Introduction Long-term treatment is used in patients with osteoporosis, and bisphosphonates (BPs) are the most commonly prescribed medications. However, in some patients this therapy is not effective, cause different side effects and complications. Unfortunately, at least one year is needed to identify and confirm an ineffectiveness of BPs therapy on bone mineral density (BMD). Among other factors, a response to BPs therapy may also be explained by genetic factors. The aim of this study was to analyze the influence of SOST , PTH , FGF2 , FDPS , GGPS1 , and LRP5 gene variants on the response to treatment with aminobisphosphonates. Materials and methods Women with postmenopausal osteoporosis were included to this study if they used aminobisphosphonates for at least 12 months. Exclusion criteria were: persistence on BPs therapy less than 80%, bone metabolic diseases, diseases deemed to affect bone metabolism, malignant tumours, using of any medications influencing BMD. The study protocol was approved by the local ethics committee. The BMD at the lumbar spine and femoral neck were measured using dual x-ray absorptiometry (GE Lunar) before and at least 12 months after treatment with BPs. According to BMD change, patients were divided in two groups–responders and non-responders to BPs terapy. Polymorphic variants in SOST , PTH , FGF2 , FDPS , GGPS1 , and LRP5 genes were determined using PCR analysis with TaqMan probes (Thermo Scientific). Results In total, 201 women with BPs therapy were included in the study. No statistically significant differences were observed in age, age at menopause, weight, height, BMI and baseline BMD levels between responders (122 subjects) and non-responders (79 subjects). As single markers, the SOST rs1234612 T/T (OR = 2.3; P = 0.02), PTH rs7125774 T/T (OR = 2.8, P = 0.0009), FDPS rs2297480 G/G (OR = 29.3, P = 2.2×10 −7 ), and GGPS1 rs10925503 C/C+C/T (OR = 2.9; P = 0.003) gene variants were over-represented in non-responders group. No significant association between FGF2 rs6854081 and LRP5 rs3736228 gene variants and response to BPs treatment was observed. The carriers of T-T-G-C allelic combination (constructed from rs1234612, rs7125774, rs2297480, and rs10925503) were predisposed to negative response to BPs treatment (OR = 4.9, 95% CI 1.7–14.6, P = 0.005). The C-C-T-C combination was significantly over-represented in responders (OR = 0.1, 95% CI 0.1–0.5, P = 0.006). Conclusions ...
Background and objectives: One of the greatest challenges facing the healthcare of the aging population is frailty. There is growing scientific evidence that gait assessment using wearable sensors could be used for prefrailty and frailty screening. The purpose of this study was to examine the ability of a wearable sensor-based assessment of gait to discriminate between frailty levels (robust, prefrail, and frail). Materials and methods: 133 participants (≥60 years) were recruited and frailty was assessed using the Fried criteria. Gait was assessed using wireless inertial sensors attached by straps on the thighs, shins, and feet. Between-group differences in frailty were assessed using analysis of variance. Associations between frailty and gait parameters were assessed using multinomial logistic models with frailty as the dependent variable. We used receiver operating characteristic (ROC) curves to calculate the area under the curve (AUC) to estimate the predictive validity of each parameter. The cut-off values were calculated based on the Youden index. Results: Frailty was identified in 37 (28%) participants, prefrailty in 66 (50%), and no Fried criteria were found in 30 (23%) participants. Gait speed, stance phase time, swing phase time, stride time, double support time, and cadence were able to discriminate frailty from robust, and prefrail from robust. Stride time (AUC = 0.915), stance phase (AUC = 0.923), and cadence (AUC = 0.930) were the most sensitive parameters to separate frail or prefrail from robust. Other gait parameters, such as double support, had poor sensitivity. We determined the value of stride time (1.19 s), stance phase time (0.68 s), and cadence (101 steps/min) to identify individuals with prefrailty or frailty with sufficient sensitivity and specificity. Conclusions: The results of our study show that gait analysis using wearable sensors could discriminate between frailty levels. We were able to identify several gait indicators apart from gait speed that distinguish frail or prefrail from robust with sufficient sensitivity and specificity. If improved and adapted for everyday use, gait assessment technologies could contribute to frailty screening and monitoring.
