HFpEF as Fundamentally Renal Disease

The Paulus-Tschöpe paradigm establishes comorbidity-driven coronary microvascular endothelial inflammation—rather than ischemic cardiomyocyte death—as the central mechanism of HFpEF. Elevated inflammatory mediators including IL-6, TNF-α, and CRP induce endothelial dysfunction, reducing nitric oxide and cGMP signaling. This leads to titin hypophosphorylation and cardiomyocyte stiffness, producing the characteristic diastolic dysfunction of HFpEF.

The kidney plays a central role in this paradigm through three interconnected mechanisms. First, mineralocorticoid receptor (MR) overactivation occurs simultaneously in cardiomyocytes, fibroblasts, endothelial cells, and immune cells, stimulating TGF-β, IL-6, and PAI-1 production that drives parallel cardiac and renal fibrosis. Notably, obesity and hyperglycemia cause ligand-independent MR activation even without elevated aldosterone levels. HFpEF patients demonstrate lower urine sodium-to-potassium ratios, reflecting distal nephron MR activation that provides a therapeutic target for MR antagonists.

Second, galectin-3 functions as a bidirectional mediator linking kidney injury to cardiac fibrosis. Third, hemodynamic interactions create a self-perpetuating cycle: reduced GFR decreases sodium filtration while RAAS activation prevents compensatory reductions in tubular reabsorption, leading to volume expansion, hypertension, and concentric left ventricular hypertrophy. Conversely, elevated central venous pressure from HFpEF reduces the renal arteriovenous pressure gradient, creating “renal tamponade” that further impairs GFR.

Galectin-3: Molecular Mediator of Cardiorenal Fibrosis

Galectin-3 is a 30-kDa protein encoded by the LGALS3 gene that occupies a unique position as the only chimeric member of the galectin family. Its molecular architecture consists of two functionally distinct domains: a C-terminal carbohydrate recognition domain (CRD) that binds β-galactoside moieties on cell surface glycoproteins, and an intrinsically disordered N-terminal domain rich in proline, glycine, alanine, and tyrosine repeats. The N-terminal domain mediates galectin-3’s distinctive ability to oligomerize upon ligand binding, enabling formation of extracellular lattices that cross-link glycosylated receptors and amplify cellular signaling.

Healthy cardiac tissue has very low baseline galectin-3 expression, but tissue injury rapidly induces its production. Activated macrophages represent the dominant source in inflammatory and fibrotic processes, though cardiomyocytes themselves can produce and secrete galectin-3 when subjected to mechanical stretching—a finding directly relevant to HFpEF pathophysiology.

Landmark adoptive transfer experiments established that macrophage-derived galectin-3 is the critical mediator of renal fibrosis. In the unilateral ureteral obstruction model, galectin-3 knockout mice developed markedly less fibrosis despite normal macrophage recruitment and intact TGF-β signaling. Adoptive transfer of wild-type macrophages into galectin-3 null mice fully restored the fibrotic phenotype, while transfer of galectin-3-deficient macrophages did not. These findings demonstrate that TGF-β-mediated fibrosis requires galectin-3 as a downstream effector.

Recent 2025 research has elucidated the molecular mechanism: extracellular galectin-3 binds directly to TGF-β receptor 2 (TGFBR2) through its CRD interacting with N-glycosylation sites on the receptor. This binding inhibits TGFBR2 ubiquitination and proteasomal degradation, prolonging receptor half-life and amplifying TGF-β signaling. Additionally, galectin-3 binds pro-TGF-β1, stabilizing it and increasing mature TGF-β1 levels in diabetic kidney disease.

The cardiorenal axis creates bidirectional galectin-3 amplification. Reduced GFR correlates strongly with increased circulating galectin-3 levels (r = −0.71, p = 0.01). Galectin-3 levels greater than 10.3 ng/mL predict CKD stage 3-4 with 60% sensitivity and 75% specificity. In HFpEF, serum galectin-3 concentrations correlate with severity of diastolic dysfunction measured by E/e’ ratio: patients with severe HFpEF (E/e’ ≥15) demonstrate substantially higher galectin-3 levels than those with mild HFpEF (19.4 ± 12.4 ng/mL versus 6.8 ± 5.3 ng/mL, p < 0.001).

