Biology subjects

Pijnappels, M.

Publications and source records attributed to Pijnappels, M..

5 recordsLinked to original sources

bioRxiv2022

External validation and further exploration of fall prediction models based on questionnaires and daily-life trunk accelerometry

BackgroundAmbulatory measurements of trunk accelerations can provide valuable insight into the amount and quality of daily life activities. Such information has been used to create models that aim to identify individuals at high risk of falls. However, external validation of such prediction models is lacking, yet crucial for clinical implementation. We externally validated three previously described fall prediction models (van Schooten et al., 2015a). MethodsComplete questionnaires and one week of trunk acceleration data were obtained in 263 community-dwelling people (mean age 71.8 years, 68.1% female). To validate models, we first used the coefficients and optimal cut-offs from original cohort, then recalibrated the original models, as well as optimized parameters based on our new cohort. ResultsAmong all participants, 39.9% experienced falls during 6-month follow-up. All models showed poor precision (0.20-0.49), poor sensitivity (0.32-0.58), and good specificity (0.45-0.89). Calibration of the original models had limited effect on model performance. Using coefficients and cut-offs optimized on the external cohort also had limited benefit. Last, the odds ratios in our cohort were different from those in the original cohort and indicated that gait characteristics, except for index of harmonicity ML, were not statistically significantly associated with falls. ConclusionsPrediction of fall risk in our cohort was not as effective as in the original cohort. Recalibration as well as optimized model parameters resulted in limited increase in accuracy. Fall prediction models are highly specific to the cohort studied. This highlights the need for large representative cohorts, preferably with an external validation cohort.

bioengineering↗

bioRxiv2022

A formula for calculating 30-item Geriatric Depression Scale (GDS-30) scores from the 15-item version (GDS-15)

The Geriatric Depression Scale with 30 items (GDS-30) and with 15 items (GDS-15) are both valid tools for assessing depression in older adults, but their absolute values are not directly comparable. Here, we used a dataset (n=431) with GDS-30 scores from a project concerning fall-risk assessment in older adults (FARAO) to develop and validate a formula which can be used to convert GDS-15 scores into GDS-30 scores. We found that the GDS-15 score cannot simply be multiplied by 2 to obtain the GDS-30 scores and that estimations of GDS-30 from GDS-15 are not affected by age, sex and MMSE. Therefore, the optimal formula to estimate the GDS-30 score from the GDS-15 score was: GDS-30_estimated = 1.57 + 1.95 x GDS-15. This formula yielded an estimate of GDS-30 with an explained variance of 79%, compared to 63% when GDS-15 was simply multiplied by 2. Researchers that have used the GDS-15 and want to compare their outcomes to other studies that reported only the GDS-30 are advised to use this formula.

bioengineering↗

bioRxiv2022

In-shoe plantar pressure depends on walking speed and type of weight-bearing activity in people with diabetes at high risk of ulceration

BackgroundIn evaluating the biomechanical properties of therapeutic footwear, most often in-shoe plantar pressure is obtained during mid-gait steps at self-selected speed in a laboratory setting. However, this may not represent plantar pressures or indicate the cumulative stress experienced in daily life, where people adopt different walking speeds and weight-bearing activities. Research questionIn people with diabetes at high risk of ulceration, 1) what is the effect of walking speed on plantar pressure measures, and 2) what is the difference in plantar pressure measures between walking at self-selected speed and other weight-bearing activities? MethodsIn a cross-sectional study, we included 59 feet of 30 participants (5 females, mean age: 63.8 (SD 9.2) years). We assessed in-shoe plantar pressure with the Pedar-X system during three standardized walking speeds (0.8, 0.6 and 0.4 m/s) and eight types of activities versus walking at self-selected speed (3 components of the Timed Up and Go test (TUG), standing, accelerating, decelerating, stair ascending and descending and standing). Peak plantar pressure (PPP) and pressure-time integral (PTI) were determined for the hallux, metatarsal 1, metatarsal 2-3 and metatarsal 4-5. For statistical comparisons we used linear mixed models (<0.05) with Holm-Bonferroni correction. ResultsWith increasing walking speed, PPP increased and PTI decreased for all regions (p[≤]0.001). Standing, decelerating, stair ascending and TUG showed lower PPP than walking at self-selected speed for most regions (p[≤]0.004), whereas accelerating and stair descending showed similar PPP. Stair ascending and descending showed higher PTI than walking at self-selected speed (p[≤]0.002), standing showed lower PTI (p[≤]0.001), while the other activities showed similar PTI for most regions. SignificanceTo best evaluate the biomechanical properties of therapeutic footwear, and to assess cumulative plantar tissue stress of people with diabetes at high risk of ulceration, plantar pressures during different walking speeds and activities of daily living should be considered.

bioengineering↗

bioRxiv2021

Contribution of arm movements to recovery after a trip in older adults.

Falls are common in daily life, often caused by trips and slips and, particularly in older adults, with serious consequences. Although arm movements play an important role in balance control, there is limited research into the role of arm movements during balance recovery after tripping in older adults. We investigated how older adults use their arms to recover from a trip and the difference in the effects of arm movements between fallers (n=5) and non-fallers (n=11). Sixteen older males and females (69.7{+/-}2.3 years) walked along a walkway and were occasionally tripped over suddenly appearing obstacles. We analysed the first trip using a biomechanical model based on full-body kinematics and force-plate data to calculate whole body orientation during the trip and recovery phase. With this model, we simulated the effects of arm movements at foot-obstacle impact and during trip recovery on body orientation. Apart from an increase in sagittal plane forward body rotation at touchdown in fallers, we found no significant differences between fallers and non-fallers in the effects of arm movements on trip recovery. Like earlier studies in young adults, we found that arm movements during the recovery phase had most favourable effects in the transverse plane: by delaying the transfer of angular momentum of the arms to the body, older adults rotated the tripped side more forward thereby allowing for a larger recovery step. Older adults that are prone to falling might improve their balance recovery after tripping by learning to prolong ongoing arm movements.

animal behavior and cognition↗

bioRxiv2021

Differences in gait stability, trunk and foot accelerations between healthy young and older women

Our aim was to evaluate differences in gait acceleration intensity, variability and stability of feet and trunk between older females and young females using inertial sensors. Twenty older females (OF; mean age 68.4, SD 4.1 years) and eighteen young females (YF; mean age 22.3, SD 1.7 years) were asked to walk straight for 100 meters at their preferred speed, while wearing inertial sensors on heels and lower back. We calculated spatiotemporal measures, foot and trunk acceleration characteristics and their variability, as well as trunk stability using the local divergence exponent (LDE). Two-way analysis of variance (including the factors foot and age), Students t-test, and Mann-Whitney U test were used to compare statistical differences of measures between groups. Cohens d effects were calculated for each variable. Foot maximum vertical acceleration and amplitude, trunk-foot vertical acceleration attenuation, as well as their variability were significantly smaller in OF than in YF. In contrast, trunk mediolateral acceleration amplitude, maximum vertical acceleration, and amplitude, as well as their variability were significantly larger in OF than in YF. Moreover, OF showed lower stability (i.e., higher LDE values) in mediolateral acceleration, mediolateral and vertical angular velocity of the trunk. Even though we measured healthy older females, these participants showed lower vertical foot accelerations with higher vertical trunk acceleration, lower trunk-foot vertical acceleration attenuation, less gait stability, and more variability of the trunk, and hence, were more likely to fall. These findings suggest that instrumented gait measurements may help for early detection of changes or impairments in gait performance, even before this can be observed by clinical eye or gait speed.

bioengineering↗