantity of daily steps, were extracted from activity bouts and events. FLFPs were further categorized into discrete domains (e.g., pace, complexity) defined by conceptual or data-driven models. Heterogeneity was found within the reviewed studies, which includes variance in: terminology (e.g., quantity vs macro), hyperparameters to define/estimate FLFPs, models and domains, and data processing approaches (e.g., the cut-off thresholds to define an ambulatory bout). These inconsistencies led to different results for similar FLFPs, limiting the ability to interpret and compare the evidence.

CONCLUSION

Free-living FRA is a promising avenue for fall prevention. Achieving a harmonized model is necessary to systematically address the inconsistencies in the field and identify FLFPs with the highest predictive values for falls to eventually address intervention programs and fall prevention.

Integrating Technology Into Clinical Practice for the Assessment of Balance and Mobility: Perspectives of Exercise Professionals Practicing in Retirement and Long-term Care

Objective

To explore exercise professionals’ perspectives on technology integration for balance and mobility assessment practices in retirement and long-term care.

Setting

A private residential care organization in Ontario, Canada, with 18 sites providing accommodation and services for older adults.

Design

A qualitative descriptive approach was used including semistructured focus group interviews. Open-ended questions explored perceptions of technology integration along with factors influencing its adoption. Analysis involved preliminary coding based on research questions, review and discussion of emerging themes, and final, resultant coding for each category.

Participants

Exercise professionals (kinesiologists and exercise therapists) (N=18).

Interventions

Not applicable.

Main Outcome Measures

Not applicable.

Results

All participants felt that technology could enhance their practice by supporting programming, communication, and/or information management. Potential barriers to technology integration related primarily to the need to accommodate the broad range of complex health conditions present among clients, which would impact (1) their ability to engage with the technology and (2) relevance of technology-derived outcomes. Specific concerns related to individuals with significant cognitive and/or functional impairment. Solutions to these barriers emphasized the need for flexible technology and appropriate normative data to maximize the potential for uptake.

Conclusions

The participating exercise professionals working in a retirement and long-term care setting saw technology as a potentially effective addition to current clinical practice. To increase the likelihood for clinical uptake, technology must be maximize flexibility in order to accommodate a wide range of physical and cognitive abilities and meet specific needs related to setting and job responsibilities. The findings emphasize the need for continuous dialogue between technology producers and end users for successful development and implementation.

Falls Risk in Relation to Activity Exposure in High-Risk Older Adults

Background

Physical activity is linked to many positive health outcomes, stimulating the development of exercise programs. However, many falls occur while walking and so promoting activity might paradoxically increase fall rates, causing injuries, and worse quality of life. The relationship between activity exposure and fall rates remains unclear. We investigated the relationship between walking activity (exposure to risk) and fall rates before and after an exercise program (V-TIME).

Methods

One hundred and nine older fallers, 38 fallers with mild cognitive impairment (MCI), and 128 fallers with Parkinson’s disease (PD) were randomly assigned to one of two active interventions: treadmill training only or treadmill training combined with a virtual reality component. Participants were tested before and after the interventions. Free-living walking activity was characterized by volume, pattern, and variability of ambulatory bouts using an accelerometer positioned on the lower back for 1 week. To evaluate that relationship between fall risk and activity, a normalized index was determined expressing fall rates relative to activity exposure (FRA index), with higher scores indicating a higher risk of falls per steps taken.

Results

At baseline, the FRA index was higher for fallers with PD compared to those with MCI and older fallers. Walking activity did not change after the intervention for the groups but the FRA index decreased significantly for all groups (p ≤ .035).

Conclusions

This work showed that V-TIME interventions reduced falls risk without concurrent change in walking activity. We recommend using the FRA index in future fall prevention studies to better understand the nature of intervention programs.

Do kinematic gait parameters help to discriminate between fallers and non-fallers with Parkinson's disease?

OBJECTIVE

Although a number of clinical factors have been linked to falls in Parkinson's disease (PD), the diagnostic value of gait parameters remains subject to debate. The objective of this retrospective study was to determine to what extent the combination of gait parameters with clinical characteristics can distinguish between fallers and non-fallers.

METHODS

Using a video motion system, we recorded gait in 174 patients with PD. The patients' clinical characteristics (including motor status, cognitive status, disease duration, dopaminergic treatment and any history of falls or freezing of gait) were noted. The considered kinematic gait parameters included indices of gait bradykinesia and hypokinesia, asymmetry, variability, and foot clearance. After a parameters selection using an ANCOVA analysis, support vector machine algorithm was used to build classification models for distinguishing between fallers and non-fallers. Two models were built, the first included clinical data only while the second incorporated the selected gait parameters.

RESULTS

The "clinical-only" model had an accuracy of 94% for distinguishing between fallers and non-fallers. The model incorporating additional gait parameters including stride time and foot clearance performed even better, with an accuracy of up to 97%.

CONCLUSION

Although fallers differed significantly from non-fallers with regard to disease duration, motor impairment or dopaminergic treatment, the addition of gait parameters such as foot clearance or stride time to clinical variables increased the model's discriminant power.

SIGNIFICANCE

This predictive model now needs to be validated in prospective cohorts.

Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders

Falls are the leading cause of mortality, morbidity and poor quality of life in older adults with or without neurological conditions. Applying machine learning (ML) models to gait analysis outcomes offers the opportunity to identify individuals at risk of future falls. The aim of this study was to determine the effect of different data pre-processing methods on the performance of ML models to classify neurological patients who have fallen from those who have not for future fall risk assessment. Gait was assessed using wearables in clinic while walking 20 m at a self-selected comfortable pace in 349 (159 fallers, 190 non-fallers) neurological patients. Six different ML models were trained on data pre-processed with three techniques such as standardisation, principal component analysis (PCA) and path signature method. Fallers walked more slowly, with shorter strides and longer stride duration compared to non-fallers. Overall, model accuracy ranged between 48% and 98% with 43-99% sensitivity and 48-98% specificity. A random forest (RF) classifier trained on data pre-processed with the path signature method gave optimal classification accuracy of 98% with 99% sensitivity and 98% specificity. Data pre-processing directly influences the accuracy of ML models for the accurate classification of fallers. Using gait analysis with trained ML models can act as a tool for the proactive assessment of fall risk and support clinical decision-making.

Independent domains of daily mobility in patients with neurological gait disorders

The aim of this study was to establish a comprehensive and yet parsimonious model of daily mobility activity in patients with neurological gait disorders. Patients (N = 240) with early-stage neurological (peripheral vestibular, cerebellar, hypokinetic, vascular or functional) gait disorders and healthy controls (N = 35) were clinically assessed with standardized scores related to functional mobility, balance confidence, quality of life, cognitive function, and fall history. Subsequently, daily mobility was recorded for 14 days by means of a body-worn inertial sensor (ActivPAL^®). Fourteen mobility measures derived from ActivPAL recordings were submitted to principle component analysis (PCA). Group differences within each factor obtained from PCA were analyzed and hierarchical regression analysis was performed to identify predictive characteristics from clinical assessment for each factor. PCA yielded five significant orthogonal factors (i.e., mobility domains) accounting for 92.3% of the total variance from inertial-sensor-recordings: ambulatory volume (38.7%), ambulatory pattern (22.3%), postural transitions (13.3%), sedentary volume (10.8%), and sedentary pattern (7.2%). Patients' mobility performance only exhibited reduced scores in the ambulatory volume domain but near-to-normal scores in all remaining domains. Demographic characteristics, clinical scores, and fall history were differentially associated with each domain explaining 19.2–10.2% of their total variance. This study supports a low-dimensional five-domain model for daily mobility behavior in patients with neurological gait disorders that may facilitate monitoring the course of disease or therapeutic intervention effects in ecologically valid and clinically relevant contexts. Further studies are required to explore the determinants that may explain performance differences of patients within each of these domains and to examine the consequences of altered mobility behavior with respect to patients' risk of falling and quality of life.

Detection of Gait From Continuous Inertial Sensor Data Using Harmonic Frequencies

Mobile gait analysis using wearable inertial measurement units (IMUs) provides valuable insights for the assessment of movement impairments in different neurological and musculoskeletal diseases, for example Parkinson's disease (PD). The increase in data volume due to arising long-term monitoring requires valid, robust and efficient analysis pipelines. In many studies an upstream detection of gait is therefore applied. However, current methods do not provide a robust way to successfully reject non-gait signals. Therefore, we developed a novel algorithm for the detection of gait from continuous inertial data of sensors worn at the feet. The algorithm is focused not only on a high sensitivity but also a high specificity for gait. Sliding windows of IMU signals recorded from the feet of PD patients were processed in the frequency domain. Gait was detected if the frequency spectrum contained specific patterns of harmonic frequencies. The approach was trained and evaluated on 150 clinical measurements containing standardized gait and cyclic movement tests. The detection reached a sensitivity of 0.98 and a specificity of 0.96 for the best sensor configuration (angular rate around the medio-lateral axis). On an independent validation data set including 203 unsupervised, semi-standardized gait tests, the algorithm achieved a sensitivity of 0.97. Our algorithm for the detection of gait from continuous IMU signals works reliably and showed promising results for the application in the context of free-living and non-standardized monitoring scenarios.

Fall Risk in Relation to Individual Physical Activity Exposure in Patients with Different Neurodegenerative Diseases: a Pilot Study

Falls in patients with neurodegenerative diseases (NDDs) have enormous detrimental consequences. A better understanding of the interplay between physical activity (PA) and fall risk might help to reduce fall frequency. We aimed to investigate the association between sensor-based PA and fall risk in NDDs, using "falls per individual PA exposure time" as a novel measure. Eighty-eight subjects (n = 31 degenerative ataxia (DA), n = 14 Parkinson's disease (PD), n = 12 progressive supranuclear palsy (PSP) and 31 healthy controls) were included in this pilot study. PA was recorded in free-living environments with three-axial accelerometers (activPAL™) over 7 days. Falls were prospectively assessed over 12 months. Fall incidence was calculated by (i) absolute number of falls per person years (py) and (ii) falls per exposure to individual PA. Absolute fall incidence was high in all three NDDs, with differing levels (DA, 9 falls/py; PD, 14 falls/py; PSP, 29 falls/py). Providing a more fine-grained view on fall risk, correction for individual exposure to PA revealed that measures of low walking PA were associated with higher fall incidence in all three NDDs. Additionally, higher fall incidence was associated with more sit-to-stand transfers in PD and longer walking bouts in PSP. Our results suggest that low walking PA is a risk factor for falls in DA, PD and PSP, indicating the potential benefit of increasing individual PA in these NDDs to reduce fall risk. Moreover, they show that correction for individual exposure to PA yields a more differentiated view on fall risk within and across NDDs.

