• Ana Lidia Medrano Navarro, Alicia Justel Enríquez, Javier Alameda Serrano, Yolanda Blasco Lamarca, Daniel Sáenz Abad, and José Antonio Gimeno Orna.
• Unidad de Endocrinología y Nutrición, Hospital de Barbastro, Barbastro, Huesca, España. Electronic address: analidia.medrano@gmail.com.
• Med Clin (Barc). 2019 Oct 11; 153 (7): 263-269.

Background And AimsOur aim was to assess the usefulness of KDIGO 2012 risk classification to predict total and cardiovascular mortality in type 2 diabetes mellitus (DM2).Material And MethodsProspective cohort study that included DM2 patients. Clinical end-points were total and cardiovascular mortality. The main predictive variable was KDIGO risk classification, which is a combination of urinary albumin excretion and glomerular filtration rate. The predictive value was evaluated by the integrated discrimination improvement (IDI) index.Results453 patients (39.3% males, aged 64.9 [SD 9.3] and with a mean diabetes duration of 10.4 [SD 7.5] years) were included. During a median follow-up of 13 years, mortality rates per 1000 patients/year (26.5 vs. 45.1 vs. 79,2 vs. 109,8; p<0,001) and cardiovascular mortality (8.1 vs. 17.4 vs. 24.7 vs. 57.5; p<0,001) were progressively increased in successive KDIGO categories. In the multivariate analysis, there was also a progressive increase of mortality risk (HR[moderate risk]=1.29; HR[high risk])=1.83; HR[very high risk]=2.15; p=.016) and cardiovascular mortality risk (HR[moderate risk]=1.73; HR[high risk]=2.27; HR[very high risk]=4.22; p=.007) in the successive categories. KDIGO classification was able to improve the mortality risk prediction (IDI=0.00888; p=.047) and cardiovascular mortality risk prediction (IDI=0.01813; p=.035).ConclusionsKDIGO risk classification can effectively stratify total and cardiovascular mortality risk in DM2 patients.Copyright © 2019 Elsevier España, S.L.U. All rights reserved.

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