Determinants of gait speed in COPD.
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ABSTRACT:
SUBMITTER: Karpman C
PROVIDER: S-EPMC4077407 | biostudies-other | 2014 Jul
REPOSITORIES: biostudies-other
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Project description:Gait speed is a measure of general fitness. Changing from usual (UGS) to maximum (MGS) gait speed requires coordinated action of many body systems. Gait speed reserve (GSR) is defined as MGS-UGS. From a shortlist of 88 features across five categories including sociodemographic, cognitive, and physiological, we aimed to find and compare the sets of predictors that best describe UGS, MGS, and GSR. For this, we leveraged data from 3,925 adults aged 50+ from Wave 3 of The Irish Longitudinal Study on Ageing (TILDA). Features were selected by a histogram gradient boosting regression-based stepwise feature selection pipeline. Each model's feature importance and input-output relationships were explored using TreeExplainer from the Shapely Additive Explanations explainable machine learning package. The mean Radj2 (SD) from fivefold cross-validation on training data and the Radj2 score on test data were 0.38 (0.04) and 0.41 for UGS, 0.45 (0.04) and 0.46 for MGS, and 0.19 (0.02) and 0.21 for GSR. Each model selected features across all categories. Features common to all models were age, grip strength, chair stands time, mean motor reaction time, and height. Exclusive to UGS and MGS were educational attainment, fear of falling, Montreal cognitive assessment errors, and orthostatic intolerance. Exclusive to MGS and GSR were body mass index (BMI), and number of medications. No features were selected exclusively for UGS and GSR. Features unique to UGS were resting-state pulse interval, Center for Epidemiologic Studies Depression Scale (CESD) depression, sit-to-stand difference in diastolic blood pressure, and left visual acuity. Unique to MGS were standard deviation in sustained attention to response task times, resting-state heart rate, smoking status, total heartbeat power during paced breathing, and visual acuity. Unique to GSR were accuracy proportion in a sound-induced flash illusion test, Mini-mental State Examination errors, and number of cardiovascular conditions. No interactions were present in the GSR model. The four features that overall gave the most impactful interactions in the UGS and MGS models were age, chair stands time, grip strength, and BMI. These findings may help provide new insights into the multisystem predictors of gait speed and gait speed reserve in older adults and support a network physiology approach to their study.
| S-EPMC10013005 | biostudies-literature
Project description:BackgroundThis study explores whether a sex difference in sensitivity to (strength of the association) and/or in exposure to (prevalence) determinants of gait speed contributes to the observed lower gait speed among older women compared to men.MethodsData from the Longitudinal Aging Study Amsterdam (LASA) were used. In total 2407 men and women aged 55-81 years were included, with baseline measurements in 1992/2002 and follow-up measurements every 3-4 years for 15/25 years. Multivariable mixed model analysis was used to investigate sex differences in sensitivity (interaction term with sex) and in exposure to (change of the sex difference when adjusted) socio-demographic, lifestyle, social and health determinants of gait speed.ResultsWomen had a 0.054 m/s (95 % CI: 0.076 - 0.033, adjusted for height and age) lower mean gait speed compared to men. In general, men and women had similar determinants of gait speed. However, higher BMI and lower physical activity were more strongly associated with lower gait speed in women compared to men (i.e. higher sensitivity). More often having a lower educational level, living alone and having more chronic diseases, pain and depressive symptoms among women compared to men also contributed to observed lower gait speed in women (i.e. higher exposure). In contrast, men more often being a smoker, having a lower physical activity and a smaller personal network size compared to women contributed to a lower gait speed among men (i.e. higher exposure).ConclusionsBoth a higher sensitivity and higher exposure to determinants of gait speed among women compared to men contributes to the observed lower gait speed among older women. The identified (modifiable) contributing factors should be taken into account when developing prevention and/or treatment strategies aimed to enhance healthy physical aging. This might require a sex-specific approach in both research and clinical practice, which is currently often lacking.
| S-EPMC8173843 | biostudies-literature
Project description:BackgroundFunctional independence with aging is an important goal for individuals and society. Simple prognostic indicators can inform health promotion and care planning, but evidence is limited by heterogeneity in measures of function.MethodsWe performed a pooled analysis of data from seven studies of 27,220 community-dwelling older adults aged 65 or older with baseline gait speed, followed for disability and mortality. Outcomes were incident inability or dependence on another person in bathing or dressing; and difficulty walking ¼ - ½ mile or climbing 10 steps within 3 years.ResultsParticipants with faster baseline gait had lower rates of incident disability. In subgroups (defined by 0.2 m/s-wide intervals from <0.4 to ? 1.4 m/s) with increasingly greater gait speed, 3-year rates of bathing or dressing dependence trended from 10% to 1% in men, and from 15% to 1% in women, while mobility difficulty trended from 47% to 4% in men and 40% to 6% in women. The age-adjusted relative risk ratio per 0.1 m/s greater speed for bathing or dressing dependence in men was 0.68 (0.57-0.81) and in women: 0.74 (0.66-0.82); for mobility difficulty, men: 0.75 (0.68-0.82), women: 0.73 (0.67-0.80). Results were similar for combined disability and mortality. Effects were largely consistent across subgroups based on age, gender, race, body mass index, prior hospitalization, and selected chronic conditions. In the presence of multiple other risk factors for disability, gait speed significantly increased the area under the receiver operator characteristic curve.ConclusionIn older adults, gait speed predicts 3 year incidence of bathing or dressing dependence, mobility difficulty, and a composite outcome of disability and mortality.