Falls in persons with Parkinson's disease: Do non-motor symptoms matter as much as motor symptoms?

ABSTRACT Falls are common among persons with Parkinson's disease (PD). On the other hand, predicting falls is complex as there are both generic and PD-specific contributors. In particular, the role of non-motor symptoms has been less studied. Objective: The objective of this study was to identify the role of non-motor predictors of falling in persons with PD (PwP). Methods: A cross-sectional study was carried out in PwP recruited from a movement disorders clinic. Clinical and demographical data were collected. All PwP were assessed using the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and the Non-Motor Symptoms Scale (NMSS). Variables were assessed at the bivariate level. Significant variables were put into a logistic regression model. Results: A total of 179 PwP were included. Overall, 16.8% of PwP had fallen in the past 12 months, with 53.3% of them being recurrent fallers. The mean number of monthly falls was 2.5 ± 3.3. Factors associated with falling in the bivariate analysis included the disease duration, Hoehn and Yahr stage, MDS-UPDRS part I and II, postural instability/gait disturbance (PIGD) subtype, NMSS urinary domain, NMSS miscellaneous domain, and non-motor severity burden (all p-values < 0.05). After multivariate analysis, only the disease duration (p = 0.03) and PIGD (p = 0.03) remained as independent risk factors. Conclusion: Disease duration and the PIGD subtype were identified as relevant risk factors for falls in PwP Non-motor symptoms appear to have a less important role as risk factors for falls.

Falls in Synucleinopathies

Parkinson's disease (PD) and other synucleinopathies, namely dementia with Lewy bodies (DLB) and multiple system atrophy (MSA), are common degenerative neurological disorders that share synuclein pathology. Although certain cardinal features of parkinsonism, including bradykinesia and rigidity, respond well to levodopa, axial features, such as gait and balance impairment, are less reliably responsive to dopaminergic therapy and surgical interventions. Consequently, falls are common in PD and other synucleinopathies and are a major contributor toward injury and loss of independence. This underscores the need for appropriate fall risk assessment and implementation of preventative measures in all patients with parkinsonism. The aim of this review is therefore to explore modifiable and non-modifiable risk factors for falls in synucleinopathies. We next review and evaluate the evidence for pharmacological, nonpharmacological, and surgical approaches for fall prevention, and emphasize individualized and multifaceted approaches.

Home-based monitoring of falls using wearable sensors in Parkinson's disease

INTRODUCTION

Falling is among the most serious clinical problems in Parkinson's disease (PD). We used body-worn sensors (falls detector worn as a necklace) to quantify the hazard ratio of falls in PD patients in real life.

METHODS

We matched all 2063 elderly individuals with self-reported PD to 2063 elderly individuals without PD based on age, gender, comorbidity, and living conditions. We analyzed fall events collected at home via a wearable sensor. Fall events were collected either automatically using the wearable falls detector or were registered by a button push on the same device. We extracted fall events from a 2.5-year window, with an average follow-up of 1.1 years. All falls included were confirmed immediately by a subsequent telephone call. The outcomes evaluated were (1) incidence rate of any fall, (2) incidence rate of a new fall after enrollment (ie, hazard ratio), and (3) 1-year cumulative incidence of falling.

RESULTS

The incidence rate of any fall was higher among self-reported PD patients than controls (2.1 vs. 0.7 falls/person, respectively; P < .0001). The incidence rate of a new fall after enrollment (ie, hazard ratio) was 1.8 times higher for self-reported PD patients than controls (95% confidence interval, 1.6-2.0).

CONCLUSION

Having PD nearly doubles the incidence of falling in real life. These findings highlight PD as a prime "falling disease." The results also point to the feasibility of using body-worn sensors to monitor falls in daily life. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

A Pilot Study to Test the Feasibility of a Home Mobility Monitoring System in Community-Dwelling Older Adults

Technology enables home-based personalized care through continuous, automated, real-time monitoring of a participant's health condition and remote communication between health care providers and participants. Technology has been implemented in a variety of nursing practices. However, little is known about the use of home mobility monitoring systems in visiting nursing practice. Therefore, the current study tested the feasibility of a home mobility monitoring system as a supportive tool for monitoring daily activities in community-dwelling older adults. Daily mobility data were collected for 15 months via home-based mobility monitoring sensors among eight older adults living alone. Indoor sensor outputs were categorized into sleeping, indoor activities, and going out. Atypical patterns were identified with reference to baseline activity. Daily indoor activities were clearly differentiated by sensor outputs and sensor outputs discriminated atypical activity patterns. During the year of monitoring, a health-related issue was identified in a participant. Our findings indicate the feasibility of a home mobility monitoring system for remote, continuous, and automated assessment of a participant's health-related mobility patterns. Such a system could be used as a supportive tool to detect and intervene in the case of problematic health issues.

