Risk stratification for frailty, impairment and assessment of sleep disorders in community-dwelling older adults

BACKGROUND

Frailty is associated with an increased susceptibility to functional decline, impairment, hospitalization, and mortality among the older adults. However, the potential reversibility of frailty lies in identifying modifiable factors that could prevent, mitigate, or interrupt its progression. While there is a suggestion that sleep disorders may increase the risk of frailty and impairment, the risk stratification of this relationship remains inconclusive.

OBJECTIVE

Stratify the risk of frailty and impairment and investigate potential connections with sleep quality, excessive daytime sleepiness, and the risk of obstructive sleep apnea in older adults dwelling in the community.

METHODS

This was a quantitative cross-sectional investigation. Frailty risk and impairment were stratified using the Frail Non-disabled Questionnaire (for impairment) and the FRAIL Scale (for Frailty). The assessment of excessive daytime sleepiness, sleep quality, and the risk of obstructive sleep apnea involved the employment of the Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, and the STOP-BANG questionnaire, respectively.

RESULTS

A total of 109 older adults living in the urban area (86 %, p = 0.010), females (61 %; p = 0.030), median age 68 (64-75) years, with overweight (36 %, p < 0.010) and self-identified as belonging to other racial or ethnic categories (71 %, p < 0.010). According to the impairment assessment, 32 % of participants were classified as disable (p < 0.01). Conversely, as per the frailty evaluation, 33 % were pre-frail and 25 % were identified as frail. Additionally, a substantial proportion experienced poor sleep quality (80 %, p = 0.010), exhibited a moderate risk of obstructive sleep apnea (49 %, p < 0.010), and showed no signs of excessive daytime sleepiness (62 %, p < 0.010). There was a modest correlation between frailty and impairment with poor sleep quality (rho = 0.39; p < 0.001) and the risk of obstructive sleep apnea (rho = 0.26; p = 0.000). However, the was no significant relationship was observed between frailty and impairment and excessive daytime sleepiness (rho = 0.04; p = 0.660). Similarly, a modest correlation was observed between sleep quality (rho = 0.33; p < 0.001), the risk of obstructive sleep apnea (rho = 0.27; p = 0.001), and frailty. Conversely, no correlation was found with excessive daytime sleepiness (rho = 0.05; p = 0.590). Also, the poor sleep quality and the risk of obstructive sleep apnea explain 14 % of the risk of frailty in the population of community-dwelling older adults (r2 = 0.14; p = 0.04).

CONCLUSION

This study reveals a modest risk of frailty and impairment with sleep quality and the risk of obstructive sleep apnea, but not with excessive daytime sleepiness in community-dwelling older adults.

Anticipatory postural adjustments in older versus young adults: a systematic review and meta-analysis

BACKGROUND

Anticipatory postural adjustments (APAs) are a feedforward mechanism triggered in advance to a predictable perturbation, to help the individual counteract mechanical effects that the disturbance may cause. Whether or not this strategy is compromised in the elderly is not a consensus in the literature.

METHODS

In this systematic review with meta-analysis, we investigated aging effects on postural control, based on anticipatory postural adjustments (APAs). We selected 11 eligible articles of the following databases: Lilacs, SciELO, PubMed, Cochrane Central, Embase, and CINAHL, involving 324 research participants, assessing their methodological quality and extracting electromyographic, posturographic, and kinematic measurements. We included studies that investigated the occurrence of APAs in healthy younger and older adults, published before 10th August 2022, in English. Studies involving participant with conditions that may affect balance or that did not report measures of onset or amplitude of electromyography (EMG), COP, or kinematics were excluded. To analyze the aggregated results from these studies, we performed the analysis based on the outcome measures (EMG, COP, or kinematic measures) used in individual studies. We calculated differences between younger and older adult groups as the mean differences between the groups and the estimated effect. Egger's test was conducted to evaluate whether this meta-analysis had publication bias.

