Balance differences in people with Parkinson disease with and without freezing of gait

Published in final edited form as: Gait Posture. 2015 September ; 42(3): 306–309. doi:10.1016/j.gaitpost.2015.06.007.BACKGROUND: Freezing of gait (FOG) is a relatively common and remarkably disabling impairment associated with Parkinson disease (PD). Laboratory-based measures indicate that individuals with FOG (PD+FOG) have greater balance deficits than those without FOG (PD-FOG). Whether such differences also can be detected using clinical balance tests has not been investigated. We sought to determine if balance and specific aspects of balance, measured using Balance Evaluation Systems Test (BESTest), differs between PD+FOG and PD-FOG. Furthermore, we aimed to determine if time-efficient clinical balance measures (i.e. Mini-BESTest, Berg Balance Scale (BBS)) could detect balance differences between PD+FOG and PD-FOG. METHODS: Balance of 78 individuals with PD, grouped as either PD+FOG (n=32) or PD-FOG (n=46), was measured using the BESTest, Mini-BESTest, and BBS. Between-groups comparisons were conducted for these measures and for the six sections of the BESTest using analysis of covariance. A PD composite score was used as a covariate. RESULTS: Controlling for motor sign severity, PD duration, and age, PD+FOG had worse balance than PD-FOG when measured using the BESTest (p=0.008, F=7.35) and Mini-BESTest (p=0.002, F=10.37), but not the BBS (p=0.27, F=1.26). BESTest section differences were noted between PD+FOG and PD-FOG for reactive postural responses (p<0.001, F=14.42) and stability in gait (p=0.003, F=9.18). CONCLUSIONS: The BESTest and Mini-BESTest, which specifically assessed reactive postural responses and stability in gait, were more likely than the BBS to detect differences in balance between PD+FOG and PD-FOG. Because it is more time efficient to administer, the Mini-BESTest may be the preferred tool for assessing balance deficits associated with FOG.This study was conducted with funding from the Davis Phinney Foundation, Parkinson's Disease Foundation, NIH R01 NS077959, NIH UL1 TR000448, Greater St. Louis American Parkinson Disease Association (APDA), APDA Center for Advanced PD Research at Washington University in St. Louis. The funding sources had no role in the study design, in the collection, analysis and interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication. (Davis Phinney Foundation; Parkinson's Disease Foundation; R01 NS077959 - NIH; UL1 TR000448 - NIH; Greater St. Louis American Parkinson Disease Association (APDA); APDA Center for Advanced PD Research at Washington University in St. Louis

Two-year trajectory of fall risk in people with Parkinson disease: a latent class analysis

Published in final edited form as: Arch Phys Med Rehabil. 2016 March ; 97(3): 372–379.e1. doi:10.1016/j.apmr.2015.10.105.OBJECTIVE: To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson disease (PD). DESIGN: Latent class analysis, specifically growth mixture modeling (GMM), of longitudinal fall risk trajectories. SETTING: Assessments were conducted at 1 of 4 universities. PARTICIPANTS: Community-dwelling participants with PD of a longitudinal cohort study who attended at least 2 of 5 assessments over a 2-year follow-up period (N=230). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Fall risk trajectory (low, medium, or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6 monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. RESULTS: The GMM optimally grouped participants into 3 fall risk trajectories that closely mirrored baseline fall risk status (P=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium fall risk trajectories (P<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance. CONCLUSIONS: Regardless of their baseline characteristics, most participants had clear and stable fall risk trajectories over 2 years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD.Supported by the Davis Phinney Foundation, the Parkinson's Disease Foundation, National Institutes of Health (NIH) (grant nos. NIH R01 NS077959 and NIH UL1 TR000448), the Massachusetts and Utah Chapters of the American Parkinson Disease Association (APDA), the Greater St Louis Chapter of the APDA, and the APDA Center for Advanced Research at Washington University. (Davis Phinney Foundation; Parkinson's Disease Foundation; NIH R01 NS077959 - National Institutes of Health (NIH); NIH UL1 TR000448 - National Institutes of Health (NIH); Utah Chapter of the American Parkinson Disease Association (APDA); Greater St Louis Chapter of the APDA; APDA Center for Advanced Research at Washington University; Massachusetts Chapter of the American Parkinson Disease Association (APDA)

External validation of a simple clinical tool used to predict falls in people with Parkinson disease