Analysis of Free-Living Gait in Older Adults With and Without Parkinson's Disease and With and Without a History of Falls: Identifying Generic and Disease-Specific Characteristics

BACKGROUND

Falls are associated with gait impairments in older adults (OA) and Parkinson's disease (PD). Current approaches for evaluating falls risk are based on self-report or one-time assessment and may be suboptimal. Wearable technology allows gait to be measured continuously in free-living conditions. The aim of this study was to explore generic and specific associations in free-living gait in fallers and nonfallers with and without PD.

METHODS

Two hundred and seventy-seven fallers (155 PD, 122 OA) who fell twice or more in the previous 6 months and 65 nonfallers (15 PD, 50 OA) were tested. Free-living gait was characterized as the volume, pattern, and variability of ambulatory bouts (Macro), and 14 discrete gait characteristics (Micro). Macro and Micro variables were quantified from free-living data collected using an accelerometer positioned on the low back for one week.

RESULTS

Macro variables showed that fallers walked with shorter and less variable ambulatory bouts than nonfallers, independent of pathology. Micro variables within ambulatory bouts showed fallers walked with slower, shorter and less variable steps than nonfallers. Significant interactions showed disease specific differences in variability with PD fallers demonstrating greater variability (step length) and OA fallers less variability (step velocity) than their nonfaller counterparts (p < 0.004).

CONCLUSIONS

Common and disease-specific changes in free-living Macro and Micro gait highlight generic and selective targets for intervention depending on type of faller (OA-PD). Our findings support free-living monitoring to enhance assessment. Future work is needed to confirm the optimal battery of measures, sensitivity to change and value for fall prediction.

Overview of the cholinergic contribution to gait, balance and falls in Parkinson's disease

Mobility deficits, including gait disturbance, balance impairments and falls, are common features of Parkinson's disease (PD) that negatively impact quality of life. Mobility deficits respond poorly to dopaminergic medications, indicating a role for additional neurotransmitters. Due to the critical role of cortical input to gait and balance, acetylcholine-an essential neurotransmitter system for attention-has become an area of interest for mobility. This review aimed to identify the role of cholinergic function on gait, balance, and falls in PD using three techniques; pharmacological, imaging, and electrophysiological. Studies supported the role of the cholinergic system for mobility in PD, with the most promising evidence indicating a role in falls. Imaging studies demonstrated involvement of anterior cholinergic (basal forebrain) systems in gait, and posterior (brainstem) systems in balance. However, this review identified a small number of studies which used varying protocols, making comparisons difficult. Further studies are warranted, measuring comprehensive gait and balance characteristics as well as gold standard falls detection to further quantify the relationship between ACh and mobility in PD.

Balance and mobility in patients with newly diagnosed Parkinson's disease - a five-year follow-up of a cohort in northern Sweden

Background: The presence of early balance impairment in patients with Parkinson's disease has not been fully investigated.Purpose: The purpose of this study was to examine balance and mobility, self-perceived unsteadiness, self-reported falls, and effects of medication on balance among patients at their first visit to a neurological clinic and during the ensuing five years.Materials and methods: The participants were collected from a prospective longitudinal study. One hundred and forty-five patients with idiopathic Parkinson's disease and 31 healthy controls were included. The outcome measures were the Berg Balance Scale, the Timed Up and Go, the Postural Stability test and a questionnaire.Results: At their first visit to the neurological clinic, the patients performed less well on the Berg Balance Scale (p < 0.001, r = 0.36), the Timed Up and Go (p < 0.001, r = 0.32), and the Postural Stability test (p < 0.001, r = 0.35) compared with the controls. In addition, a higher percentage of the patients reported self-perceived unsteadiness (p < 0.001, phi = 0.47). During the ensuing five years, balance and mobility worsened both with and without medication (p < 0.01, r = 0.24-0.37), although with small median differences.Conclusions: Further studies are needed to confirm that minor balance impairments exist even at the time of diagnosis and worsen during the ensuing five years.IMPLICATIONS FOR REHABILITATIONImpairments in balance and mobility may occur early in Parkinson's disease, especially in the elderly patients, and seem to worsen during the first five years.There is a need to use sensitive outcome measures and to ask the patients about unsteadiness and falls to detect balance impairment in this cohort.Parkinsonian medication has a limited effect on balance and may preferably be complemented with balance exercises to target balance impairment early in Parkinson's disease.

"Staying safe" - a narrative review of falls prevention in people with Parkinson's - "PDSAFE"

