810 resultados para Osteoporosis. Neural networks. Antenna. Bone density
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This work holds the purpose of presenting an auxiliary way of bone density measurement through the attenuation of electromagnetic waves. In order to do so, an arrangement of two microstrip antennas with rectangular configuration has been used, operating in a frequency of 2,49 GHz, and fed by a microstrip line on a substrate of fiberglass with permissiveness of 4.4 and height of 0,9 cm. Simulations were done with silica, bone meal, silica and gypsum blocks samples to prove the variation on the attenuation level of different combinations. Because of their good reproduction of the human beings anomaly aspects, samples of bovine bone were used. They were subjected to weighing, measurement and microwave radiation. The samples had their masses altered after mischaracterization and the process was repeated. The obtained data were inserted in a neural network and its training was proceeded with the best results gathered by correct classification on 100% of the samples. It comes to the conclusion that through only one non-ionizing wave in the 2,49 GHz zone it is possible to evaluate the attenuation level in the bone tissue, and that with the appliance of neural network fed with obtained characteristics in the experiment it is possible to classify a sample as having low or high bone density
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Objective. To assess the cost-effectiveness of bone density screening programmes for osteoporosis. Study design. Using published and locally available data regarding fracture rates and treatment costs, the overall costs per fracture prevented, cost per quality of life year (QALY) saved and cost per year of life gained were estimated for different bone density screening and osteoporosis treatment programmes. Main outcome measures. Cost per fracture prevented, cost per QALY saved, and cost per year of life gained. Results. In women over the age of 50 years, the costs per fracture prevented of treating all women with hormone replacement therapy, or treating only if osteoporosis is demonstrated on bone density screening were £32,594 or £23,867 respectively. For alendronate therapy for the same groups, the costs were £171,067 and £14,067 respectively. Once the background rate of treatment with alendronate reaches 18%, bone density screening becomes cost-saving. Costs estimates per QALY saved ranged from £1,514 to £39,076 for osteoporosis treatment with alendronate following bone density screening. Conclusions. For relatively expensive medications such as alendronate, treatment programmes with prior bone density screening are far more cost effective than those without, and in some circumstances become cost-saving. Costs per QALY of life saved and per year of life gained for osteoporosis treatment with prior bone density screening compare favourably with treatment of hypertension and hypercholesterolemia.
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Background: Interest in the prevention of osteoporosis is increasing and thus there is a need for an acceptable osteoporosis prevention programme in general practice. AIM. A study was undertaken to identify a cohort of middle-aged women attending a general practice who would be eligible for a longitudinal study looking at bone mineral density, osteoporosis and the effectiveness of hormone replacement therapy. This study aimed to describe the relationship between medical and lifestyle risk factors for osteoporosis and the initial bone density measurements in this group of women. METHOD. A health visitor administered a questionnaire to women aged between 48 and 52 years registered with a Belfast general practice. The main outcome measures were menopausal status, presence of medical and lifestyle risk factors and bone mineral density measurements. RESULTS. A total of 358 women our of 472 (76%) took part in the study which was conducted in 1991 and 1992. A highly significant difference was found between the mean bone mineral density of premenopausal, menopausal and postmenopausal women within the narrow study age range, postmenopausal women having the lowest bone mineral density. A significant relationship was found between body mass index and bone mineral density, a greater bone mineral density being found among women with a higher body mass index. Risk factors such as smoking and sedentary lifestyle were common (reported by approximately one third of respondents) but a poor relationship was found between these two and all the other risk factors and bone mineral density in this age group. CONCLUSION. Risk of osteoporosis cannot be identified by the presence of risk factors in women aged between 48 and 52 years. In terms of a current prevention strategy for general practice it would be better to take a population-based approach except for those women known to be at high risk of osteoporosis: women with early menopause or those who have had an oophorectomy.
