Systematic review of candidate prognostic factors for falling in older adults identified from motion analysis of challenging walking tasks

Association Between Antihypertensive Medications and Fracture Risk in Elderly Patients: A Cross-Sectional Study

Background The use of antihypertensive medications is common among older adults to manage hypertension and prevent cardiovascular events. However, the potential impact of these medications on bone health and the risk of fractures remains a concern. This study investigates the association between antihypertensive medication use and fracture risk in elderly individuals. Materials and methods A cross-sectional study was conducted from February 2023 to July 2024, including 299 elderly patients (aged ≥65) diagnosed with hypertension and currently using antihypertensive medications. Data were collected from medical records, focusing on demographics, fracture incidence, comorbid conditions, and medication use. Logistic regression models were used to analyze the association between antihypertensive use and fracture risk, adjusting for confounders. Results Among the participants, 110 reported falls, and 88 (29.43%) sustained fractures. Fractures were more prevalent among females (63.6%) and those aged 75-84 years (45.5%). A history of falls, mobility difficulties, osteoporosis, and urinary incontinence were significantly associated with fractures. While most antihypertensive classes did not show a significant association with fracture risk, diuretics were associated with a 2.3-fold increased risk of fractures (OR 2.30, p=0.037). Conclusions This study highlights the need for careful consideration of fracture risk in elderly patients using antihypertensive medications, particularly diuretics. Healthcare providers should balance the benefits of blood pressure control with the potential risk of fractures in this population.

Neuropsychological and psychiatric outcomes among community-dwelling young Chinese older adults affected by falls in the past year with and without vision impairment

OBJECTIVE

This study was to investigate the differences between young older adults with and without vision impairment on neuropsychological and psychiatric outcomes following falls during the past year and to identify predictors of cognitive decline or mental distress.

METHODS

A secondary analysis of 668 young older Chinese adults aged 65 ∼ 79 years old with a history of falls was conducted from the cross-sectional survey data in the 2018 wave of the Chinese Longitudinal Health Longevity Survey (CLHLS).

RESULTS

Participants with vision impairment scored significantly higher on anxiety and depression and lower on cognitive function and SWB than those without vision impairment. And vision impairment was a significant predictor of adverse outcomes for all four neuropsychological and psychiatric measures.

CONCLUSION

Neurocognitive deficits, psychological problems, and decreased self-sufficiency are quite common among community-dwelling older adults with visual impairment who have a history of falls within a year.

Walking on a Balance Beam as a New Measure of Dynamic Balance to Predict Falls in Older Adults and Patients with Neurological Conditions

BACKGROUND

Beam walking is a new test to estimate dynamic balance. We characterized dynamic balance measured by the distance walked on beams of different widths in five age groups of healthy adults (20, 30, 40, 50, 60 years) and individuals with neurological conditions (i.e., Parkinson, multiple sclerosis, stroke, age: 66.9 years) and determined if beam walking distance predicted prospective falls over 12 months.

METHODS

Individuals with (n = 97) and without neurological conditions (n = 99, healthy adults, age 20-60) participated in this prospective longitudinal study. Falls analyses over 12 months were conducted. The summed distance walked under single (walking only) and dual-task conditions (walking and serial subtraction by 7 between 300 to 900) on three beams (4, 8, and 12-cm wide) was used in the analyses. Additional functional tests comprised grip strength and the Short Physical Performance Battery.

RESULTS

Beam walking distance was unaffected on the 12-cm-wide beam in the healthy adult groups. The distance walked on the 8-cm-wide beam decreased by 0.34 m in the 20-year-old group. This reduction was ~ 3 × greater, 1.1 m, in the 60-year-old group. In patients, beam walking distances decreased sharply by 0.8 m on the 8 versus 12 cm beam and by additional 1.6 m on the 4 versus 8 cm beam. Beam walking distance under single and dual-task conditions was linearly but weakly associated with age (R2 = 0.21 for single task, R2 = 0.27 for dual-task). Age, disease, and beam width affected distance walked on the beam. Beam walking distance predicted future falls in the combined population of healthy adults and patients with neurological conditions. Based on receiver operating characteristic curve analyses using data from the entire study population, walking ~ 8.0 of the 12 m maximum on low-lying beams predicted future fallers with reasonable accuracy.

CONCLUSION

Balance beam walking is a new but worthwhile measure of dynamic balance to predict falls in the combined population of healthy adults and patients with neurological conditions. Future studies are needed to evaluate the predictive capability of beam walking separately in more homogenous populations. Clinical Trial Registration Number NCT03532984.