| S-EPMC4715231 | biostudies-literature
Project description:Inertial swimmers use flexural movements to push water and generate thrust. We quantify this dynamical process for a slender body in a fluid by accounting for passive elasticity and hydrodynamics and active muscular force generation and proprioception. Our coupled elastohydrodynamic model takes the form of a nonlinear eigenvalue problem for the swimming speed and locomotion gait. The solution of this problem shows that swimmers use quantized resonant interactions with the fluid environment to enhance speed and efficiency. Thus, a fish is like an optimized diode that converts a prescribed alternating transverse motion to forward motion. Our results also allow for a broad comparative view of swimming locomotion and provide a mechanistic basis for the empirical relation linking the swimmer's speed U, length L, and tail beat frequency f, given by U/L ~ f [Bainbridge R (1958) J Exp Biol 35:109-133]. Furthermore, we show that a simple form of proprioceptive sensory feedback, wherein local muscle activation is function of body curvature, suffices to drive elastic instabilities associated with thrust production and leads to a spontaneous swimming gait without the need for a central pattern generator. Taken together, our results provide a simple mechanistic view of swimming consistent with natural observations and suggest ways to engineer artificial swimmers for optimal performance.
| S-EPMC4386394 | biostudies-literature
Project description:Gait biofeedback is a well-studied strategy to reduce gait impairments such as propulsion deficits or asymmetric step lengths. With biofeedback, participants alter their walking to reach the desired magnitude of a specific parameter (the biofeedback target) with each step. Biofeedback of anterior ground reaction force and step length is commonly used in post-stroke gait training as these variables are associated with self-selected gait speed, fall risk, and the energy cost of walking. However, biofeedback targets are often set as a function of an individual's baseline walking pattern, which may not reflect the ideal magnitude of that gait parameter. Here we developed prediction models based on speed, leg length, mass, sex, and age to predict anterior ground reaction force and step length of neurotypical adults as a possible method for personalized biofeedback. Prediction of these values on an independent dataset demonstrated strong agreement with actual values, indicating that neurotypical anterior ground reaction forces can be estimated from an individual's leg length, mass, and gait speed, and step lengths can be estimated from individual's leg length, mass, age, sex, and gait speed. Unlike approaches that rely on an individual's baseline gait, this approach provides a standardized method to personalize gait biofeedback targets based on the walking patterns exhibited by neurotypical individuals with similar characteristics walking at similar speeds without the risk of over- or underestimating the ideal values that could limit feedback-mediated reductions in gait impairments.
| S-EPMC10195830 | biostudies-literature
Project description:Locomotion is a fundamental motor function common to the animal kingdom. It is implemented episodically and adapted to behavioural needs, including exploration, which requires slow locomotion, and escape behaviour, which necessitates faster speeds. The control of these functions originates in brainstem structures, although the neuronal substrate(s) that support them have not yet been elucidated. Here we show in mice that speed and gait selection are controlled by glutamatergic excitatory neurons (GlutNs) segregated in two distinct midbrain nuclei: the cuneiform nucleus (CnF) and the pedunculopontine nucleus (PPN). GlutNs in both of these regions contribute to the control of slower, alternating-gait locomotion, whereas only GlutNs in the CnF are able to elicit high-speed, synchronous-gait locomotion. Additionally, both the activation dynamics and the input and output connectivity matrices of GlutNs in the PPN and the CnF support explorative and escape locomotion, respectively. Our results identify two regions in the midbrain that act in conjunction to select context-dependent locomotor behaviours.
| S-EPMC5937258 | biostudies-literature
Project description:ObjectiveTo investigate in vivo the relationship of regional brain β-amyloid (Aβ) to gait speed in a group of elderly individuals at high risk for dementia.MethodsCross-sectional associations between brain Aβ as measured with [18F]florbetapir PET and gait speed were examined in 128 elderly participants. Subjects ranged from healthy to mildly cognitively impaired enrolled in the control arm of the multidomain intervention in the Multidomain Alzheimer Preventive Trial (MAPT). Nearly all participants presented spontaneous memory complaints. Regional [18F]florbetapir (AV45) standardized uptake volume ratios were obtained via semiautomated quantitative analysis using the cerebellum as reference region. Gait speed was measured by timing participants while they walked 4 meters. Associations were explored with linear regression, correcting for age, sex, education, body mass index (BMI), and APOE genotype.ResultsWe found a significant association between Aβ in the posterior and anterior putamen, occipital cortex, precuneus, and anterior cingulate and slow gait speed (all corrected p < 0.05). A multivariate model emphasized the locations of the posterior putamen and the precuneus. Aβ burden explained up to 9% of the variance in gait speed, and significantly improved regression models already containing demographic variables, BMI, and APOE status.ConclusionsThe present PET study confirms, in vivo, previous postmortem evidence showing an association between Alzheimer disease (AD) pathology and gait speed, and provides additional evidence on potential regional effects of brain Aβ on motor function. More research is needed to elucidate the neural mechanisms underlying these regional associations, which may involve motor and sensorimotor circuits hitherto largely neglected in the pathophysiology of AD.