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BACKGROUND Although factors associated with the utilisation of bone density measurement (BDM) and osteoporosis treatment have been regularly assessed in the US and Canada, they have not been effectively analysed in European countries. This study assessed factors associated with the utilisation of BDM and osteoporosis medication (OM) in Switzerland. METHODS The Swiss Health Survey 2007 data included self-reported information on BDM and OM for women aged 40 years and older who were living in private households. Multivariable logistic regression analysis was used to identify sociodemographic, socioeconomic, healthcare-related and osteoporosis risk factors associated with BDM and OM utilisation. RESULTS The lifetime prevalence of BDM was 25.6% (95% CI: 24.3-26.9%) for women aged 40 years and older. BDM utilisation was associated with most sociodemographic factors, all the socioeconomic and healthcare-related factors, and with major osteoporosis risk factors analysed. The prevalence of current OM was 7.8% (95% CI: 7.0-8.6%) and it was associated with some sociodemographic and most healthcare-related factors but only with one socioeconomic factor. CONCLUSIONS In Swiss women, ever having had a BDM and current OM were low and utilisation disparities exist according to sociodemographic, socioeconomic and healthcare-related factors. This might foster further health inequalities. The reasons for these findings should be addressed in further studies of the elderly women, including those living in institutions.
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Objective: To assess the effectiveness of 12 weekly physical therapy sessions for urinary incontinence (UI) compared with a control intervention, for reducing the number of UI episodes measured with the 7-day bladder diary, at 3 months and 1 year postrandomization. Methods: A single parallel-group randomized controlled trial was conducted at one outpatient public health center, in postmenopausal women aged 55 years and over with osteoporosis or low bone density and UI. Women were randomized to physical therapy (PT) for UI or osteoporosis education. The primary outcome measure was number of leakage episodes on the 7-day bladder diary, assessed at baseline, after treatment and at 1 year. The secondary outcome measures included the pad test and disease-specific quality of life and self-efficacy questionnaires assessed at the same timepoints. Results: Forty-eight women participated (24 per group). Two participants dropped out of each group and one participant was deceased before 3-month follow-up. Intention-to-treat analysis was undertaken. At 3 months and 1 year, there was a statistically significant difference in the number of leakage episodes on the 7-day bladder diary (3 mo: P = 0.04; 1 y: P = 0.01) in favor of the PT group. The effect size was 0.34 at 1 year. There were no harms reported. Conclusions: After a 12-week course of PT once per week for UI, PT group participants had a 75% reduction in weekly median number of leakage episodes, whereas the control group's condition had no improvement. At 1 year, the PT group participants maintained this improvement, whereas the control group's incontinence worsened.
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Objective: To assess the effectiveness of 12 weekly physical therapy sessions for urinary incontinence (UI) compared with a control intervention, for reducing the number of UI episodes measured with the 7-day bladder diary, at 3 months and 1 year postrandomization. Methods: A single parallel-group randomized controlled trial was conducted at one outpatient public health center, in postmenopausal women aged 55 years and over with osteoporosis or low bone density and UI. Women were randomized to physical therapy (PT) for UI or osteoporosis education. The primary outcome measure was number of leakage episodes on the 7-day bladder diary, assessed at baseline, after treatment and at 1 year. The secondary outcome measures included the pad test and disease-specific quality of life and self-efficacy questionnaires assessed at the same timepoints. Results: Forty-eight women participated (24 per group). Two participants dropped out of each group and one participant was deceased before 3-month follow-up. Intention-to-treat analysis was undertaken. At 3 months and 1 year, there was a statistically significant difference in the number of leakage episodes on the 7-day bladder diary (3 mo: P = 0.04; 1 y: P = 0.01) in favor of the PT group. The effect size was 0.34 at 1 year. There were no harms reported. Conclusions: After a 12-week course of PT once per week for UI, PT group participants had a 75% reduction in weekly median number of leakage episodes, whereas the control group's condition had no improvement. At 1 year, the PT group participants maintained this improvement, whereas the control group's incontinence worsened.
