Screening and Staging CKM Historically, there is about a 17-year gap between evidence of clinical benefit from a new treatment and adoption into routine clinical practice. The millions of people at increasing risk of death from CKM syndrome progression to CKD and/or CVD cannot wait.20- Gaps Between Knowledge and Implementation in Kidney Care The CKM staging path is bidirectional. The absolute risk of both ASCVD and HF increase with progression from Stage 0 to more advanced stages. Individuals can also regress toward, or to, Stage 0 with the appropriate targeted interventions. The clinical conundrum is accurately assessing and predicting CKM risk to best match the type and intensity of intervention with the predicted risk to reduce morbidity and mortality.12-Introduction 18 Reducing that 17-year gap starts with appropriate screening, risk prediction and risk stratification. CKM syndrome is a five-stage spectrum with stepwise increases in absolute CVD risk. STAGE 0 represents no CKM risk factors.4 STAGE 1 is excess or dysfunctional adiposity. STAGE 2 includes metabolic risk factors of moderate to high risk of CKD. STAGE 3 Subclinical CVD in CKM or the risk equivalents of subclinical CVD, either highrisk CKD or high predicted risk of CVD. STAGE 4 Clinical CVD with CKM risk factors. CVD risk equations have long omitted the welldocumented recognized associations between obesity, diabetes, CKD and CVD morbidity and mortality. These four factors are interrelated, mutually reinforcing and disproportionately affect disenfranchised populations, e.g., underrepresented racial and ethnic groups.12-Introduction Multiple new risk equations are being developed to better assess CKM, CVD and CKD risk in different populations with and without diabetes. These equations include familiar risk factors such as blood pressure, lipids and BMI, and add measures such as eGFR, uACR and SDOH to more accurately predict risk of CKM, CKD and CVD over different time periods.12, 18, 23, 25, 26, 29 The PREVENT equation, developed by the AHA, provides sex-specific and race-free estimates of 10- and 30year for total CVD, a composite of ASCVD and HF, among adults 30 to 79 years of age. The central model includes eGFR and adjusts for competing risks of non-CVD death. Additional models enhance predictive utility by adding uACR, A1C or SDOH measures when available. Growing evidence supports observations that declining kidney health is associated with worse CVD outcomes. Kidney-protective therapies improve CVD outcomes.12Predicting Adverse Kidney Outcomes to Optimize Prevention of CVD PREVENT can be applied in a broad range of clinical and community settings using readily available clinical factors plus additional factors as available. The equation can be implemented by any clinician caring for adult patients, including primary care, obstetrics and gynecology, cardiology, nephology and endocrinology.12-Conclusions Clinical practice guidelines from cardiovascular, nephrology and diabetes organizations recommend the four pillars approach, but translating guidelines into clinical practice can be slow.19 Clinicians typically add each successive therapy in the order in which evidence was generated, first RAS blockade, followed by SGLT2 inhibition, nsMRA (finerenone) and GLP-1 receptor agonist.21
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