RESULTS

Through this review, older adults showed no significant difference in the velocity to perform a movement compared to the younger adults (MD 0.95, 95% CI -0.86, 2.76, I² = 82%), but both muscle onset and center of pressure (COP) onset were significantly more delayed in older than in younger adults: erector spinae (MD -31.44, 95% CI -61.79, -1.09, I² = 95%); rectus abdominis (RA) (MD -31.51, 95% CI -70.58, -3.57, I² = 85%); tibialis anterior (TA) (MD -44.70, 95% CI -94.30, 4.91, I² = 63%); soleus (SOL) (MD -37.74, 95% CI -65.43, -10.05, I² = 91%); gastrocnemius (GAS) (MD -120.59, 95% CI -206.70, -34.49, I² = 94%); quadriceps (Q) (MD -17.42, 95% CI -34.73, -0.12, I² = 0%); biceps femoris (BF) (MD -117.47, 95% CI -192.55, -42.70, I² = 97%); COP onset (MD -45.28, 95% CI -89.57, -0.98, I² = 93%), and COP apa (COPapa) (MD 2.35, 95% CI -0.09, 4.79, I² = 64%). These changes did not seem to be linked to the speed of movement but possibly to age-related physiological changes that indicated decreased motor control during APAs in older adults.

CONCLUSIONS

Older adults use different postural strategies that aim to increase the safety margin and stabilize the body to perform the movement, according to the requirements imposed, and this should be considered in rehabilitation protocols.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD420119143198.

The hand tremor spectrum is modified by the inertial sensor mass during lightweight wearable and smartphone-based assessment in healthy young subjects

Tremors are common disorders characterized by an involuntary and relatively rhythmic oscillation that can occur in any part of the body and may be physiological or associated with some pathological condition. It is known that the mass loading can change the power spectral distribution of the tremor. Nowadays, many instruments have been used in the evaluation of tremors with bult-in inertial sensors, such as smartphones and wearables, which can significantly differ in the device mass. The aim of this study was to compare the quantification of hand tremor using Fourier spectral techniques obtained from readings of accelerometers built-in a lightweight handheld device and a commercial smartphone in healthy young subjects. We recruited 28 healthy right-handed subjects with ages ranging from 18 to 40 years. We tested hand tremors at rest and postural conditions using lightweight wearable device (5.7 g) and smartphone (169 g). Comparing both devices at resting tremor, we found with smartphone the power distribution of peak ranging 5 and 12 Hz in both hands. With wearable, the result was similar but less evident. When comparing both devices in postural tremor, there were significant differences in both frequency ranges in peak frequency and peak amplitude in both hands. Our main findings show that in resting condition the hand tremor spectrum had a higher peak amplitude in the 5–12 Hz range when the tremor was recorded with smartphones, and in postural condition there was a significantly (p < 0.05) higher peak power spectrum and peak frequency in the dominant hand tremors recorded with smartphones compared to those obtained with lightweight wearable device. Devices having different masses can alter the features of the hand tremor spectrum and their mutual comparisons can be prejudiced.

Bioelectrical impedance vector analysis and body composition in cervical spinal cord injury: A pilot study

Introduction

Body composition assessment in cervical spinal cord injury (c-SCI) individuals is important to monitor the fat free-mass (FFM) loss, due to immobilization, or gain, due to exercise practice. Single frequency bioelectrical impedance analysis (SF-BIA) is low in cost, simple and easy.

Objectives

The aims of this study are: to evaluate the concordance between the FFM values obtained using dual X-ray absorptiometry (DXA) and the three SF-BIA previous predictive equations; and to test the applicability of the bioelectrical impedance vector analysis (BIVA).

Methods

Twenty-three c-SCI males were divided into two groups: Physically active (PA; n = 13; at least 150 min/week) and non-active individuals (NPA) and were assessed by DXA and SF-BIA simultaneously.

Results

FFM values were similar between groups PA and NPA. Considering all participants, FFM values obtained by Kocina and Heyward (>11%) and Sun (<15.4%) predictive equations were different when compared to DXA (p < 0.01). However, Buchholz's et al. predictive equation showed FFM values similar to DXA, but presented poor concordance (<7%, p = 0.99; concordance coefficient = 0.85). BIVA showed consistency in ellipse distribution using FFM obtained using Buchholz et al. predictive equation.

