Free-living gait cadence measured by wearable accelerometer: a promising alternative to traditional measures of mobility for assessing fall risk

Background Wearable devices have become widespread in research applications, yet evidence on whether they are superior to structured clinic-based assessments is sparse. In this manuscript, we compare traditional, lab-based metrics of mobility with a novel accelerometry-based measure of free-living gait cadence for predicting fall rates. Methods Using negative binomial regression, we compared traditional in-clinic measures of mobility (6-minute gait cadence, speed, and distance, and 4-meter gait speed) with free-living gait cadence from wearable accelerometers in predicting fall rates. Accelerometry data were collected with wrist-worn Actigraphs (GT9X) over 7 days in 432 community-dwelling older adults (aged 77.29±5.46 yrs, 59.1% men, 80.2% White) participating in the Study to Understand Fall Reduction and Vitamin D in You (STURDY). Falls were ascertained using monthly calendars, quarterly contacts, and ad-hoc telephone reports. Accelerometry-based free-living gait cadence was estimated with the Adaptive Empirical Pattern Transformation algorithm. Results Across all participants, free-living cadence was significantly related to fall rates; every 10 steps/min. higher cadence was associated with a 13.2% lower fall rate (p=0.036). Clinic-based measures of mobility were not related to falls (p>0.05). Among higher-functioning participants (cadence ≥100 steps/min.), every 10 steps/min higher free-living cadence was associated with a 27.7% lower fall rate (p=0.01). In participants with slow baseline gait (gait speed <0.8 m/s), all metrics were significantly associated with fall rates. Conclusion Data collected from biosensors in the free-living environment may provide a more sensitive indicator of fall risk than in-clinic tests, especially among higher functioning older adults who may be more responsive to intervention.

On the quality of RS41 radiosonde descent data

Radiosonde descent profiles have been available from tens of stations for several years now – mainly from Vaisala RS41 radiosondes. They have been compared with the ascent profiles, with ECMWF short-range forecasts and with co-located radio occultation retrievals. Over this time, our understanding of the data has grown, and the comparison has also shed some light on radiosonde ascent data. The fall rate is very variable and is an important factor, with high fall rates being associated with temperature biases, especially at higher altitudes. Ascent winds are affected by pendulum motion; on average, descent winds are less affected by pendulum motion and are smoother. It is plausible that the true wind variability in the vertical lies between that shown by ascent and descent profiles. This discrepancy indicates the need for reference wind measurements. With current processing, the best results are for radiosondes with parachutes and pressure sensors. Some of the wind, temperature and humidity data are now assimilated in the ECMWF forecast system.

2020 Pennsylvania Patient Safety Reporting: Updated Acute Care Reporting Rates

In our recent article summarizing 2020 data from acute care facilities in Pennsylvania, reporting rates and fall rates were provided for Q1 and Q2 2020 based on the latest data we had available at the time of publication. Given that 2020 was an unpredictable year in healthcare, any forecasting of rates for Q3 and Q4 2020 would have been unreliable. Therefore, this data snapshot serves to complete reporting rates for 2020 now that all hospital patient days and surgical encounters data from 2020 have been made available for rate calculations.

A Pilot Study Quantifying Center of Mass Trajectory during Dynamic Balance Tasks Using an HTC Vive Tracker Fixed to the Pelvis

Fall rates are increasing among the aging population and even higher falls rates have been reported in populations with neurological impairments. The Berg Balance Scale is often used to assess balance in older adults and has been validated for use in people with stroke, traumatic brain injury, and Parkinson’s disease. While the Berg Balance Scale (BBS) has been found to be predictive of the length of rehabilitation stay following stroke, a recent review concluded the BBS lacked predictive validity for fall risk. Conversely, sophisticated measures assessing center of mass (COM) displacement have shown to be predictive of falls risk. However, calculating COM displacement is difficult to measure outside a laboratory. Accordingly, we sought to validate COM displacement measurements derived from an HTC Vive tracker secured to the pelvis by comparing it to COM derived from ‘gold’ standard laboratory-based full-body motion capture. Results showed that RMS between the COM calculated from HTC Vive tracker and full body motion capture agree with an average error rate of 2.1 ± 2.6 cm. Therefore, we conclude measurement of COM displacement using an HTC Vive tracker placed on the pelvis is reasonably representative of laboratory-based measurement of COM displacement.

