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

Fecha de publicación: 01/01/2019

Autores de IIS La Fe

Antonio Martínez Millana

Autor
María Argente Pla

Autor
Bernardo Valdivieso Martínez

Autor
Vicente Traver Salcedo

Autor
Juan Francisco Merino Torres

Autor

Grupos

Unidad Mixta de Investigación en Endocrinología, Nutrición y Dietética clínica

Leader

Juan Francisco Merino Torres
Unidad Mixta de Investigacion en TICs aplicadas a la reingeniería en procesos sociosanitarios (ERPSS)

Investigador Principal

María Eugenia Gas López

Abstract

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.

Datos de la publicación

ISSN/ISSNe:: 2077-0383, 2077-0383
Tipo:: Article
Páginas:: -
DOI:: 10.3390/jcm8010107

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Métricas

Filiaciones

Martinez-Millana, A:: Univ Politecn Valencia, ITACA, Camino Vera S-N, E-46022 Valencia, Spain
Argente-Pla, M:: Univ Hosp La Fe, Endocrinol & Nutr Dept, Avinguda Fernando Abril Martorell 106, Valencia 46026, Spain

Instituto de Investigación. La Fe Hlth Res Inst, Mixed Res Unit Endocrinol Nutr & Dietet, Ave Fernando Abril Martorell,Torre 106 A 7Planta, Valencia 46026, Spain
Martinez, BV:: Instituto de Investigación. Hosp Univ & Politecn La Fe, Inst Invest Sanitaria, Unidad Mixta Reingn Proc Sociosanitarios, Bulevar Sur S-N, Valencia 46026, Spain

La Fe Univ & Polytech Hosp, Home Care & Telemed Dept, Valencia 46026, Spain
Salcedo, VT:: Univ Politecn Valencia, ITACA, Camino Vera S-N, E-46022 Valencia, Spain

Instituto de Investigación. Hosp Univ & Politecn La Fe, Inst Invest Sanitaria, Unidad Mixta Reingn Proc Sociosanitarios, Bulevar Sur S-N, Valencia 46026, Spain
Merino-Torres, JF:: Univ Hosp La Fe, Endocrinol & Nutr Dept, Avinguda Fernando Abril Martorell 106, Valencia 46026, Spain

Instituto de Investigación. La Fe Hlth Res Inst, Mixed Res Unit Endocrinol Nutr & Dietet, Ave Fernando Abril Martorell,Torre 106 A 7Planta, Valencia 46026, Spain