Background: Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms. Falling is common and disabling. Current medical management shows minimal impact to reduce falls or fall-related risk factors, such as deficits in gait, strength, and postural instability. Despite evidence supporting rehabilitation in reducing fall risk factors, the most appropriate intervention to reduce overall fall rate remains inconclusive. This article aims to 1) synthesise current evidence and conceptual models of falls rehabilitation in Parkinson's in a narrative review; and based on this evidence, 2) introduce the treatment protocol used in the falls prevention and multi-centre clinical trial "PDSAFE". Method: Search of four bibliographic databases using the terms "Parkinson*" and "Fall*" combined with each of the following; "Rehab*, Balanc*, Strength*, Strateg*and Exercis*" and a framework for narrative review was followed. A total of 3557 papers were identified, 416 were selected for review. The majority report the impact of rehabilitation on isolated fall risk factors. Twelve directly measure the impact on overall fall rate. Discussion: Results were used to construct a narrative review with conceptual discussion based on the "International Classification of Functioning", leading to presentation of the "PDSAFE" intervention protocol. Conclusions: Evidence suggests training single, fall risk factors may not affect overall fall rate. Combining with behavioural and strategy training in a functional, personalised multi-dimensional model, addressing all components of the "International Classification of Functioning" is likely to provide a greater influence on falls reduction. "PDSAFE" is a multi-dimensional, physiotherapist delivered, individually tailored, progressive, home-based programme. It is designed with a strong evidence-based approach and illustrates a model for the clinical delivery of the conceptual theory discussed. Implications for Rehabilitation Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms, where falling is common and disabling. Current medical and surgical management have minimal impact on falls, rehabilitation of falls risk factors has strong evidence but the most appropriate intervention to reduce overall fall rate remains inconclusive. Addressing all components of the International Classification of Function in a multifactorial model when designing falls rehabilitation interventions may be more effective at reducing fall rates in people with Parkinson's than treating isolated risk factors. The clinical model for falls rehabilitation in people with Parkinson's should be multi-dimensional.

Gait & Posture Special Issue: Gait adaptations in response to obstacle type in fallers with Parkinson's disease

BACKGROUND

Gait impairment places older adults and people with Parkinson's disease (PD) at an increased risk of falls when walking over obstacles. Increasing the height of obstacles results in greater challenge to balance however little is known about the demands encountered when negotiating obstacles of greater depth which may be greater for PD who often walk with a short, shuffling gait.

RESEARCH QUESTION

To describe gait adaptation in older adults and people with PD when walking over long and tall obstacles.

METHODS

20 people with PD and 13 older adults with a history of falls walked across an instrumented walkway under four conditions: level walking, and over a small, long and tall obstacle. Differences due to group, step and obstacle type were evaluated using General Linear Models.

RESULTS

An increased step duration, longer single limb support and a wider step (p < .033) were observed when crossing the tall obstacle for both older adults and PD. The PD group completed the crossing steps more slowly than controls, with a shorter step and longer single limb support (p < .043). Obstacle type did not significantly influence step length.

SIGNIFICANCE

The greatest temporal-spatial adaptations were elicited when participants negotiated the tall obstacle. Electing a wider step when crossing the tall obstacle was a strategy common to both faller groups (older adults and PD). The tall obstacle presented added challenge for PD who spent longer in single limb support during the crossing steps compared to controls. The long obstacle did not cause a disproportionate change in step length in people with PD, and we suggest that the obstacle may have acted as a visual cue in this group.

Health-Related Quality of Life Is Severely Affected in Primary Orthostatic Tremor

Background

Primary orthostatic tremor (POT) is a movement disorder characterized by unsteadiness upon standing still due to a tremor affecting the legs. It is a gradually progressive condition with limited treatment options. Impairments in health-related quality of life (HQoL) seem to far exceed the physical disability associated with the condition.

Methods

A multi-center, mixed-methodology study was undertaken to investigate 40 consecutive patients presenting with POT to four movement disorder centers in France. HQoL was investigated using eight quantitative scales and a qualitative study which employed semi-structured interviews. Qualitative data were analyzed with a combination of grounded-theory approach.

Results

Our results confirm that HQoL in POT is severely affected. Fear of falling was identified as the main predictor of HQoL. The qualitative arm of our study explored our initial results in greater depth and uncovered themes not identified by the quantitative approach.

Conclusion

Our results illustrate the huge potential of mixed methodology in identifying issues influencing HQoL in POT. Our work paves the way for enhanced patient care and improved HQoL in POT and is paradigmatic of this modern approach for investigating HQoL issues in chronic neurological disorders.

Measuring Activity Performance of Older Adults Using the activPAL: A Rapid Review

Current measures of physical activity and sedentary behaviors such as questionnaires and functional assessments are insufficient to provide comprehensive data on older adults. In response, the use of activity monitors has increased. The purpose of this review was to summarize and assess the quality of observational literature on activity measuring of older adults using the activPAL activity monitor. Seventeen databases and a bibliography, compiled by the activPAL creators, were searched. Articles were included if they were in English, were peer-reviewed, included people 65 years or older, measured activity using the activPAL and reported at least one of the following outcomes: step count, hours upright, hours sitting/lying, hours stepping, or hours standing. The search revealed 404 titles; after exclusions 24 were included in the final review. Of these studies, one examined older adults from residential aged care, six from hospital in-patient clinics, nine from outpatient clinics and eight examined community-dwellers. Mean age ranged from 66.0 to 84.2 years. Not all studies reported similar outcome variables, preventing data pooling. The review found a lack of high quality articles. There may be limitations to using the activPAL among older adults but further research is required to examine its use in this population.

Falls in Parkinson's disease: A complex and evolving picture

Falls are a major determinant of poor quality of life, immobilization, and reduced life expectancy in people affected by Parkinson's disease (PD) and in older adults more generally. Although many questions remain, recent research has advanced the understanding of this complex problem. The goal of this review is to condense new knowledge of falls in PD from prodromal to advanced disease, taking into account risk factors, assessment, and classification as well as treatment. The fundamental steps of clinical and research-based approaches to falls are described, namely, the identification of fall risk factors, clinical and instrumental methods to evaluate and classify fall risk, and the latest evidence to reduce or delay falls in PD. We summarize recent developments, the direction in which the field should be heading, and what can be recommended at this stage. We also provide a practical algorithm for clinicians.© 2017 International Parkinson and Movement Disorder Society.

