Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/42242
Título: A probabilistic model for cushing's syndrome screening in at-risk populations: a prospective multicenter study
Autores/as: León-Justel, Antonio
Madrazo-Atutxa, Ainara
Alvarez-Rios, Ana I.
Infantes-Fontán, Rocio
Garcia-Arnés, Juan A.
Lillo-Muñoz, Juan A.
Aulinas, Anna
Urgell-Rull, Eulàlia
Boronat, Mauro 
Sánchez-De-Abajo, Ana 
Fajardo-Montañana, Carmen
Ortuño-Alonso, Mario
Salinas-Vert, Isabel
Granada, María L.
Cano, David A.
Leal-Cerro, Alfonso
Clasificación UNESCO: 3205 Medicina interna
320502 Endocrinología
Palabras clave: Cushing’s syndrome
Fecha de publicación: 2016
Publicación seriada: Journal of Clinical Endocrinology and Metabolism 
Resumen: Context: Cushing's syndrome (CS) is challenging to diagnose. Increased prevalence of CS in specific patient populations has been reported, but routine screening for CS remains questionable. To decrease the diagnostic delay and improve disease outcomes, simple new screening methods for CS in at-risk populations are needed. Objective: To develop and validate a simple scoring system to predict CS based on clinical signs and an easy-to-use biochemical test. Design: Observational, prospective, multicenter. Setting: Referral hospital. Patients: A cohort of 353 patients attending endocrinology units for outpatient visits. Interventions: All patients were evaluated with late-night salivary cortisol (LNSC) and a low-dose dexamethasone suppression test for CS. Main Outcome Measures: Diagnosis or exclusion of CS. Results: Twenty-six cases of CS were diagnosed in the cohort. A risk scoring system was developed by logistic regression analysis, and cutoff values were derived from a receiver operating characteristic curve. This risk score included clinical signs and symptoms (muscular atrophy, osteoporosis, and dorsocervical fat pad) and LNSC levels. The estimated area under the receiver operating characteristic curve was 0.93, with a sensitivity of 96.2% and specificity of 82.9%. Conclusions: We developed a risk score to predict CS in an at-risk population. This score may help to identify at-risk patients in non-endocrinological settings such as primary care, but external validation is warranted.
URI: http://hdl.handle.net/10553/42242
ISSN: 0021-972X
DOI: 10.1210/jc.2016-1673
Fuente: Journal of Clinical Endocrinology and Metabolism[ISSN 0021-972X],v. 101, p. 3747-3754
Colección:Artículos
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