| S-EPMC4731288 | biostudies-literature
Project description:ObjectiveWe investigated dopaminergic and cholinergic correlates of gait speed in Parkinson disease (PD) and non-PD control subjects to test the hypothesis that gait dysfunction in PD may result from multisystem degeneration.MethodsThis was a cross-sectional study. Subjects with PD but without dementia (n = 125, age 65.6 ± 7.3 years) and elderly subjects without PD (n = 32, age 66.0 ± 10.6 years) underwent [¹¹C]dihydrotetrabenazine dopaminergic and [(11)C]methyl-4-piperidinyl propionate acetylcholinesterase PET imaging, and cognitive and clinical testing, including an 8.5-m walk in the dopaminergic "off" state. The fifth percentile of cortical cholinergic activity in the elderly without PD was used to define normal-range activity in the subjects with PD.ResultsNormal-range cortical cholinergic activity was present in 87 subjects with PD (69.6%). Analysis of covariance using gait speed as the dependent variable demonstrated a significant model (F = 6.70, p < 0.0001) with a significant group effect (F = 3.36, p = 0.037) and significant slower gait speed in the low cholinergic PD subgroup (0.97 ± 0.22 m/s) with no significant difference between the normal-range cholinergic PD subgroup (1.12 ± 0.20 m/s) and control subjects (1.17 ± 0.18 m/s). Covariate effects were significant for cognition (F = 6.58, p = 0.011), but not for striatal dopaminergic innervation, sex, or age.ConclusionComorbid cortical cholinergic denervation is a more robust marker of slowing of gait in PD than nigrostriatal denervation alone. Gait speed is not significantly slower than normal in subjects with PD with relatively isolated nigrostriatal denervation.
| S-EPMC3806920 | biostudies-literature
Project description:Locomotion requires precise control of the strength and speed of muscle contraction and is achieved by recruiting functionally-distinct subtypes of motor neurons (MNs). MNs are essential to movement and differentially susceptible in disease, but little is known about how MNs acquire functional subtype-specific features during development. Using single-cell RNA profiling in embryonic and larval zebrafish, we identify novel and conserved molecular signatures for MN functional subtypes, and identify genes expressed in both early post-mitotic and mature MNs. Assessing MN development in genetic mutants, we define a molecular program essential for MN functional subtype specification. Two evolutionarily-conserved transcription factors, Prdm16 and Mecom, are both functional subtype-specific determinants integral for fast MN development. Loss of prdm16 or mecom causes fast MNs to develop transcriptional profiles and innervation similar to slow MNs. These results reveal the molecular diversity of vertebrate axial MNs and demonstrate that functional subtypes are specified through intrinsic transcriptional codes.
2023-08-24 | GSE240026 | GEO
Project description:BACKGROUND AND PURPOSE:Given the heterogeneity of mobility outcomes after stroke, the purpose of this study was to examine how the minimal detectable change (MDC) for gait speed varies based on an individual's baseline walking speed. METHODS:Seventy-six participants with chronic stroke and able to walk without therapist assistance participated in 2 visits to record overground self-selected comfortable gait speed (CGS) and fast gait speed (FGS). Based on the CGS at visit 1, participants were assigned to 1 of 3 speed groups: low (<0.4 m/s; n = 32), moderate (0.4-0.8 m/s; n = 29), and high functioning group (>0.8 m/s; n = 15). Participants were then reclassified using updated gait speed cutoffs of 0.49 and 0.93 m/s. For each group, we determined test-retest reliability between visits, and the MDC for CGS and FGS. RESULTS:Gait speed significantly increased from visit 1 to visit 2 for each group (P < 0.001). The reliability for CGS declined with increasing gait speed, and MDC95 values increased with increasing gait speed (low: 0.10 m/s; moderate: 0.15 m/s; and high: 0.18 m/s). Similar findings were observed for FGS, and when participants were recoded using alternative thresholds. DISCUSSION AND CONCLUSIONS:Slower walkers demonstrated greater consistency in walking speed from day to day, which contributed to a smaller MDC95 than faster walkers. These data will help researchers and clinicians adjust their expectations and goals when working with individuals with chronic stroke. Expectations for changing gait speed should be based on baseline gait speed, and will allow for more appropriate assessments of intervention outcomes. AVAILABLE: for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A253).
| S-EPMC6361716 | biostudies-literature