Value of the short physical performance battery (SPPB) in predicting fall and fall-induced injury among old Chinese adults

Effects of a sequential square mat walking training program Fisior® on improving physical performance in older adults with Parkinson's disease: A pilot study

BACKGROUND

This study aimed to assess the efficacy of a 12-week functional walking training program utilizing a sequential square mat (Fisior® Mat) on the physical performance of older adults diagnosed with Parkinson's Disease (PD).

METHODS

Participants, aged over 60 and diagnosed with mild to moderate PD, underwent progressive resistance training sessions lasting 30-40 minutes, three times a week, using the Fisior® sequential square mat. A randomized clinical trial was conducted with participants from a patient association. Multiple linear regression models were employed to analyze physical performance variation between intervention and control groups.

RESULTS

Twenty-eight patients (14 in each group) participated, with improvements observed in total Short Physical Performance Battery (SPPB) score, chair test score, gait speed score, and balance test score. Participants in the intervention group showed significant improvement in chair and balance test scores compared to controls.

CONCLUSION

The Fisior® sequential square mat program, as an adjunct to conventional outpatient physiotherapy, effectively enhances physical performance in older adults with PD.

Walking and balance in older adults with age-related hearing loss: A cross-sectional study of cases and matched controls

BACKGROUND

Hearing loss (HL) is prevalent in older individuals. It is suggested that there is an association between age-related HL, walking and balance, leading to poorer function and increased risk of falls in older individuals.

RESEARCH QUESTION

Is HL associated with physical performance, gait variability, and postural sway in older adults, and will additional dizziness moderate the effect of HL on balance?

METHODS

In this cross-sectional study we examined 100 older individuals (age ≥70 years, 60 % females), divided in two groups, with or without age-related HL. Physical function and balance were evaluated by the Short Physical Performance Battery (SPPB), postural sway measured on a force platform (posturography), and balance in walking (gait variability) measured with a body-worn sensor. Multiple linear regression was used to examine the relationships between the variables, with physical function and balance as outcomes and HL as a dichotomous exposure (>30 dB). For all analyses, we further tested if associations were modified by self-reported dizziness.

RESULTS

Multiple regression analysis with HL, age, sex, education, diabetes, and cardiovascular disease revealed a significant association between reduced SPPB and HL. Multiple linear regression analysis also showed that HL was associated with increased postural sway on firm surface with eyes open and closed after adjusting for age, sex, education, diabetes, and cardiovascular disease. There was significant association between HL and increased gait variability during dual task walking in all directions after adjusting for age, sex, education, diabetes, and cardiovascular disease. Further, we found that the association between HL and SPPB was significantly stronger in those with dizziness compared with those without dizziness. Dizziness also modified the association of HL with the other SPPB sub-scores but not for the other outcomes of postural sway or gait variability.

SIGNIFICANCE

In this study, age-related HL was associated with worse physical performance as measured by SPPB, postural sway, and gait variability. This relationship illustrates the importance of assessing physical performance in people with HL to prevent risk of falls and disability.

Short physical performance battery is not associated with falls and injurious falls in older persons: longitudinal data of the SCOPE project

INTRODUCTION

Falls and fall-related injuries in older persons are a major public health problem. Our objective was to study the predictive value of the Short Physical Performance Battery (SPPB) in the cohort of the SCOPE project on falls, injurious falls, and possible difference of prediction between indoors and outdoors falls.

METHODS

For this sub-study of the SCOPE project participants reporting no falls at baseline, and survey data on falls at the 12-month and 24-month follow-up were included. Participant´s characteristics were assessed during the baseline interview and medical examinations. Falls as well as injurious falls and fall circumstances were obtained self-reported. SPPB and its association with fallers vs. no fallers at 12 and at 24 months were studied with logistic regression models.

RESULTS

The 1198 participants had a median age of 79 years (77-82), and a median SPPB of 10 (8-11), with a 52.5% of female. A total of 227 and 277 falls (12- and 24- month visits, respectively) were reported. In the crude model, the SPPB sum scores (p < 0.001) as well as most single item scores were significant different between fallers and non-fallers over time. However, the association was attenuated in models adjusted for age, sex, marital status, number of medications, quality of life, handgrip strength, and muscle mass [e.g., 12 months; OR 0.94 (0.87-1.02)]. While SPPB fails to differentiate between injurious and non-injurious falls (p = 0.48), a lower SPPB score was associated with falls at home (p < 0.01) after 24 months.

CONCLUSION

SBPP was not able to significantly predict the risk of falling as well as experiencing an injurious fall.

TRIAL REGISTRATION

This study was registered prospectively on 25th February 2016 at clinicaltrials.gov (NCT02691546).

Machine learning versus binomial logistic regression analysis for fall risk based on SPPB scores in older adult outpatients

Objective

To compare the performance of the diagnostic model for fall risk based on the short physical performance battery (SPPB) developed using commercial machine learning software (MLS) and binomial logistic regression analysis (BLRA).

Methods

We enrolled 797 out of 850 outpatients who visited the clinic between March 2016 and November 2021. Patients were categorized into the development (n = 642) and validation (n = 155) datasets. Age, sex, number of comorbidities, number of medications, body mass index (BMI), calf circumference (left-right average), handgrip strength (left-right average), total SPPB score, and history of falls were determined. We defined fall risk by an SPPB score of ≤6 in men and ≤9 in women. The main metrics used for evaluating the machine learning model and BLRA were the area under the curve (AUC), accuracy, precision, recall (sensitivity), specificity, and F-measure. The commercial MLS automatically calculates the parameter range of the highest contribution.

Results

The participants included 797 outpatients (mean age, 76.3 years; interquartile range, 73.0-81.0; 288 men). The metrics of the current diagnostic model in the commercial MLS were as follows: AUC = 0.78, accuracy = 0.74, precision = 0.46, recall (sensitivity) = 0.81, specificity = 0.71, F-measure = 0.59. The metrics of the current diagnostic model in the BLRA were as follows: AUC = 0.77, accuracy = 0.75, precision = 0.47, recall (sensitivity) = 0.67, specificity = 0.77, F-measure = 0.55. The risk factors for falls in older adult outpatients were handgrip strength, female sex, experience of falls, BMI, and calf circumference in the commercial MLS.

Conclusions

The diagnostic model for fall risk based on SPPB scores constructed using commercial MLS is noninferior to BLRA.