Osteoporose nas regiões Norte e Nordeste do Brasil: estimativas do número de anos vividos com essa enfermidade pelos idosos/ Osteoporosis in the North and Northeast regions of Brazil: estimates of the number of years lived with this disease by the elderly

Bomfim, Wanderson Costa; Camargos, Mirela Castro Santos

doi:10.34119/bjhrv4n1-309

Cited by 2 publications

(3 citation statements)

References 22 publications

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“…39675020.0.0000.5292/2020, and in accordance with the Helsinki Accords (as amended in 2004). The calculation of the sample size was determined by the following equation: where: P = proportion expected to test positive for osteoporosis (24%) 27 , D = half-range of the confidence interval (maximum acceptable error of plus or minus 0.04). Z = 1.96 (for α = 0.05 and 95%CI).…”

Section: Methodsmentioning

confidence: 99%

“…The proportion P = 24% 27 used reflects the expectation of a positive osteoporosis test for the general population living in the north and northeast regions of Brazil. The sample ensured an alpha probability below 0.05, specifically 0.0449.…”

Section: Methodsmentioning

confidence: 99%

“…where: P = proportion expected to test positive for osteoporosis (24%) 27 , D = half-range of the confidence interval (maximum acceptable error of plus or minus 0.04). Z = 1.96 (for α = 0.05 and 95%CI).…”

Section: Methodsmentioning

confidence: 99%

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Osteoporosis screening using machine learning and electromagnetic waves

Albuquerque

Carvalho

Cruz

et al. 2023

Sci Rep

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Osteoporosis is a disease characterized by impairment of bone microarchitecture that causes high socioeconomic impacts in the world because of fractures and hospitalizations. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing the disease, access to DXA in developing countries is still limited due to its high cost, being present only in specialized hospitals. In this paper, we analyze the performance of Osseus, a low-cost portable device based on electromagnetic waves that measures the attenuation of the signal that crosses the medial phalanx of a patient’s middle finger and was developed for osteoporosis screening. The analysis is carried out by predicting changes in bone mineral density using Osseus measurements and additional common risk factors used as input features to a set of supervised classification models, while the results from DXA are taken as target (real) values during the training of the machine learning algorithms. The dataset consisted of 505 patients who underwent osteoporosis screening with both devices (DXA and Osseus), of whom 21.8% were healthy and 78.2% had low bone mineral density or osteoporosis. A cross-validation with k-fold = 5 was considered in model training, while 20% of the whole dataset was used for testing. The obtained performance of the best model (Random Forest) presented a sensitivity of 0.853, a specificity of 0.879, and an F1 of 0.859. Since the Random Forest (RF) algorithm allows some interpretability of its results (through the impurity check), we were able to identify the most important variables in the classification of osteoporosis. The results showed that the most important variables were age, body mass index, and the signal attenuation provided by Osseus. The RF model, when used together with Osseus measurements, is effective in screening patients and facilitates the early diagnosis of osteoporosis. The main advantages of such early screening are the reduction of costs associated with exams, surgeries, treatments, and hospitalizations, as well as improved quality of life for patients.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Osteoporosis screening using machine learning and electromagnetic waves

Albuquerque

Carvalho

Cruz

et al. 2023

Sci Rep

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Aspectos Gerais Dos Marcadores Bioquímicos Presentes Nas Principais Doenças Osteometabólicas: Uma Revisão Integrativa Da Literatura

Sampaio,

Medeiros,

Diniz

et al. 2024

Rev. Contemp.

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O tecido ósseo além de possuir funções básicas como a sustentação do esqueleto e proteção dos órgãos vitais, ainda é caracterizado como um tecido metabolicamente ativo graças às atividades de células características do próprio sistema, responsáveis pela formação e manutenção, a saber, os osteoclastos, osteoblastos e os osteócitos. Com os crescentes avanços das novas tecnologias e métodos diagnósticos, os marcadores bioquímicos vêm ganhando cada vez mais notoriedade e aplicabilidade no diagnóstico de inúmeras patologias, bem como auxiliam nas decisões e condutas terapêuticas, no acompanhamento da regressão, progressão ou na fase estacionária da doença, a depender do estágio a qual o paciente encontra-se. De forma geral, o presente trabalho detém como objetivo principal promover o conhecimento de forma sucinta, porém consistente sobre as principais doenças osteometabólicas de maior prevalência, assim como os seus respectivos diagnósticos, principalmente os de cunho laboratorial, dos quais serão observados marcadores bioquímicos importantes e suas respectivas alterações. Desse modo, serão apontados os aspectos gerais sobre os marcadores bioquímicos predominantes nas principais doenças osteometabólicas. O presente trabalho deriva de uma pesquisa de revisão integrativa da literatura realizada nas seguintes plataformas de pesquisa: BIREME, LILACS, MEDLINE, SCIELO, acervos das bibliotecas virtuais das Universidades Públicas do Brasil e site do Ministério da Saúde do Brasil, onde foram filtrados artigos e outros trabalhos acadêmicos escritos e publicados entre os anos de 1999 e 2023.

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Osteoporose nas regiões Norte e Nordeste do Brasil: estimativas do número de anos vividos com essa enfermidade pelos idosos/ Osteoporosis in the North and Northeast regions of Brazil: estimates of the number of years lived with this disease by the elderly

Cited by 2 publications

References 22 publications

Osteoporosis screening using machine learning and electromagnetic waves

Osteoporosis screening using machine learning and electromagnetic waves

Aspectos Gerais Dos Marcadores Bioquímicos Presentes Nas Principais Doenças Osteometabólicas: Uma Revisão Integrativa Da Literatura

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