Natural history of falls in an incident cohort of Parkinson's disease: early evolution, risk and protective features

The natural history of falls in early Parkinson’s disease (PD) is poorly understood despite the profound effect of falls on outcome. The primary aim of this study was to describe the natural history of falls, and characterise fallers over 54 months in 99 newly diagnosed people with PD. Seventy-nine (79.7%) participants fell over 54 months and 20 (20.3%) remained falls-naïve. Twenty six (26.2%) reported retrospective falls at baseline. Gait outcomes, disease severity and self-efficacy significantly discriminated across groups. Subjective cognitive complaints emerged as the only significant cognitive predictor. Without exception, outcomes were better for non-fallers compared with fallers at any time point. Between group differences for 54 month fallers and non-fallers were influenced by the inclusion of retrospective fallers and showed a broader range of discriminant characteristics, notably stance time variability and balance self-efficacy. Single fallers (n = 7) were significantly younger than recurrent fallers (n = 58) by almost 15 years (P = 0.013). Baseline performance in early PD discriminates fallers over 54 months, thereby identifying those at risk of falls. Clinical profiles for established and emergent fallers are to some extent distinct. These results reiterate the need for timely interventions to improve postural control and gait.

Towards holistic free-living assessment in Parkinson's disease: Unification of gait and fall algorithms with a single accelerometer

Technological developments have seen the miniaturization of sensors, small enough to be embedded in wearable devices facilitating unobtrusive and longitudinal monitoring in free-living environments. Concurrently, the advances in algorithms have been ad-hoc and fragmented. To advance the mainstream use of wearable technology and improved functionality of algorithms all methodologies must be unified and robustly tested within controlled and free-living conditions. Here we present and unify a (i) gait segmentation and analysis algorithm and (ii) a fall detection algorithm. We tested the unified algorithms on a cohort of young healthy adults within a laboratory. We then deployed the algorithms on longitudinal (7 day) accelerometer-based data from an older adult with Parkinson's disease (PD) to quantify real world gait and falls. We compared instrumented falls to a self-reported falls diary to test algorithm efficiency and discuss the use of unified algorithms to impact free-living assessment in PD where accurate recognition of gait may reduce the number of automated detected falls (38/week). This informs ongoing work to use gait and related outcomes as pragmatic clinical markers.

Longitudinal falls data in Parkinson's disease: feasibility of fall diaries and effect of attrition

BACKGROUND

Identifying causes of falls for people with Parkinson's disease has met with limited success. Prospective falls measurement using the "gold standard" approach is challenging. This paper examines the process and outcomes associated with longitudinal falls reporting in this population.

METHODS

Participants were recruited from ICICLE-GAIT (a collaborative study with ICICLE-PD; an incident cohort study). Monthly falls diaries were examined over 48 months for accuracy of data and rate of attrition. To further inform analysis, characteristics of participants with 36-month completed diaries were compared with those who did not complete diaries.

RESULTS

One hundred and twenty-one participants were included at baseline. By 12 months, falls diary data had reduced to 107 participants; to 81 participants by 36 months; and to 59 participants by 48 months. Key reasons for diary attrition were withdrawal from ICICLE-gait (n = 16) (13.2%), and noncompliance (n = 11) (9.1%). The only significant difference between the completed and non-completed diary groups was age at 36 months, with older participants being more likely to send in diaries.

CONCLUSIONS

Prospective falls data is feasible to collect over the long term. Attrition rates are high; however, participants retained in the study are overall representative of the total falls diary cohort. Implications for Rehabilitation Understanding falls evolution in Parkinson's disease through consistent, personalized monitoring of falls events is critical to inform effective management. Our study shows that it is feasible to collect longitudinal falls data using "gold standard" methodology, although significant resources are required for implementation. We anticipate that our study methodology is broadly applicable to any at-risk falls cohort including older adults and diverse neurological conditions. Researchers and clinicians collating prospective falls data must ensure that participants understand what constitutes a fall, as per the World Health Organization definition. A second key point is to ensure prompt recording of any fall event.

Wearables for independent living in older adults: Gait and falls

Solutions are needed to satisfy care demands of older adults to live independently. Wearable technology (wearables) is one approach that offers a viable means for ubiquitous, sustainable and scalable monitoring of the health of older adults in habitual free-living environments. Gait has been presented as a relevant (bio)marker in ageing and pathological studies, with objective assessment achievable by inertial-based wearables. Commercial wearables have struggled to provide accurate analytics and have been limited by non-clinically oriented gait outcomes. Moreover, some research-grade wearables also fail to provide transparent functionality due to limitations in proprietary software. Innovation within this field is often sporadic, with large heterogeneity of wearable types and algorithms for gait outcomes leading to a lack of pragmatic use. This review provides a summary of the recent literature on gait assessment through the use of wearables, focusing on the need for an algorithm fusion approach to measurement, culminating in the ability to better detect and classify falls. A brief presentation of wearables in one pathological group is presented, identifying appropriate work for researchers in other cohorts to utilise. Suggestions for how this domain needs to progress are also summarised.

