Identification of Clinical and Functional Falls Risk Factors Among Low Bone Density Older Women: A Longitudinal Study

Accuracy of Tools to Differentiate Single From Recurrent Fallers Pre-Frail Older Women

Objectives

The objectives of this study were to analyze and compare musculoskeletal and functional performance and present cutoff points to differentiate pre-frail community-dwelling older women regarding their fall history: non fallers (0 falls), fallers (single fall), and recurrent fallers (≥2 falls).

Method

This is a cross-sectional, retrospective study on 90 pre-frail community-dwelling older women (71.2 ± 4.49 years) according to Fried criteria. We assessed peak torque (PT) (isokinetic dynamometer), muscle architecture/mass (ultrasound/dual-energy X-ray absorptometry), and the following functional performance: usual gait speed (UGS), fast gait speed (FGS), walking speed reserve (WSR), cadence and step length, and timed up and go.

Results

The recurrent fallers presented lower UGS (1.12 ± 0.18 vs. 1.29 ± 0.28 m/s; p = 0.05) and isometric PT of knee extensors than the fallers (89.88 ± 20.99 vs. 115.55 ± 23.09 Nm; p = 0.01), and lower FGS than the fallers (1.35 ± 0.26 vs. 1.5 ± 0.29 m/s; p = 0.03) and non-fallers (1.35 ± 0.26 vs. 1.52 ± 0.26 m/s; p = 0.01). The outcomes that differentiated the fallers from the non-fallers were both WSR calculated as a difference (WSRdiff) (≤0.26 m/s) and WSR calculated as a ratio (WSRratio) (≤1.25 m/s), while to differentiate the recurrent fallers from the non-fallers were FGS (≤1.44 m/s) and step length (≤73 cm). The following cutoff points might be used to differentiate recurrent fallers and fallers: UGS (≤1.12 m/s), FGS (≤1.34m/s), step length (≤73 cm), PT knee extension (≤114.2 Nm), PT knee flexion (≤46.3 Nm), and PT ankle dorsiflexion (≤22.1 Nm).

Conclusion

Recurrent fallers community-dwelling pre-frail older women presented a worse musculoskeletal and functional performance when compared to the non-fallers and fallers. Gait speed, step length, PT of both knee extension and flexion, and ankle dorsiflexion can be used to identify both single and recurrent fallers pre-frail older women, contributing to guide interventions and prevent falls and fractures.

Effects of 8 Weeks of Balance Training, Virtual Reality Training, and Combined Exercise on Lower Limb Muscle Strength, Balance, and Functional Mobility Among Older Men: A Randomized Controlled Trial

BACKGROUND

Poor muscle strength, balance, and functional mobility have predicted falls in older adults. Fall prevention guidelines recommend highly challenging balance training modes to decrease falls; however, it is unclear whether certain modes are more effective. The purpose of this study was to determine whether traditional balance training (BT), virtual reality balance training (VR), or combined exercise (MIX) relative to a waitlist control group (CON) would provoke greater improvements in strength, balance, and functional mobility as falls risk factor proxies for falls in older men.

HYPOTHESIS

We hypothesized that 8 weeks of MIX will provoke the greatest improvements in falls risk factors, followed by similar improvements after BT and VR, relative to the CON.

STUDY DESIGN

Single-blinded randomized controlled trial NCT02778841 (ClinicalTrials.gov identifier).

LEVEL OF EVIDENCE

Level 2.

METHODS

In total, 64 community-dwelling older men (age 71.8 ± 6.09 years) were randomly assigned into BT, VR, MIX, and CON groups and tested at baseline and at the 8-week follow-up. The training groups exercised for 40 minutes, 3 times per week, for 8 weeks. Isokinetic quadriceps and hamstrings strength on the dominant and nondominant legs were primary outcomes measured by the Biodex Isokinetic Dynamometer. Secondary outcomes included 1-legged stance on firm and foam surfaces, tandem stance, the timed-up-and-go, and gait speed. Separate one-way analyses of covariance between groups were conducted for each outcome using baseline scores as covariates.

