Major bleeding risk prediction using Chronic Kidney Disease Epidemiology Collaboration and Modification of Diet in Renal Disease equations in acute coronary syndrome.

Published

Journal Article

BACKGROUND: Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations estimate glomerular filtration rate more accurately than the Modification of Diet in Renal Disease (MDRD) Study equation. Our aim was to evaluate whether CKD-EPI equations based on serum creatinine and/or cystatin C (CysC) predict risk for major bleeding (MB) more accurately than the MDRD Study equation in patients with non-ST-segment elevation acute coronary syndromes (ACS). MATERIALS AND METHODS: Three hundred and fifty consecutive subjects with non-ST-segment elevation ACS (68 ± 12 years, 70% male) were studied. Glomerular filtration rate was estimated using the CKD-EPI and MDRD Study equations. The primary endpoint was the occurrence of MB during the follow-up, which was defined according to the Bleeding Academic Research Consortium Definition criteria as bleeding types 3-5. RESULTS: During the median follow-up of 589 days (interquartile range, 390-986), 27 patients had MB (0.04% events per person year). Patients with MB had worse kidney function parameters, regardless of the estimating equation used (P < 0.001). After multivariate Cox regression adjustment, both CysC-based CKD-EPI equations were independent predictors of MB (CKD-EPI(creatinine-cystatin) C per mL/min/1.73 m(2), HR = 0.973 (95%CI 0.955-0.991; P = 0.003) and CKD-EPI(cystatin) C per mL/min/1.73 m(2), HR = 0.976 (95%CI 0.976-0.992; P = 0.003), while the CKD-EPI(creatinine) and MDRD equations did not achieve statistical significance. Both CKD-EPI(creatine-cystatin) C and CKD-EPI(cystatin) C were associated with a significant improvement in MB risk reclassification. CONCLUSIONS: In this cohort of non-ST-segment elevation ACS patients with relatively preserved renal function, both CysC-based CKD-EPI equations improved ability to predict risk for MB and were superior to other equations for this application.

Full Text

Duke Authors

Cited Authors

  • Flores-Blanco, PJ; López-Cuenca, Á; Januzzi, JL; Marín, F; Sánchez-Martínez, M; Quintana-Giner, M; Romero-Aniorte, AI; Valdés, M; Manzano-Fernández, S

Published Date

  • April 2015

Published In

Volume / Issue

  • 45 / 4

Start / End Page

  • 385 - 393

PubMed ID

  • 25661774

Pubmed Central ID

  • 25661774

Electronic International Standard Serial Number (EISSN)

  • 1365-2362

Digital Object Identifier (DOI)

  • 10.1111/eci.12418

Language

  • eng

Conference Location

  • England