Femur Fractures in Parkinsonism: Analysis of a National Sample Cohort in South Korea

Background and Purpose

Falling with a femur fracture is a serious event that negatively affects the quality of life of elderly individuals as well as patients with parkinsonism. This study investigated the association between parkinsonism and femur fracture and compared the risk of femur fracture between subjects with and without parkinsonism.

Methods

This study examined a population-based matched cohort constructed using the National Sample Cohort data set, which comprises approximately one million subscribers to medical insurance and aid in South Korea. Subjects with parkinsonism during 2003–2013 were identified as the exposed group, and up to five individuals matched for age, sex, and index years were identified as the controls for each parkinsonism subject. The risk of femur fracture for parkinsonism was evaluated using Cox regression.

Results

The incidence of femur fracture according to age, sex, and body mass index varied significantly between subjects with parkinsonism and controls (p<0.001). The presence of parkinsonism was associated with a higher risk of femur fractures for males [hazard ratio (HR)=2.85, 95% confidence interval [CI]=1.87–4.34], subjects younger than 65 years (HR=2.89, 95% CI=1.64–5.11), and underweight subjects (HR=3.90, 95% CI=1.82–8.35). The adjusted HR for femur fracture with parkinsonism was highest within 2 years of the disease diagnosis (HR=3.10, 95% CI=2.12–4.53).

Conclusions

Our study found that the presence of parkinsonism is more strongly related to femur fracture in males, and increases the influence of traditional risk factors on femur fracture. It is necessary to consider how factors associated with the amount of ambulatory activity–even in an early diagnosed state–can play an important role in femur fracture in subjects with parkinsonism.

Long-term risk of falls in an incident Parkinson's disease cohort: the Norwegian ParkWest study

The objective of this study is to examine the frequency, development, concomitants, and risk factors of falls in a population-based incident Parkinson's disease (PD) cohort. One hundred eighty-one drug-naïve patients with incident PD and 173 normal controls recruited from the Norwegian ParkWest study were prospectively monitored over 7 years. Information on falls was obtained biannually from patients, and at baseline and after 1, 3, 5, and 7 years of follow-up in control subjects. Generalized estimating equation models for correlated data were applied to investigate concomitant features of falls and risk factors for incident falls during 7 years of follow-up in PD. Overall, 64.1% of patients reported falling during the study period. The 7-year cumulative incidence of falls in non-falling patients at baseline (n = 153) was 57.5%, with a relative risk to controls of at least 3.1 (95% confidence interval 1.5-6.3; p < 0.002). Significant concomitants of falls in patients during the study period were higher age, Unified PD Rating Scale motor score, postural instability and gait difficulties (PIGD) phenotype, dementia, and follow-up time. Higher age at baseline, PIGD phenotype at 1-year visit, and follow-up time were independent risk factors for incident falls during follow-up. Nearly two-thirds of patients in the general PD population experience falls within 7 years of diagnosis, representing a more than threefold increased risk compared to age- and gender-matched controls. Patients with higher age at baseline and early PIGD have the greatest risk of falling and may, therefore, be the prime target of specialized assessment and treatment interventions.

Predictive model for falling in Parkinson disease patients

Background/aims

Falls are a common complication of advancing Parkinson's disease (PD). Although numerous risk factors are known, reliable predictors of future falls are still lacking. The aim of this study was to develop a multivariate model to predict falling in PD patients.

Methods

Prospective cohort with forty-nine PD patients. The area under the receiver-operating characteristic curve (AUC) was calculated to evaluate predictive performance of the purposed multivariate model.

Results

The median of PD duration and UPDRS-III score in the cohort was 6 years and 24 points, respectively. Falls occurred in 18 PD patients (30%). Predictive factors for falling identified by univariate analysis were age, PD duration, physical activity, and scores of UPDRS motor, FOG, ACE, IFS, PFAQ and GDS (p-value < 0.001), as well as fear of falling score (p-value = 0.04). The final multivariate model (PD duration, FOG, ACE, and physical activity) showed an AUC = 0.9282 (correctly classified = 89.83%; sensitivity = 92.68%; specificity = 83.33%).

Conclusions

This study showed that our multivariate model have a high performance to predict falling in a sample of PD patients.

•

In PD patients the fall rates doubles the reported rates in community welling older people without neurological disease, ranging from 35% to 90%.

•

Falls have a negative psychosocial impact creating a spiral of increased fear of falling and reduced physical activity, and increased likelihood of nursing home admission.

•

A multivariate model (PD duration, freezing of gait, Addenbrook's Cognitive Examination, and physical activity) to predict falling in our sample of PD patients showed a high performance.

Beyond the front end: Investigating a thigh worn accelerometer device for step count and bout detection in Parkinson's disease

Free-living ambulation with accelerometer-based devices is an attractive methodology to assess habitual behaviour within Parkinson's disease (PD). However, slowness of movement can contribute to difficulty in quantifying ambulatory/walking outcomes within this group by these devices. This study investigates the use of a commercial accelerometer device (activPAL^™) in those with moderate PD to understand its proprietary software (inbuilt algorithm) limitations. The values provided by the proprietary software are evaluated in comparison to novel algorithms on the same raw data to examine limitations for use within this cohort. The bespoke algorithms help to alter sensitivity in outcomes stemming from the same accelerometer data while also highlighting how slight changes in algorithms can drastically inflate/deflate values. In general, results show that the proprietary software generally quantifies lower values of outcomes (step and bout count), which is similar to previous findings. Variations in algorithm functionality highlight large heterogeneity in bout and step counts resulting from a lack of how they are defined within the literature. The novel alternative ambulatory algorithms presented here should be considered for use on raw data from the activPAL^™ in those with moderate/severe PD.