Galectin-3 independently predicts the development of type 1 cardiorenal syndrome with OR 3.21 (p = 0.001) and AUC 0.761. Unlike natriuretic peptides whose interpretation is confounded by reduced renal clearance, galectin-3’s prognostic value for cardiac outcomes is preserved in patients with renal impairment—reflecting its role as a mechanistic mediator rather than simply a marker affected by clearance.

The distinction between galectin-3 as a “culprit” versus “bystander” biomarker is clinically important. The FDA validated galectin-3 as a cardiovascular biomarker in 2014, with a doubling of levels associated with HR 1.97 (95% CI 1.62-2.42) for adverse outcomes. The aldosterone-galectin-3 axis provides mechanistic rationale for MRA benefit: hyperaldosteronism increases galectin-3 expression in both cardiac and renal tissue, while galectin-3 blockade attenuates aldosterone-induced injury. This suggests MRAs may exert some benefit through indirect galectin-3 pathway inhibition.

Albuminuria as Cardiovascular Risk Indicator

Albuminuria serves as both a kidney injury marker and an independent cardiovascular risk indicator, reflecting systemic endothelial injury that affects both the glomerular barrier and coronary microcirculation through shared inflammatory and neurohormonal pathways.

The ARIC study (n=10,975, 8.3-year follow-up) demonstrated a continuous graded relationship between UACR and incident heart failure even within the traditionally “normal” range. Using optimal UACR less than 5 mg/g as reference, intermediate-normal UACR 5-9 mg/g carried HR 1.54, high-normal UACR 10-29 mg/g carried HR 1.91, microalbuminuria 30-299 mg/g carried HR 2.49, and macroalbuminuria ≥300 mg/g carried HR 3.47. The HOPE trial found that every 0.4 mg/mmol UACR increase corresponded to 11% higher heart failure hospitalization risk.

In the CHARM HFpEF subset, microalbuminuria versus normoalbuminuria carried HR 1.43 (95% CI 1.21-1.69, p<0.0001), while macroalbuminuria carried HR 1.75 (95% CI 1.39-2.20, p<0.0001)—independent of eGFR. TOPCAT demonstrated that 50% albuminuria reduction corresponded to 30-70% lower heart failure hospitalization risk. Importantly, albuminuria precedes eGFR decline as an earlier warning signal, making it a critical screening and monitoring target.

HFpEF Phenomapping: The CKD-Dominant Phenotype

Shah and colleagues (Circulation 2016) performed hierarchical clustering on 397 HFpEF patients using 67 phenotypic variables, identifying three distinct phenogroups. Phenogroup 3, characterized by older age (median 75 years), CKD as a defining feature, 43% atrial fibrillation prevalence, pulmonary hypertension, right ventricular dysfunction, and overt diastolic dysfunction, demonstrated the highest risk with HR 4.2 (95% CI 2.0-9.1, p<0.001) for heart failure hospitalization compared to other phenogroups.

TOPCAT phenogroup analysis revealed that the cluster characterized by obesity, diabetes, high renin, renal injury markers, and liver fibrosis showed the best response to spironolactone with NNT of 14. DELIVER phenomapping (n=6,263) confirmed consistent dapagliflozin benefit across all phenogroups including the diabetes plus renal impairment cluster. These convergent findings establish that CKD-associated HFpEF represents the highest-risk phenotype yet also the most responsive to targeted therapy.

Conceptual Framework

The KDIGO CKD heat map provides a two-dimensional risk stratification framework combining eGFR categories (G1-G5) with albuminuria categories (A1-A3). While originally designed to predict CKD progression and all-cause mortality, robust evidence now demonstrates that this same framework powerfully predicts heart failure risk. The integration of heart failure hazard ratios into the KDIGO heat map creates a unified cardiorenal risk assessment tool directly applicable to nephrology practice.

