Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/50720
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dc.contributor.authorDel Carmen Navarro, Maríaen_US
dc.contributor.authorSaavedra Santana, Pedroen_US
dc.contributor.authorGómez-de-Tejada, María Jesúsen_US
dc.contributor.authorSuárez, Mercedesen_US
dc.contributor.authorHernández, Diegoen_US
dc.contributor.authorSosa-Henríquez, Manuelen_US
dc.date.accessioned2018-11-24T18:18:57Z-
dc.date.available2018-11-24T18:18:57Z-
dc.date.issued2012en_US
dc.identifier.issn0171-967Xen_US
dc.identifier.urihttp://hdl.handle.net/10553/50720-
dc.description.abstractQuantitative ultrasound (QUS) of the heel has been proposed as a screening tool to evaluate the bone status and risk of osteoporotic fragility fractures. The aim of this study was to define threshold values that would maximize the predictive ability of QUS to discriminate subjects with vertebral fractures using the classification and regression trees (CART) models. A cross-sectional analysis was made of a cohort of 1,132 postmenopausal women with a mean age of 58 years. A total of 205 women (18.1 %) presented with a history of vertebral fracture. For all patients, a questionnaire of osteoporosis risk factors was given and measurements of the heel QUS and bone mineral density at the lumbar spine and the proximal femur, obtained by dual-energy X-ray absorptiometry (DXA), were made. Spinal radiographs were assessed for vertebral fractures. Sensitivity, specificity, predictive values, likelihood ratios, and receiver operator characteristics (ROC) curve QUS values were calculated using the optimal threshold identified in the CART models. Cutoff values calculated from best CART model (i.e., a QUS index > 90.5 %) yielded a sensitivity of 80.3 % (95 % CI 69.2-88.1), a negative predictive value of 94 % (95 % CI 90.1-96.5), and a specificity of 68.8 % (95 % CI 63.3-73.8). This cutoff value would obviate the need to perform DXA in 32.8 % of the women of our population at risk for vertebral fractures. The area under the ROC curve of the best model was 0.8071. QUS was shown to discriminate between women with and without a history of vertebral fracture and constitutes a useful tool for assessing vertebral fracture risk. The application of decision trees (CART analyses) was helpful to define the optimal threshold QUS values.en_US
dc.languagespaen_US
dc.publisher0171-967X-
dc.relation.ispartofCalcified Tissue Internationalen_US
dc.sourceCalcified Tissue International[ISSN 0171-967X],v. 91, p. 114-120en_US
dc.subject.otherBone-Mineral Densityen_US
dc.subject.otherX-Ray Absorptiometryen_US
dc.subject.otherPopulation-Based Sampleen_US
dc.subject.otherHip Fractureen_US
dc.subject.otherOlder Womenen_US
dc.subject.otherOsteoporosisen_US
dc.subject.otherRisken_US
dc.subject.otherDensitometryen_US
dc.subject.otherPredictionen_US
dc.subject.otherMenen_US
dc.titleDiscriminative ability of heel quantitative ultrasound in postmenopausal women with prevalent vertebral fractures: application of optimal threshold cutoff values using classification and regression tree modelsen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1007/s00223-012-9616-3en_US
dc.identifier.scopus84865972639-
dc.identifier.isi000306438100002-
dc.contributor.authorscopusid54390903000-
dc.contributor.authorscopusid56677724200-
dc.contributor.authorscopusid6507688533-
dc.contributor.authorscopusid7202996105-
dc.contributor.authorscopusid7201790739-
dc.contributor.authorscopusid7004134221-
dc.description.lastpage120en_US
dc.description.firstpage114en_US
dc.relation.volume91en_US
dc.type2Artículoen_US
dc.contributor.daisngid506996-
dc.contributor.daisngid8838450-
dc.contributor.daisngid7636995-
dc.contributor.daisngid5833525-
dc.contributor.daisngid1398569-
dc.contributor.daisngid574595-
dc.utils.revisionen_US
dc.contributor.wosstandardWOS:Navarro, MD-
dc.contributor.wosstandardWOS:Saavedra, P-
dc.contributor.wosstandardWOS:Gomez-de-Tejada, MJ-
dc.contributor.wosstandardWOS:Suarez, M-
dc.contributor.wosstandardWOS:Hernandez, D-
dc.contributor.wosstandardWOS:Sosa, M-
dc.date.coverdateAgosto 2012en_US
dc.identifier.ulpgcen_US
dc.description.sjr1,175
dc.description.jcr2,495
dc.description.sjrqQ1
dc.description.jcrqQ3
dc.description.scieSCIE
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptGIR Estadística-
crisitem.author.deptDepartamento de Matemáticas-
crisitem.author.deptGIR SIANI: Ingeniería biomédica aplicada a estimulación neural y sensorial-
crisitem.author.deptIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.orcid0000-0003-1681-7165-
crisitem.author.orcid0000-0001-6845-2933-
crisitem.author.parentorgDepartamento de Matemáticas-
crisitem.author.parentorgIU Sistemas Inteligentes y Aplicaciones Numéricas-
crisitem.author.fullNameSaavedra Santana, Pedro-
crisitem.author.fullNameSosa Henríquez,Manuel José-
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