RESULTS

(1) MIX elicited greater improvements in strength, balance, and functional mobility relative to BT, VR, and CON; (2) VR exhibited better balance and functional mobility relative to BT and CON; and (3) BT demonstrated better balance and functional mobility relative to CON.

CONCLUSION

The moderate to large effect sizes in strength and large effect sizes for balance and functional mobility underline that MIX is an effective method to improve falls risk among older adults.

CLINICAL RELEVANCE

This study forms the basis for a larger trial powered for falls.

Accuracy of clinical-functional tools to identify risk of falls among community-dwelling older adults

Abstract Introduction: The identification of older adults who present greater chances of falling is the first step in the prevention of falls. Clinical instruments have been shown to be able to differentiate fallers from non-fallers, but their predictive validity remains controversial. Objective: To investigate the accuracy of the Short Physical Performance Battery (SPPB) and Quick Screen Clinical Fall Risk Assessment (QuickScreen) instruments to identify risk of falls in community-dwelling older adults. Method: This is a prospective methodological study with 81 older adults (≥ 60 years), assessed at baseline by SPPB and QuickScreen and monitored after one year to identify the occurrence of falls. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and area under the ROC curve (AUC) were calculated. Results: 28.4% of the sample reported falls. QuickScreen presented 52.2% sensitivity, 74.1% specificity, 44.4% PPV, 79.6% NPV and 0.656 AUC. The AUC for SPPB was not significant (p = 0.087). Conclusion: QuickScreen presented poor accuracy when predicting falls and SPPB was unable to identify community-dwelling older adults at risk of falls. The QuickScreen instrument stood out for its high potential to identify true negatives.

The Cumulative Complexity Model and Repeat Falls: A Quality Improvement Project

PURPOSE OF PROJECT

The purpose of this article is to demonstrate the effectiveness of the Cumulative Complexity Model as a framework to build an Excel tool and a Pareto tool that will enable inpatient case managers to predict the increased risk for and prevent repeat falls. The Excel tool is based on work explained in a previous article by and uses a macro to analyze the factors causing the repeat falls and then calculate the probability of it happening again. This enables the case manager to identify trends in how the patient is transitioning toward goals of care and identify problems before they become barriers to the smooth transition to other levels of care. Thus, the case manager will save the facility money by avoiding unneeded days of care and avoiding the costs that result from rendering medical care for the patient who has fallen.

PRIMARY PRACTICE SETTINGS

In July 2015, a group of nurses at a small Veterans Health Administration Hospital in the Northwest collaborated to find ways to reverse a trend of increasing falls and repeat falls.

METHODOLOGY AND SAMPLE

A retrospective chart review of all falls and repeat falls (N = 73) that happened between January 2013 and July 2015 was used to generate a list of top 11 contributing variables that enabled evaluation of the data. A bundle of 3 interventions was instituted in October 2015: (1) development of a dedicated charge nurse/resource nurse, (2) use of a standardized method of rounding, and (3) use of a noncontact patient monitoring system ("virtual nurses"). Falls pre- and postimplementation (N = 109) were analyzed using linear and logistic regression analyses. Data were entered into an Excel sheet and analyzed to identify the major contributing factors to falls and repeat falls and to identify trends. These data were also evaluated to find out whether length of stay and nurse workload contributed to falls.

RESULTS

Fifteen months after implementation of the aforementioned interventions, falls on the unit went down from 30 aggregate falls in 2015 to 17 aggregate falls in 2016. Repeat falls in 2015 went from 9 repeat falls after admission to the unit down to 2 repeat falls in 2016. Each additional extrinsic variable that was present added an additional 1.43 to the odds ratio (OR) for a fall. Similarly, each additional intrinsic variable present added 2.08 to the OR for a fall. The linear regression of length of stay and falls demonstrated that 17.5% of falls correlated with length of stay, F(1,36) = 7.63, p = .009, R = .175, adjusted R = .152. Workload correlated with work 17% of the time, as measured by using ward days of care, F(1,100) = 20.84, p = .00001, R = .17, adjusted R = .16.

IMPLICATIONS FOR CASE MANAGERS

Two examples of the how to use these tools are located in the "Discussion" section of the article.