Background: One of the greatest challenges facing the healthcare of the aging population is frailty. There is growing scientific evidence that gait assessment using wearable sensors could be used for prefrailty and frailty screening. The purpose of this study was to examine the ability of a wearable sensor-based assessment of gait to discriminate between frailty levels (robust, prefrail, and frail).Methods: 133 participants (≥ 60 years) were recruited and frailty was assessed using the Fried criteria. Gait was assessed using wireless inertial sensors attached by straps on the thighs, shins, and feet. Between-group differences in frailty were assessed using analysis of variance. Associations between frailty and gait parameters was assessed using multinomial logistic models with frailty as the dependent variable. We used receiver operating characteristic (ROC) curves to calculate the area under the curve (AUC) to estimate the predictive validity of each parameter. The cut-off values were calculated based on the Youden index.Results: Frailty was identified in 37 (28%) participants, prefrailty in 66 (50%), and no Fried criteria were found in 30 (23%) participants. Gait speed, stance phase time, swing phase time, stride time, double support time, and cadence were able to discriminate frailty from robust, and prefrail from robust. Stride time (AUC = 0.915), stance phase (AUC = 0.923), and cadence (AUC = 0.930) were the most sensitive parameters to separate frail or prefrail from robust. Other gait parameters, such as double support, had poor sensitivity. We determined the value of stride time (1.19s), stance phase time (0.68s), and cadence (101 steps/min) to identify individuals with prefrailty or frailty with sufficient sensitivity and specificity.Conclusions: The results of our study show that gait analysis using wearable sensors could discriminate between frailty levels. We were able to identify several gait indicators apart from gait speed that distinguish frail or prefrail from robust with sufficient sensitivity and specificity. If improved and adapted for everyday use, gait assessment technologies could contribute to frailty screening and monitoring.
IntroductionDespite the growing number of octogenarians, little is known about their vitamin D status and activities of daily living (ADL) relations.ObjectiveThe aim of this study was to investigate peculiarities of vitamin D and ADL and to assess their relations in octogenarians.MethodsA cross-sectional study was performed at the National Osteoporosis Centre located in Vilnius, Lithuania. Community-dwelling ambulatory persons aged ≥80 years were included. Current users of vitamin D supplements were excluded. Total 25 hydroxyvitamin D concentration in serum was measured with Cobas E411. Functional status was assessed by Katz ADL and the Lawton Instrumental Activities of Daily Living (IADL) scales. Subjects were divided into three groups according to age and into two groups according to vitamin D level. One-way analysis of variance with post hoc test was used to determine between-group comparisons. Associations between vitamin D and ADL score, and IADL score were assessed using Spearman’s correlation.ResultsThe study was performed on 153 octogenarians: 81 (52.9%) women and 72 (47.1%) men. The average age of subjects was 83.9 ± 3.2 years. Mean total 25 hydroxyvitamin D concentration was 11.2 ± 7.0 ng/ml; 137 (89.5%) persons had vitamin D deficiency, 12 (7.8%) had insufficiency, and only 4 (2.6%) persons were vitamin D sufficient. Positive weak correlation between total 25 hydroxyvitamin D and ADL score (r = 0.2, p = 0.01) and very weak correlation between total 25 hydroxyvitamin D and IADL score (r = 0.19, p = 0.02) were found. Total 25 hydroxyvitamin D level was correlated with ADL score in women (r = 0.23, p = 0.04). In the 80–84 years group ADL score correlated with total 25 hydroxyvitamin D level (r = 0.23, p = 0.02).ConclusionThe majority of investigated octogenarians had vitamin D deficiency. The level of vitamin D was associated with the ADL score. There was no association between the vitamin D level and the IADL score, although a weak correlation was found between vitamin D level and category of food preparation.
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