Conclusions

The use of non-specific BIA equations can lead to misinterpretation in FFM values in male c-SCI individuals. Predictive equations for this group need to be developed.

Validity and reliability of a smartphone-based assessment for anticipatory and compensatory postural adjustments during predictable perturbations

BACKGROUND

Postural adjustments involve displacements of the center of mass (COM), controlled by the central nervous system (CNS), to maintain equilibrium whilst standing. Postural adjustments can be anticipatory (APAs) or compensatory (CPAs), and are triggered to counteract predictable perturbations.

RESEARCH QUESTION

Is the new smartphone application, Momentum, a valid and reliable tool for the assessment of body balance, by measuring APAs and CPAs using accelerometer readings?

METHODS

20 young adults were exposed to external predictable perturbations induced at the shoulder level, whilst standing. COM linear acceleration was recorded by Momentum (extracting data from a smartphone's accelerometer) and a 3D motion capture system.

RESULTS

The key results demonstrated a very high, significant correlation (r ≥ 0.7, p < 0.05) between the two device settings in the APA parameters_, which obtained r = 0.65, denoting a high correlation. Considering the reliability, variables that are compensatory in nature are presented on a scale of good to excellent in measurement methods, kinematics, and Momentum. However, the anticipatory variables presented excellent reliability only for the kinematics.

SIGNIFICANCE

These experiments show that Momentum is a valid method for measuring COM acceleration under predictable perturbations and is reliable for compensatory events.

Hand Resting Tremor Assessment of Healthy and Patients With Parkinson's Disease: An Exploratory Machine Learning Study

The aim of this study is comparing the accuracies of machine learning algorithms to classify data concerning healthy subjects and patients with Parkinson’s Disease (PD), toward different time window lengths and a number of features. Thirty-two healthy subjects and eighteen patients with PD took part on this study. The study obtained inertial recordings by using an accelerometer and a gyroscope assessing both hands of the subjects during hand resting state. We extracted time and temporal frequency domain features to feed seven machine learning algorithms: k-nearest-neighbors (kNN); logistic regression; support vector classifier (SVC); linear discriminant analysis; random forest; decision tree; and gaussian Naïve Bayes. The accuracy of the classifiers was compared using different numbers of extracted features (i.e., 272, 190, 136, 82, and 27) from different time window lengths (i.e., 1, 5, 10, and 15 s). The inertial recordings were characterized by oscillatory waveforms that, especially in patients with PD, peaked in a frequency range between 3 and 8 Hz. Outcomes showed that the most important features were the mean frequency, linear prediction coefficients, power ratio, power density skew, and kurtosis. We observed that accuracies calculated in the testing phase were higher than in the training phase. Comparing the testing accuracies, we found significant interactions among time window length and the type of classifier (p < 0.05). The study found significant effects on estimated accuracies, according to their type of algorithm, time window length, and their interaction. kNN presented the highest accuracy, while SVC showed the worst results. kNN feeding by features extracted from 1 and 5 s were the combination with more frequently highest accuracies. Classification using few features led to similar decision of the algorithms. Moreover, performance increased significantly according to the number of features used, reaching a plateau around 136. Finally, the results of this study suggested that kNN was the best algorithm to classify hand resting tremor in patients with PD.

Wearable sensors, cerebral palsy and gait assessment in everyday environments: is it a reality? - A systematic review

This systematic review aimed to investigate emerging methods used to quantify gait parameters in children with cerebral palsy (CP) in everyday environments. The StArt computational tool automatically screened the following databases: ACM, Engineering Village, IEEE, PubMed, Scopus and Web of Science from inception to June 2018. Studies reporting the use of wearable sensors to assess gait in daily settings in children with CP were included. Data regarding 1563 studies were extracted, but only three studies could be included on the basis of the inclusion/ exclusion criteria. These studies proposed wearable technologies based on the use of signals provided by triaxial accelerometers and force resistive pressure sensors. These are able to track levels of activity and detect falls, gait deviations and gait symmetry in children with CP in their daily environments. To date, only two types of sensors have been tested in this population and it remains to be clarified how wearable sensors, used to quantify activity level, might benefit children with CP.