Disability is an Independent Predictor of Falls and Recurrent Falls in People with Parkinson's Disease Without a History of Falls: A One-Year Prospective Study

BACKGROUND

Predictors of falls in people with Parkinson's disease (PD) who have not previously fallen are yet to be identified.

OBJECTIVES

We aimed to identify predictors of all falls and recurrent falls in people with PD who had not fallen in the previous year and to explore the timing of falls in a 12-month follow-up period.

METHODS

Participants with PD (n = 130) were assessed by disease-specific, self-report and balance measures. Falls were recorded prospectively for 12 months. Univariate and multivariate analyses were performed. Kaplan-Meier survival analysis was used to investigate time to falling.

RESULTS

Forty participants (31%) had ≥1 fall during follow-up and 21 (16%) had ≥2 falls. Disability, reduced balance confidence and greater concern about falling were associated with ≥1 fall in univariate analyses. Additionally, PD duration and severity, freezing of gait and impaired balance were associated with ≥2 falls (p <  0.05). Disability (Schwab and England scale, Odds Ratio [OR] = 0.56 per 10 points increase; 95% confidence interval [CI] 0.39-0.80; p = 0.002) was associated with ≥1 fall in the final multivariate model (area under the receiver operating characteristic curve [AUC] = 0.65; 95% CI 0.55-0.76; p = 0.005). Disability (Unified Parkinson's Disease Rating Scale activities of daily living, OR = 1.20; 95% CI 1.07-1.34; p = 0.001) and levodopa equivalent dose (OR = 1.11 per 100 mg increase; 95% CI 0.95-1.30; p = 0.19) were associated with ≥2 falls in the final multivariate model (AUC = 0.72; 95% CI 0.60-0.84; p = 0.001). Recurrent fallers experienced their first fall earlier than single fallers (p <  0.05).

CONCLUSIONS

Self-reported disability was the strongest single predictor of all falls and recurrent falls.

External validation of a 3-step falls prediction model in mild Parkinson's disease

The 3-step falls prediction model (3-step model) that include history of falls, history of freezing of gait and comfortable gait speed <1.1 m/s was suggested as a clinical fall prediction tool in Parkinson’s disease (PD). We aimed to externally validate this model as well as to explore the value of additional predictors in 138 individuals with relatively mild PD. We found the discriminative ability of the 3-step model in identifying fallers to be comparable to previously studies [area under curve (AUC), 0.74; 95 % CI 0.65–0.84] and to be better than that of single predictors (AUC, 0.61–0.69). Extended analyses generated a new model for prediction of falls and near falls (AUC, 0.82; 95 % CI 0.75–0.89) including history of near falls, retropulsion according to the Nutt Retropulsion test (NRT) and tandem gait (TG). This study confirms the value of the 3-step model as a clinical falls prediction tool in relatively mild PD and illustrates that it outperforms the use of single predictors. However, to improve future outcomes, further studies are needed to firmly establish a scoring system and risk categories based on this model. The influence of methodological aspects of data collection also needs to be scrutinized. A new model for prediction of falls and near falls, including history of near falls, TG and retropulsion (NRT) may be considered as an alternative to the 3-step model, but needs to be tested in additional samples before being recommended. Taken together, our observations provide important additions to the evidence base for clinical fall prediction in PD.

A novel approach to falls classification in Parkinson's disease: development of the Fall-Related Activity Classification (FRAC)

BACKGROUND

Falls are a major problem for people with Parkinson's disease (PD). Despite years of focused research knowledge of falls aetiology is poor. This may be partly due to classification approaches which conventionally report fall frequency. This nosology is blunt, and does not take into account causality or the circumstances in which the fall occurred. For example, it is likely that people who fall from a postural transition are phenotypically different to those who fall during high level activities. Recent evidence supports the use of a novel falls classification based on fall related activity, however its clinimetric properties have not yet been tested.

OBJECTIVE

This study describes further development of the Fall-Related Activity Classification (FRAC) and reports on its inter-rater reliability (IRR).

METHOD

Descriptors of the FRAC were refined through an iterative process with a multidisciplinary team. Three categories based on the activity preceding the fall were identified. PD fallers were categorised as: (1) advanced (2) combined or (3) transitional. Fifty-five fall scenarios were rated by 23 raters using a standardised process. Raters comprised 3 clinical subgroups: (1) physiotherapists, (2) physicians, (3) non-medical researchers. IRR analysis was performed using weighted kappa coefficients and included sub group analysis based on clinical speciality.

RESULTS

Excellent agreement was reached for all clinicians, κ=0.807 (95% CI 0.732 to 0.870). Clinical subgroups performed similarly well (range of κ=0.780 to 0.822).

CONCLUSION

The FRAC can be reliably used to classify falls. This may discriminate between phenotypically different fallers and subsequently strengthen falls predictors in future studies.