000095075 001__ 95075
000095075 005__ 20200904094320.0
000095075 0247_ $$2doi$$a10.3390/jcm9051546
000095075 0248_ $$2sideral$$a118736
000095075 037__ $$aART-2020-118736
000095075 041__ $$aeng
000095075 100__ $$0(orcid)0000-0002-6765-8259$$aAyensa-Vázquez, José Ángel$$uUniversidad de Zaragoza
000095075 245__ $$aAgreement between Type 2 Diabetes Risk Scales in a Caucasian Population: A Systematic Review and Report
000095075 260__ $$c2020
000095075 5060_ $$aAccess copy available to the general public$$fUnrestricted
000095075 5203_ $$aEarly detection of people with undiagnosed type 2 diabetes (T2D) is an important public health concern. Several predictive equations for T2D have been proposed but most of them have not been externally validated and their performance could be compromised when clinical data is used. Clinical practice guidelines increasingly incorporate T2D risk prediction models as they support clinical decision making. The aims of this study were to systematically review prediction scores for T2D and to analyze the agreement between these risk scores in a large cross-sectional study of white western European workers. A systematic review of the PubMed, CINAHL, and EMBASE databases and a cross-sectional study in 59, 042 Spanish workers was performed. Agreement between scores classifying participants as high risk was evaluated using the kappa statistic. The systematic review of 26 predictive models highlights a great heterogeneity in the risk predictors; there is a poor level of reporting, and most of them have not been externally validated. Regarding the agreement between risk scores, the DETECT-2 risk score scale classified 14.1% of subjects as high-risk, FINDRISC score 20.8%, Cambridge score 19.8%, the AUSDRISK score 26.4%, the EGAD study 30.3%, the Hisayama study 30.9%, the ARIC score 6.3%, and the ITD score 3.1%. The lowest agreement was observed between the ITD and the NUDS study derived score (kappa = 0.067). Differences in diabetes incidence, prevalence, and weight of risk factors seem to account for the agreement differences between scores. A better agreement between the multi-ethnic derivate score (DETECT-2) and European derivate scores was observed. Risk models should be designed using more easily identifiable and reproducible health data in clinical practice.
000095075 536__ $$9info:eu-repo/grantAgreement/ES/ISCIII/RD16-0007-008
000095075 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000095075 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000095075 700__ $$aLeiva, Alfonso
000095075 700__ $$aTauler, Pedro
000095075 700__ $$aLópez-Gónzalez, Ángel Arturo
000095075 700__ $$aAguiló, Antoni
000095075 700__ $$aTomás-Salvá, Matías
000095075 700__ $$aBennasar-Veny, Miquel
000095075 7102_ $$14001$$2215$$aUniversidad de Zaragoza$$bDpto. Ciencias de la Educación$$cÁrea Didáctica y Organiz. Esc.
000095075 773__ $$g9, 5 (2020), 1546  [19 pp.]$$pJ. clin.med.$$tJOURNAL OF CLINICAL MEDICINE$$x2077-0383
000095075 8564_ $$s693062$$uhttps://zaguan.unizar.es/record/95075/files/texto_completo.pdf$$yVersión publicada
000095075 8564_ $$s501931$$uhttps://zaguan.unizar.es/record/95075/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000095075 909CO $$ooai:zaguan.unizar.es:95075$$particulos$$pdriver
000095075 951__ $$a2020-09-04-08:32:13
000095075 980__ $$aARTICLE