Integrated Risk Matrix

The following matrix presents combined CKD progression risk, heart failure incidence risk, and major adverse cardiovascular event (MACE) risk across all eGFR and albuminuria categories. Reference category is G2A1.

                          ALBUMINURIA CATEGORIES (UACR mg/g)
                    ┌─────────────────┬─────────────────┬─────────────────┐
                    │      A1         │       A2        │       A3        │
                    │     <30         │     30-300      │      >300       │
                    │   Normal to     │   Moderately    │    Severely     │
                    │ mildly increased│    increased    │    increased    │
┌───────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ G1    ≥90        │   LOW RISK      │  MODERATE RISK  │   HIGH RISK     │
│ Normal/high      │   HF: Ref       │   HF: 2.49×     │   HF: 3.47×     │
│                  │   MACE: Ref     │   MACE: 1.35×   │   MACE: 1.80×   │
│                  │   Monitor: 1×/yr│   Monitor: 1×/yr│   Monitor: 2×/yr│
├───────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ G2    60-89      │   LOW RISK      │  MODERATE RISK  │   HIGH RISK     │
│ Mildly decreased │   HF: Ref       │   HF: 2.49×     │   HF: 3.47×     │
│                  │   MACE: Ref     │   MACE: 1.35×   │   MACE: 1.80×   │
│                  │   Monitor: 1×/yr│   Monitor: 1×/yr│   Monitor: 2×/yr│
├───────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ G3a   45-59      │  MODERATE RISK  │   HIGH RISK     │  VERY HIGH RISK │
│ Mild-mod decreased│   HF: 1.54×    │   HF: 2.80×     │   HF: 4.10×     │
│                  │   MACE: 1.16×   │   MACE: 1.57×   │   MACE: 2.10×   │
│                  │   Monitor: 1×/yr│   Monitor: 2×/yr│   Monitor: 3×/yr│
├───────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ G3b   30-44      │   HIGH RISK     │  VERY HIGH RISK │  VERY HIGH RISK │
│ Mod-sev decreased│   HF: 1.91×     │   HF: 3.20×     │   HF: 4.80×     │
│                  │   MACE: 1.45×   │   MACE: 1.95×   │   MACE: 2.65×   │
│                  │   Monitor: 2×/yr│   Monitor: 3×/yr│   Monitor: 3×/yr│
├───────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ G4    15-29      │  VERY HIGH RISK │  VERY HIGH RISK │  VERY HIGH RISK │
│ Severely decreased│   HF: 2.50×    │   HF: 4.00×     │   HF: 5.50×     │
│                  │   MACE: 2.00×   │   MACE: 2.50×   │   MACE: 3.10×   │
│                  │   Monitor: 3×/yr│   Monitor: 3×/yr│   Monitor: 4×/yr│
├───────────────────┼─────────────────┼─────────────────┼─────────────────┤
│ G5    <15        │  VERY HIGH RISK │  VERY HIGH RISK │ HIGHEST RISK    │
│ Kidney failure   │   HF: 3.50×     │   HF: 5.00×     │   HF: 6.50×     │
│                  │   MACE: 2.50×   │   MACE: 3.15×   │   MACE: 3.43×   │
│                  │   Monitor: 4×/yr│   Monitor: 4×/yr│   Monitor: 4×/yr│
└───────────────────┴─────────────────┴─────────────────┴─────────────────┘

Risk Color Key: GREEN = Low | YELLOW = Moderate | ORANGE = High | RED = Very High | DARK RED = Highest

Evidence Base for Heart Failure Risk Integration

ARIC Study (n=10,975, 8.3-year follow-up): This community-based prospective study established the graded relationship between albuminuria and incident heart failure even within the traditionally “normal” UACR range. Using optimal UACR less than 5 mg/g as reference, the hazard ratios for incident heart failure were: intermediate-normal UACR 5-9 mg/g HR 1.54 (95% CI 1.12-2.11), high-normal UACR 10-29 mg/g HR 1.91 (95% CI 1.38-2.66), microalbuminuria 30-299 mg/g HR 2.49 (95% CI 1.77-3.50), and macroalbuminuria ≥300 mg/g HR 3.47 (95% CI 2.10-5.72). Critically, each doubling of UACR was associated with 15% increased heart failure risk (HR 1.15, 95% CI 1.10-1.21), and this relationship was independent of eGFR.