Performance during attention-demanding walking conditions in older adults

BACKGROUND

Conventional balance and gait assessments for fall risk screening are often conducted under unperturbed conditions. However, older adults can allocate their attention to motor tasks (balance or walking) without revealing performance deficiencies, posing a challenge in identifying those with compromised gait and balance.

RESEARCH QUESTIONS

Do community-dwelling older adults exhibit greater changes in cognitive and/or walking performance under balance-challenging conditions compared to typical dual-task walking conditions?

METHODS

Twenty-nine healthy, community-dwelling older adults performed four cognitive tasks (visual and auditory Stroop tasks, Clock task, and Paced Auditory Serial Addition Test) while walking with and without lateral treadmill sways (Perturbed vs. Unperturbed) and during standing. We calculated dual-task costs (DTC) and walking perturbation effects (WPE) as the percentage of change in cognitive and walking performance between dual and single-task conditions and between Perturbed and Unperturbed conditions, respectively.

RESULTS

Older adults exhibited similar DTC and WPE on cognitive task performance. However, in walking performance, they demonstrated significantly greater WPE than DTC across all gait and stability measures (p < 0.01), including the mean and variability of stride and margins of stability (MOS) measures, the variability of trunk movement and lower-limb joint angles, and the local stability measures. Older adults took shorter but wider steps, exhibited shorter MOSAP but greater MOSML, and experienced increased movement variability and walking instability to a greater extent than during dual-task walking. Overall, changes in variability and stability measures were more pronounced than those in mean gait measures.

SIGNIFICANCE

Introducing destabilizing perturbations to increase the task demands of balance and gait assessments is a more effective method to challenge older adults compared to simply adding a concurrent cognitive task. Fall screening assessments for community-dwelling older adults should incorporate balance-challenging conditions, such as introducing gait perturbations.

In-hospital fall prediction using machine learning algorithms and the Morse fall scale in patients with acute stroke: a nested case-control study

BACKGROUND

Falls are one of the most common accidents in medical institutions, which can threaten the safety of inpatients and negatively affect their prognosis. Herein, we developed a machine learning (ML) model for fall prediction in patients with acute stroke and compared its accuracy with that of the existing fall risk prediction tool, the Morse Fall Scale (MFS).

METHODS

This is a retrospective nested case-control study. The initial sample size was 8462 admitted to a single cerebrovascular specialty hospital with acute stroke. A total of 156 fall events occurred, and each fall case was randomly matched with six control cases. Six ML algorithms were used, namely, regularized logistic regression, support vector machine, naïve Bayes (NB), k-nearest neighbors, random forest, and extreme-gradient boosting (XGB).

RESULTS

We included 156 in the fall group and 934 in the non-fall group. The mean ages of the fall and non-fall groups were 68.3 (± 12.2) and 65.3 (± 12.9) years old, respectively. The MFS total score was significantly higher in the fall group (54.3 ± 18.3) than in the non-fall group (37.7 ± 14.7). The area under the receiver operating curve (AUROC) of the MFS in predicting falls was 0.76 (0.73-0.79). XGB had the highest AUROC of 0.85 (0.78-0.92), and XGB and NB had the highest F1 score of 0.44.

CONCLUSIONS

The AUROC values of all of ML algorithms were similar to those of the MFS in predicting fall risk in patients with acute stroke, allowing for accurate and efficient fall screening.

Accuracy of the Fullerton Advanced Balance (FAB) scale and a modified FAB model for predicting falls in older adults: A prospective study

BACKGROUND

This study aimed to determine the accuracy of the FAB scale and the accuracy of combining certain FAB scale items into a model for predicting falls in older adults.

METHODS

Eighty older adults were evaluated at baseline using all FAB scale items. A 6-month follow-up period was used to determine fall incidence. The Receiver Operation Characteristic (ROC) curve was used to assess the predictive capability of the total FAB scale for falls in older adults. A model comprising some FAB items was constructed using logistic regression analysis and a forward stepwise method. ROC curve analysis was used to assess the accuracy of the new model.

RESULTS

The accuracy of the total FAB scale for predicting falls was excellent (AUC = 0.95). The cut-off score for the FAB scale was 25 points, with a sensitivity of 96.5% and a specificity of 80%. Among the ten FAB items, a regression model was identified by combining four items: step up onto and over a 6-inch bench; tandem walk; standing on foam with eyes closed; and reactive postural control. The new model achieved an excellent level of accuracy (AUC = 0.98) with a cut-off score of 11 out of 16 points, a sensitivity of 100%, and a specificity of 87%.

CONCLUSIONS

Both the total FAB score and the new FAB model were highly accurate for predicting falls in older adults.