Fourier transform infrared (FTIR) spectroscopy as a screening tool for osteosarcopenia in community-dwelling older women.
Raysa Vanessa de Medeiros FreitasDaniel Lucas Dantas de FreitasIgor Rafael Damasceno de OliveiraCristiano Dos Santos GomesGerlane Coelho Bernardo GuerraPaulo Moreira Silva DantasTales Gomes da SilvaGustavo DuqueKassio Michell Gomes de LimaRicardo Oliveira GuerraPublished in: The journals of gerontology. Series A, Biological sciences and medical sciences (2023)
Osteosarcopenia is a complex geriatric syndrome characterized by the presence of both sarcopenia and osteopenia/osteoporosis. This condition increases rates of disability, falls, fractures, mortality and mobility impairments in older adults. The purpose of this study was to analyze the Fourier Transform Infrared (FTIR) spectroscopy diagnostic power for osteosarcopenia in community-dwelling older women (n = 64, 32 osteosarcopenic and 32 non-osteosarcopenia). FTIR is a fast and reproducible technique highly sensitive to biological tissues and a mathematical model was created using multivariate classification techniques that denoted the graphic spectra of the molecular groups. Genetic algorithm and support vector machine regression (GA-SVM) was the most feasible model, achieving 80.0% of accuracy. GA-SVM identified 15 wavenumbers responsible for class differentiation, in which several amino acids (responsible for the proper activation of the mammalian target of rapamycin) and hydroxyapatite (an inorganic bone component) were observed. Imaging tests and a low availability of instruments that allow the observation of osteosarcopenia involves high health costs for patients and restrictive indications. Therefore, FTIR can be used to diagnose osteosarcopenia due to its efficiency, low cost and to enable early detection in the geriatric services, contributing to advances in science and technology that are potential "conventional" methods in the future.
Keyphrases
- community dwelling
- low cost
- high resolution
- deep learning
- pet ct
- healthcare
- end stage renal disease
- machine learning
- public health
- bone mineral density
- single molecule
- mental health
- ejection fraction
- newly diagnosed
- primary care
- postmenopausal women
- chronic kidney disease
- patient reported outcomes
- multiple sclerosis
- physical activity
- gene expression
- cardiovascular events
- prognostic factors
- type diabetes
- climate change
- risk factors
- mass spectrometry
- human health
- risk assessment
- case report
- cardiovascular disease
- copy number
- skeletal muscle
- photodynamic therapy
- bone regeneration
- current status
- data analysis
- fluorescence imaging
- neural network