Published online Mar 26, 2023. doi: 10.4330/wjc.v15.i3.76
Peer-review started: October 2, 2022
First decision: November 25, 2022
Revised: December 31, 2022
Accepted: February 22, 2023
Article in press: February 22, 2023
Published online: March 26, 2023
Processing time: 169 Days and 14.5 Hours
Chronic kidney disease (CKD) patients face an unacceptably high morbidity and mortality, mainly from cardiovascular diseases. Diabetes mellitus, arterial hypertension and dyslipidemia are highly prevalent in CKD patients. Established therapeutic protocols for the treatment of diabetes mellitus, arterial hypertension, and dyslipidemia are not as effective in CKD patients as in the general population. The role of non-traditional risk factors (RF) has gained interest in the last decades. These entail the deranged clinical spectrum of secondary hyperparathyroidism involving vascular and valvular calcification, under the term “CKD-mineral and bone disorder” (CKD-MBD), uremia per se, inflammation and oxidative stress. Each one of these non-traditional RF have been addressed in various study designs, but the results do not exhibit any applied clinical benefit for CKD-patients. The “crusade” against cardiorenal morbidity and mortality in CKD-patients is in some instances, derailed. We propose a therapeutic paradigm advancing from isolated treatment targets, as practiced today, to precision medicine involving patient phenotypes with distinct underlying pathophysiology. In this regard we propose two steps, based on current stratification management of corona virus disease-19 and sepsis. First, select patients who are expected to have a high mortality, i.e., a prognostic enrichment. Second, select patients who are likely to respond to a specific therapy, i.e., a predictive enrichment.
Core Tip: Stagnation in the Nephrology field has to be overcome with a new perspective. This new vision takes lessons from the past as personalized medicine, adapts precision medicine from today’s lessons from corona virus disease-19 and sepsis and looks into the future with the aid of the big data. Our proposal is that cardiorenal management should be stratified according to patient phenotypes and not as an assembly of individual targets.