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Driving Type 2 Diabetes Risk Scores into Clinical Practice: Performance Analysis in Hospital Settings

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Driving Type 2 Diabetes Risk Scores into Clinical Practice: Performance Analysis in Hospital Settings

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dc.contributor.author Martinez-Millana, Antonio es_ES
dc.contributor.author Argente-Pla, María es_ES
dc.contributor.author Valdivieso Martinez, Bernardo es_ES
dc.contributor.author Traver Salcedo, Vicente es_ES
dc.contributor.author Merino-Torres, Juan Francisco es_ES
dc.date.accessioned 2021-01-12T04:31:48Z
dc.date.available 2021-01-12T04:31:48Z
dc.date.issued 2019-01 es_ES
dc.identifier.uri http://hdl.handle.net/10251/158677
dc.description.abstract [EN] Electronic health records and computational modelling have paved the way for the development of Type 2 Diabetes risk scores to identify subjects at high risk. Unfortunately, few risk scores have been externally validated, and their performance can be compromised when routine clinical data is used. The aim of this study was to assess the performance of well-established risk scores for Type 2 Diabetes using routinely collected clinical data and to quantify their impact on the decision making process of endocrinologists. We tested six risk models that have been validated in external cohorts, as opposed to model development, on electronic health records collected from 2008-2015 from a population of 10,730 subjects. Unavailable or missing data in electronic health records was imputed using an existing validated Bayesian Network. Risk scores were assessed on the basis of statistical performance to differentiate between subjects who developed diabetes and those who did not. Eight endocrinologists provided clinical recommendations based on the risk score output. Due to inaccuracies and discrepancies regarding the exact date of Type 2 Diabetes onset, 76 subjects from the initial population were eligible for the study. Risk scores were useful for identifying subjects who developed diabetes (Framingham risk score yielded a c-statistic of 85%), however, our findings suggest that electronic health records are not prepared to massively use this type of risk scores. Use of a Bayesian Network was key for completion of the risk estimation and did not affect the risk score calculation (p > 0.05). Risk score estimation did not have a significant effect on the clinical recommendation except for starting pharmacological treatment (p = 0.004) and dietary counselling (p = 0.039). Despite their potential use, electronic health records should be carefully analyzed before the massive use of Type 2 Diabetes risk scores for the identification of high-risk subjects, and subsequent targeting of preventive actions. es_ES
dc.description.sponsorship MOSAIC project, funded by the European Commission Grant nr. FP7-ICT 600914. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Journal of Clinical Medicine es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Risk scores es_ES
dc.subject Prediction es_ES
dc.subject T2DM es_ES
dc.subject Clinical data es_ES
dc.subject Screening es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Driving Type 2 Diabetes Risk Scores into Clinical Practice: Performance Analysis in Hospital Settings es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/jcm8010107 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/600914/EU/MOSAIC - MOdels and Simulation techniques for discovering diAbetes Influence faCtors/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Martinez-Millana, A.; Argente-Pla, M.; Valdivieso Martinez, B.; Traver Salcedo, V.; Merino-Torres, JF. (2019). Driving Type 2 Diabetes Risk Scores into Clinical Practice: Performance Analysis in Hospital Settings. Journal of Clinical Medicine. 8(1):1-19. https://doi.org/10.3390/jcm8010107 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/jcm8010107 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 8 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 2077-0383 es_ES
dc.identifier.pmid 30658456 es_ES
dc.identifier.pmcid PMC6352264 es_ES
dc.relation.pasarela S\376366 es_ES
dc.contributor.funder European Commission es_ES
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