A clinical-genetic approach to assessing cardiovascular risk in patients with CKD
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AuthorRodrigo Calabia, Emilio; Pich, Sara; Subirana, Isaac; Fernández Fresnedo, Gema; Barreda, Paloma; Ferrer Costa, Carles; Martín de Francisco Hernández, Ángel Luis; Salas, Eduardo; Elosua, Roberto; Arias Rodríguez, Manuel
Background: Coronary heart disease (CHD) is the primary cause of death in individuals with chronic kidney disease (CKD), but current equations for assessing coronary risk have low accuracy in this group. We have reported that the addition of a genetic risk score (GRS) to the Framingham risk function improved its predictive capacity in the general population. The aims of this study were to evaluate the association between this GRS and coronary events in the CKD population and to determine whether the addition of the GRS to coronary risk prediction functions improves the estimation of coronary risk at the earliest possible stages of kidney disease. Methods: A total of 632 CKD patients, aged 35?74 years, who had Stage 4?5 CKD, were on dialysis, had a functioning renal transplant or had returned to dialysis after transplant failure were included and followed up for a mean of 9.3 years. The transitions between disease states and the development of coronary events were registered. The increase in predictive ability that was obtained by including the GRS was measured as the improvement in the C-statistic and as the net reclassification index. Results: The GRS was independently associated with the risk of CHD (hazards ratio 1.34; 95% confidence interval 1.04?1.71; P¼0.022), especially in Stages 4 and 5 CKD, and kidney transplant patients. A coronary risk prediction function that incorporated chronic kidney disease (CKD) disease state, age, sex and the GRS had significantly greater predictive capacity (AUC 70.1, P¼0.01) and showed good reclassification (net reclassification improvement 28.6). Conclusion: This new function, combining genetic and clinical data, identifies CKD patients with a high risk of coronary events more accurately, allowing us to prevent such events more effectively.