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Context: Osteoporosis is a common, highly heritable condition that causes substantial morbidity and mortality, the etiopathogenesis of which is poorly understood. Genetic studies are making increasingly rapid progress in identifying the genes involved. Evidence Acquisition and Synthesis: In this review, we will summarize the current understanding of the genetics of osteoporosis based on publications from PubMed from the year 1987 onward. Conclusions: Most genes involved in osteoporosis identified to date encode components of known pathways involved in bone synthesis or resorption, but as the field progresses, new pathways are being identified. Only a small proportion of the total genetic variation involved in osteoporosis has been identified, and new approaches will be required to identify most of the remaining genes.
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Genetic factors are known to influence both the peak bone mass and probably the rate of change in bone density. A range of regulatory and structural genes has been proposed to be involved including collagen 1α1 (COL1A1), the estrogen receptor (ER), and the vitamin D receptor (VDR), but the actual genes involved are uncertain. We therefore studied the role of the COL1A1 and VDR loci in control of bone density by linkage in 45 dizygotic twin pairs and 29 nuclear families comprising 120 individuals. The influences on bone density of polymorphisms of COL1A1, VDR, and ER were studied by association both cross-sectionally and longitudinally in 193 elderly postmenopausal women (average age, 69 years) over a mean follow-up time of 6.3 years. Weak linkage of the COL1A1 locus with bone density was observed in both twins and families (p = 0.02 in both data sets), confirming previous observations of linkage of this locus with bone density. Association between the MscI polymorphism of COL1A1 and rate of lumbar spine bone loss was observed with significant gene-environment interaction related to dietary calcium intake (p = 0.0006). In the lowest tertile of dietary calcium intake, carriers of "s" alleles lost more bone than "SS" homozygotes (p = 0.01), whereas the opposite was observed in the highest dietary calcium intake (p = 0.003). Association also was observed between rate of bone loss at both the femoral neck and the lumbar spine and the TaqI VDR polymorphism (p = 0.03). This association was strongest in those in the lowest tertile of calcium intake, also suggesting the presence of gene-environment interaction involving dietary calcium and VDR, influencing bone turnover. No significant association was observed between the PvuII ER polymorphism alone or in combination with VDR or COL1A1 genotypes, with either bone density or its rate of change. These data support the involvement of COL1A1 in determination of bone density and the interaction of both COL1A1 and VDR with calcium intake in regulation of change of bone density over time.
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Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.
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Phyto-oestrogens have been associated with a decreased risk for osteoporosis, but results from intervention and observational studies in Western countries have been inconsistent. In the present study, we investigated the association between habitual phyto-oestrogen intake and broadband ultrasound attenuation (BUA) of the calcanaeum as a marker of bone density. We collected 7 d records of diet, medical history and demographic and anthropometric data from participants (aged 45–75 years) in the European Prospective Investigation into Cancer-Norfolk study. Phyto-oestrogen (biochanin A, daidzein, formononetin; genistein, glycitein; matairesinol; secoisolariciresinol; enterolactone; equol) intake was determined using a newly developed food composition database. Bone density was assessed using BUA of the calcanaeum. Associations between bone density and phyto-oestrogen intake were investigated in 2580 postmenopausal women who were not on hormone replacement therapy and 4973 men. Median intake of total phyto-oestrogens was 876 (interquartile range 412) μg/d in postmenopausal women and 1212 (interquartile range 604) μg/d in men. The non-soya isoflavones formononetin and biochanin A were marginally significant or significantly associated with BUA in postmenopausal women (β = 1·2; P < 0·1) and men (β = 1·2; P < 0·05), respectively; enterolignans and equol were positively associated with bone density in postmenopausal women, but this association became non-significant when dietary Ca was added to the model. In the lowest quintile of Ca intake, soya isoflavones were positively associated with bone density in postmenopausal women (β = 1·4; P < 0·1). The present results therefore suggest that non-soya isoflavones are associated with bone density independent of Ca, whereas the association with soya or soya isoflavones is affected by dietary Ca.
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This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)