Unraveling Cardiovascular Risk in Renal Patients: A New Take on Old Tale

Chronic kidney disease (CKD), defined by an estimated glomerular filtration rate <60 ml/min/1.73 m(2) and/or an increase in urine protein excretion (i.e., albuminuria), is an important public health problem. Prevalence and incidence of CKD have risen by 87 and 89%, worldwide, over the last three decades. The onset of either albuminuria and eGFR reduction has found to predict higher cardiovascular (CV) risk, being this association strong, independent from traditional CV risk factors and reproducible across different setting of patients. Indeed, this relationship is present not only in high risk cohorts of CKD patients under regular nephrology care and in those with hypertension or type 2 diabetes, but also in general, otherwise healthy population. As underlying mechanisms of damage, it has hypothesized and partially proved that eGFR reduction and albuminuria can directly promote endothelial dysfunction, accelerate atherosclerosis and the deleterious effects of hypertension. Moreover, the predictive accuracy of risk prediction models was consistently improved when eGFR and albuminuria have been added to the traditional CV risk factors (i.e., Framingham risk score). These important findings led to consider CKD as an equivalent CV risk. Although it is hard to accept this definition in absence of additional reports from scientific Literature, a great effort has been done to reduce the CV risk in CKD patients. A large number of clinical trials have tested the effect of drugs on CV risk reduction. The targets used in these trials were different, including blood pressure, lipids, albuminuria, inflammation, and glucose. All these trials have determined an overall better control of CV risk, performed by clinicians. However, a non-negligible residual risk is still present and has been attributed to: (1) missed response to study treatment in a consistent portion of patients, (2) role of many CV risk factors in CKD patients not yet completely investigated. These combined observations provide a strong argument that kidney measures should be regularly included in individual prediction models for improving CV risk stratification. Further studies are needed to identify high risk patients and novel therapeutic targets to improve CV protection in CKD patients.