Published in final edited form as: Parkinsonism Relat Disord. 2015 August ; 21(8): 960–963. doi:10.1016/j.parkreldis.2015.05.008.BACKGROUND: Assessment of fall risk in an individual with Parkinson disease (PD) is a critical yet often time consuming component of patient care. Recently a simple clinical prediction tool based only on fall history in the previous year, freezing of gait in the past month, and gait velocity <1.1 m/s was developed and accurately predicted future falls in a sample of individuals with PD. METHODS: We sought to externally validate the utility of the tool by administering it to a different cohort of 171 individuals with PD. Falls were monitored prospectively for 6 months following predictor assessment. RESULTS: The tool accurately discriminated future fallers from non-fallers (area under the curve [AUC] = 0.83; 95% CI 0.76–0.89), comparable to the developmental study. CONCLUSION: The results validated the utility of the tool for allowing clinicians to quickly and accurately identify an individual's risk of an impending fall.Davis Phinney Foundation, Parkinson Disease Foundation, NIH, APDA. (Davis Phinney Foundation; Parkinson Disease Foundation; NIH; APDA

Are the average gait speeds during the 10 meter and 6 minute walk tests redundant in Parkinson disease?

Published in final edited form as: Gait Posture. 2017 February ; 52: 178–182. doi:10.1016/j.gaitpost.2016.11.033.We investigated the relationships between average gait speed collected with the 10Meter Walk Test (Comfortable and Fast) and 6Minute Walk Test (6MWT) in 346 people with Parkinson disease (PD) and how the relationships change with increasing disease severity. Pearson correlation and linear regression analyses determined relationships between 10Meter Walk Test and 6MWT gait speed values for the entire sample and for sub-samples stratified by Hoehn & Yahr (H&Y) stage I (n=53), II (n=141), III (n=135) and IV (n=17). We hypothesized that redundant tests would be highly and significantly correlated (i.e. r>0.70, p<0.05) and would have a linear regression model slope of 1 and intercept of 0. For the entire sample, 6MWT gait speed was significantly (p<0.001) related to the Comfortable 10 Meter Walk Test (r=0.75) and Fast 10Meter Walk Test (r=0.79) gait speed, with 56% and 62% of the variance in 6MWT gait speed explained, respectively. The regression model of 6MWT gait speed predicted by Comfortable 10 Meter Walk gait speed produced slope and intercept values near 1 and 0, respectively, especially for participants in H&Y stages II-IV. In contrast, slope and intercept values were further from 1 and 0, respectively, for the Fast 10Meter Walk Test. Comfortable 10 Meter Walk Test and 6MWT gait speeds appeared to be redundant in people with moderate to severe PD, suggesting the Comfortable 10 Meter Walk Test can be used to estimate 6MWT distance in this population.This study was funded by the Davis Phinney Foundation, the Parkinson's Disease Foundation, and the National Institutes of Health (R01 NS077959, K12 HD055931, UL1 TR000448). The funding sources had no input related to study design, data collection, or decision to submit for publication. (Davis Phinney Foundation; Parkinson's Disease Foundation; R01 NS077959 - National Institutes of Health; K12 HD055931 - National Institutes of Health; UL1 TR000448 - National Institutes of Health

Comparative utility of the BESTest, mini-BESTest, and brief-BESTest for predicting falls in individuals with Parkinson disease: A cohort study

BACKGROUND: The newly developed Brief–Balance Evaluation System Test (Brief-BESTest) may be useful for measuring balance and predicting falls in individuals with Parkinson disease (PD). OBJECTIVES: The purposes of this study were: (1) to describe the balance performance of those with PD using the Brief-BESTest, (2) to determine the relationships among the scores derived from the 3 versions of the BESTest (ie, full BESTest, Mini-BESTest, and Brief-BESTest), and (3) to compare the accuracy of the Brief-BESTest with that of the Mini-BESTest and BESTest in identifying recurrent fallers among people with PD. DESIGN: This was a prospective cohort study. METHODS: Eighty participants with PD completed a baseline balance assessment. All participants reported a fall history during the previous 6 months. Fall history was again collected 6 months (n=51) and 12 months (n=40) later. RESULTS: At baseline, participants had varying levels of balance impairment, and Brief-BESTest scores were significantly correlated with Mini-BESTest (r=.94, P<.001) and BESTest (r=.95, P<.001) scores. Six-month retrospective fall prediction accuracy of the Brief-BESTest was moderately high (area under the curve [AUC]=0.82, sensitivity=0.76, and specificity=0.84). Prospective fall prediction accuracy over 6 months was similarly accurate (AUC=0.88, sensitivity=0.71, and specificity=0.87), but was less sensitive over 12 months (AUC=0.76, sensitivity=0.53, and specificity=0.93). LIMITATIONS: The sample included primarily individuals with mild to moderate PD. Also, there was a moderate dropout rate at 6 and 12 months. CONCLUSIONS: All versions of the BESTest were reasonably accurate in identifying future recurrent fallers, especially during the 6 months following assessment. Clinicians can reasonably rely on the Brief-BESTest for predicting falls, particularly when time and equipment constraints are of concern

