Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/50723
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dc.contributor.authorNavarro Rodríguez, María del Carmenen_US
dc.contributor.authorSaavedra Santana, Pedroen_US
dc.contributor.authorGómez De Tejada Romero, Mª Jesúsen_US
dc.contributor.authorSuárez, Mercedesen_US
dc.contributor.authorHernández, Diegoen_US
dc.contributor.authorSosa-Henríquez, Manuelen_US
dc.date.accessioned2018-11-24T18:20:27Z-
dc.date.available2018-11-24T18:20:27Z-
dc.date.issued2011en_US
dc.identifier.issn1094-6950en_US
dc.identifier.urihttp://hdl.handle.net/10553/50723-
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 of QUS that would maximize the predictive ability of this technique to discriminate subjects with fragility fractures. A cross-sectional analysis was made of a cohort of 1132 postmenopausal women with a mean age of 58 yr. A total of 361 women (31.9%) presented with a history of osteoporotic fracture. Most fractures (74.1%) were nonvertebral. For all patients, a questionnaire of osteoporosis risk factors 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 assessed. Spinal radiographs were assessed for fractures and historical nonvertebral fragility fractures. Sensitivity, specificity, predictive values, likelihood ratios, and receiver operator characteristic (ROC) curve QUS values were calculated using the optimal threshold identified in the classification and regression trees (CART) models. Cutoff values calculated from the best CART model (i.e., a quantitative ultrasound index (QUI) greater than 88.5% in women aged 58 yr or older) yielded 88.8% (95% confidence interval [CI]: 81.4-93.5) for sensitivity, a negative predictive value of 93.8 (95% CI: 89.4-96.4), and 70.4% (95% CI: 64.6-75.7) for specificity. This cutoff value would obviate the need to perform DXA in 43.1% of the population. The area under the ROC curve of the best model was 0.8363 (95% CI: 0.8249-0.8477). In conclusion, QUS was shown to discriminate between women with and without a history of fragility fracture and constitutes a useful tool for assessing fracture risk. The application of decision trees (CART analyses) was helpful to define the optimal threshold QUS values.en_US
dc.languageengen_US
dc.relation.ispartofJournal of Clinical Densitometryen_US
dc.sourceJournal of Clinical Densitometry [ISSN 1094-6950],v. 14, p. 492-498 (Octubre 2011)en_US
dc.subject32 Ciencias médicasen_US
dc.subject3205 Medicina internaen_US
dc.subject.otherClinical Risk-Factorsen_US
dc.subject.otherHip Fractureen_US
dc.subject.otherVertebral Fracturesen_US
dc.subject.otherBone Densitometryen_US
dc.subject.otherOsteoporosisen_US
dc.subject.otherPopulationen_US
dc.subject.otherPredictionen_US
dc.subject.otherMenen_US
dc.subject.otherAssociationen_US
dc.subject.otherAttenuationen_US
dc.titleDiscriminative ability of heel quantitative ultrasound in postmenopausal women with prevalent low-trauma fractures: application of optimal threshold cutoff values using CART modelsen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.jocd.2011.06.008en_US
dc.identifier.scopus82855170844-
dc.identifier.isi000296952400018-
dc.contributor.authorscopusid35345286600-
dc.contributor.authorscopusid56677724200-
dc.contributor.authorscopusid6507688533-
dc.contributor.authorscopusid7202996105-
dc.contributor.authorscopusid7201790739-
dc.contributor.authorscopusid7004134221-
dc.description.lastpage498en_US
dc.description.firstpage492en_US
dc.relation.volume14en_US
dc.investigacionCiencias de la Saluden_US
dc.type2Artículoen_US
dc.contributor.daisngid506996-
dc.contributor.daisngid8838450-
dc.contributor.daisngid7636995-
dc.contributor.daisngid5833525-
dc.contributor.daisngid1398569-
dc.contributor.daisngid34938799-
dc.description.numberofpages7en_US
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.coverdateOctubre 2011en_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-MEDen_US
dc.description.sjr1,018-
dc.description.jcr1,295-
dc.description.sjrqQ1-
dc.description.jcrqQ4-
dc.description.scieSCIE-
item.grantfulltextnone-
item.fulltextSin texto completo-
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.orcid0000-0002-7780-2277-
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.fullNameNavarro Rodríguez, María del Carmen-
crisitem.author.fullNameSaavedra Santana, Pedro-
crisitem.author.fullNameGómez De Tejada Romero, Mª Jesús-
crisitem.author.fullNameSosa Henríquez,Manuel José-
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