Free-Living Gait Cadence Measured by Wearable Accelerometers for Assessing Fall Risk

Accelerometers are widespread in research applications, yet whether they are superior to structured clinic-based assessments is unknown. Using negative binomial regression, we compared traditional in-clinic measures of mobility (6-minute gait cadence, speed, and distance, and 4-meter gait speed) with free-living gait cadence from wrist accelerometers (Actigraph GT9X) in predicting fall rates in 432 older adults (age 77.29±5.46 yrs, 59.1% men, 80.2% White) participating in the Study to Understand Fall Reduction and Vitamin D in You (STURDY). Accelerometry-based gait cadence was estimated with the Adaptive Empirical Pattern Transformation algorithm. Across all participants, every 10 steps/min higher cadence was associated with a 13.2% lower fall rate (p=0.036). Mobility measures were not related to falls (p>0.05). Among higher-functioning participants (cadence ≥100 steps/min), every 10 steps/min higher free-living cadence (p=0.01) was associated with a 27.7% lower fall rate. Data collected from accelerometers may provide a more sensitive indicator of fall risk than in-clinic tests.

Preventing Falls in Long-Term Care Using Patient-Centered Fall Interventions

Practice Problem: The practice problem identified within the Community Living Center included continuous falls, despite using current fall prevention strategies and provider-driven interventions. Baseline data reflected a fall rate of 4.2 in the long-term care areas despite improving the fall prevention program. PICOT: The PICOT question that guided this project was: In older adult residents (P), what is the effect of a standing operating procedure (SOP) using patient-centered interventions (I) compared to physician-driven fall interventions (C) on decreasing falls and falls with injuries (O) within one month (T)? Evidence: In twelve high-quality articles that fit the eligibility criteria and contained EBP literature, the overwhelming evidence revealed that an SOP encompassing patient-centered fall interventions could decrease LTC falls and falls within injury rates. Outcome: Observations reflected the nursing staff utilized the SOP and patient-centered fall interventions in practice; however, fall rates on both LTC #1 and LTC #2 increased from baseline, but the falls with injury rates remained zero. Patient satisfaction measured a weighted mean score of 4.7 of 5 points, representing satisfaction with the patient-centered interventions and nurses as a whole. Conclusion: The EBP project did not result in an overall reduction in the fall rates; however, falls with injury rates remained at zero. Furthermore, the patient's overall satisfaction with the nurses and patient-centered fall prevention program was favorable. It is essential to note that due to COVID-19 related events, the project halted after 30 days, and the results might have been different if implemented 90 days as initially projected.

Analysis of the state of grape cultivation in ATU Gagauzia

The role and importance of viticulture for the regional economy are shown. The state of grape production in ATU Gagauzia for 1997-2020 and an analysis of the stability of production for these years are presented, using the method of average annual moving indicators. Potential levels of vine productivity have been substantiated and real reserves for growth of vineyards productivity have been estimated. The analysis of indicators of grape production in agricultural enterprises of Comrat, Ceadir-Lunga and Vulcanesti districts for 2009-2020 was also carried out. In the course of the analysis, calculations were made of the growth (fall) rates of the harvesting areas, gross harvest and yield for the studied 24 years. In addition, the forecast of indicators for 2021-2022 was calculated. All calculated indicators are presented in the graphs for clarity. In conclusion, it is noted that the proposed version of the analysis of the state of grape cultivation in ATU Gagauzia is quite simple and affordable and therefore can be used by both practicing specialists and university students.

Self-Monitoring of Balance Performance can Reduce the Rate of Falls Among Older Adults

Background: 29% of older adults fall annually, resulting in the leading cause of accidental death. Fall prevention programs typically include exercise training and self-monitoring of physical activity has a positive effect on the self-efficacy and self-regulation of exercise behaviors. We assessed if self-monitoring of fall risk, without an intervention, impacts fall rates.Methods: Fifty-three older adults had open access to a balance measuring platform which allowed them to self-monitor their postural stability and fall risk using a simple 1-min standing balance test. 12-month retrospective fall history was collected and a monthly/bimonthly fall log captured prospective falls. Participants had access to self-monitoring for up to 2.2 years. Fall history and fall incidence rate ratios and their confidence intervals were compared between the periods of time with and without access to self-monitoring.Results: A 54% reduction in the number of people who fell and a 74% reduction in the number of falls was observed when participants were able to self-monitor their postural stability and fall risk, after normalizing for participation length. Further, 42.9% of individuals identified as having high fall risk at baseline shifted to a lower risk category at a median 34 days and voluntarily measured themselves for a longer period of time.Discussion: We attribute this reduction in falls to changes in health behaviors achieved through empowerment from improved self-efficacy and self-regulation. Providing older adults with the ability to self-monitor their postural stability and intuit their risk of falling appears to have modified their health behaviors to successfully reduce fall rates.