Predictors of gait speeds and the relationship of gait speeds to falls in men and women with Parkinson disease

Gait difficulties and falls are commonly reported in people with Parkinson disease (PD). Reduction in gait speed is a major characteristic of Parkinsonian gait, yet little is known about its underlying determinants, its ability to reflect an internal reservation about walking, or its relationship to falls. To study these issues, we selected age, disease severity, and nonmotor factors (i.e., depression, quality of life, balance confidence, and exercise beliefs and attitudes) to predict self-selected (SELF), fast-as-possible (FAST), and the difference (DIFF) between these walking speeds in 78 individuals with PD. We also examined gender differences in gait speeds and evaluated how gait speeds were related to a retrospective fall report. Age, disease severity, and balance confidence were strong predictors of SELF, FAST, and, to a lesser extent, DIFF. All three parameters were strongly associated with falling. DIFF was significantly greater in men compared to women and was significantly associated with male but not female fallers. The results supported the clinical utility of using a suite of gait speed parameters to provide insight into the gait difficulties and differentiating between fallers in people with PD

Accuracy of Fall Prediction in Parkinson Disease: Six-Month and 12-Month Prospective Analyses

Introduction. We analyzed the ability of four balance assessments to predict falls in people with Parkinson Disease (PD) prospectively over six and 12 months. Materials and Methods. The BESTest, Mini-BESTest, Functional Gait Assessment (FGA), and Berg Balance Scale (BBS) were administered to 80 participants with idiopathic PD at baseline. Falls were then tracked for 12 months. Ability of each test to predict falls at six and 12 months was assessed using ROC curves and likelihood ratios (LR). Results. Twenty-seven percent of the sample had fallen at six months, and 32% of the sample had fallen at 12 months. At six months, areas under the ROC curve (AUC) for the tests ranged from 0.8 (FGA) to 0.89 (BESTest) with LR+ of 3.4 (FGA) to 5.8 (BESTest). At 12 months, AUCs ranged from 0.68 (BESTest, BBS) to 0.77 (Mini-BESTest) with LR+ of 1.8 (BESTest) to 2.4 (BBS, FGA). Discussion. The various balance tests were effective in predicting falls at six months. All tests were relatively ineffective at 12 months. Conclusion. This pilot study suggests that people with PD should be assessed biannually for fall risk

Updated Poster Presentation Abstract (n = 58) From 2020 Combined Sections Meeting Of The American Physical Therapy Association: How Well Do Clinical Walking Measures Predict Natural Walking Behavior In Parkinson Disease?

Declines in the amount and intensity of natural walking behavior in people with Parkinson disease (PD) may precede declines in motor behavior, gait, and balance. Physical interventions targeting walking behavior in PD may have the greatest impact on slowing the progression of disability. Despite a lack of supporting evidence, however, clinicians may be more likely to rely on quick performance measures of walking speed, capacity, and balance to make inferences about a patient’s walking health, rather than direct measures of natural walking behavior. Our primary purpose, therefore, was to examine the extent to which clinical walking measures might predict natural walking behavior in early to mid-stage PD. Secondarily we sought to explore differences in the predictive capability of clinical measures between relatively less active and more active participants

2020 APTA Combined Sections Meeting Scientific Poster Presentation: How Well Do Clinical Walking Measures Predict Natural Walking Behavior In Parkinson Disease?

Declines in the amount and intensity of natural walking behavior in people with Parkinson disease (PD) may precede declines in motor behavior, gait, and balance. Physical interventions targeting walking behavior in PD may have the greatest impact on slowing the progression of disability. Despite a lack of supporting evidence, however, clinicians may be more likely to rely on quick performance measures of walking speed, capacity, and balance to make inferences about a patient’s walking health, rather than direct measures of natural walking behavior. Our primary purpose, therefore, was to examine the extent to which clinical walking measures might predict natural walking behavior in early to mid-stage PD. Secondarily we sought to explore differences in the predictive capability of clinical measures between relatively less active and more active participants.https://dune.une.edu/pt_facpost/1006/thumbnail.jp

Search for New Physics with Jets and Missing Transverse Momentum in pp collisions at sqrt(s) = 7 TeV

A search for new physics is presented based on an event signature of at least three jets accompanied by large missing transverse momentum, using a data sample corresponding to an integrated luminosity of 36 inverse picobarns collected in proton--proton collisions at sqrt(s)=7 TeV with the CMS detector at the LHC. No excess of events is observed above the expected standard model backgrounds, which are all estimated from the data. Exclusion limits are presented for the constrained minimal supersymmetric extension of the standard model. Cross section limits are also presented using simplified models with new particles decaying to an undetected particle and one or two jets