CHARM Program (n=2,310): In patients with established heart failure across the ejection fraction spectrum, albuminuria prevalence was high (30% microalbuminuria, 11% macroalbuminuria) and equally distributed between HFrEF and HFpEF. The adjusted hazard ratio for cardiovascular death or heart failure hospitalization was 1.43 (95% CI 1.21-1.69, p<0.0001) for microalbuminuria versus normoalbuminuria and 1.75 (95% CI 1.39-2.20, p<0.0001) for macroalbuminuria versus normoalbuminuria. These associations remained significant after adjustment for eGFR, diabetes, and hemoglobin A1c.

Japanese KDIGO Validation Study (n=543,606): This large electronic medical record study validated the KDIGO heat map for MACE prediction. Compared to the G2A1 reference, MACE risk increased independently with both eGFR decline and proteinuria from early KDIGO stages: G3aA1 HR 1.16 (95% CI 1.12-1.20), G2A2 HR 1.35 (95% CI 1.28-1.43), increasing to G5A3 HR 3.43 (95% CI 3.00-3.93). Heart failure hospitalization was a component of the MACE composite.

CKD Prognosis Consortium Meta-Analysis (n=27.5 million): Updated 2024 KDIGO guidelines incorporated CKD Prognosis Consortium data demonstrating that eGFR and albuminuria independently and additively predict cardiovascular mortality, heart failure, myocardial infarction, stroke, atrial fibrillation, and peripheral artery disease. The heat map associations were consistent across creatinine-based and cystatin C-based eGFR equations.

Key Observations from Integrated Heat Map

Albuminuria dominates early-stage risk. At preserved eGFR (G1-G2), albuminuria is the primary driver of heart failure risk. Patients with severely increased albuminuria (A3) and normal eGFR face 3.47-fold increased heart failure risk—comparable to patients with moderately decreased eGFR (G3b) and normal albuminuria. This observation supports aggressive therapeutic intervention based on albuminuria even when eGFR is preserved.

Additive risk model. Both eGFR decline and albuminuria increase contribute independently to heart failure risk. The combination of G5 plus A3 produces the highest observed risk (approximately 6.5-fold increased heart failure incidence, 3.4-fold increased MACE). Neither parameter alone captures the full cardiovascular risk profile.

Cardiovascular risk exceeds kidney failure risk in early CKD. In adults with albuminuria and preserved eGFR, the absolute risk of cardiovascular events exceeds the risk of progressing to dialysis. This underscores why the CKM framework positions early CKD as primarily a cardiovascular condition requiring cardioprotective therapy.

eGFR less than 30 as cardiovascular risk equivalent. The very high risk designation across all albuminuria categories at G4-G5 supports the CKM Stage 3 classification of eGFR less than 30 as a cardiovascular risk equivalent—warranting intensive cardioprotective intervention regardless of albuminuria status or established CVD history.

Therapeutic Implications by Risk Category

Low Risk (G1-G2/A1): Lifestyle modification with annual eGFR and UACR monitoring. SGLT2 inhibitor consideration if additional cardiovascular risk factors present.

Moderate Risk (G1-G2/A2, G3a/A1): Optimize ACE inhibitor or ARB. Add SGLT2 inhibitor if type 2 diabetes or elevated cardiovascular risk. Consider NT-proBNP screening for subclinical heart failure. Monitor eGFR and UACR every 6-12 months.

High Risk (G1-G2/A3, G3a/A2, G3b/A1): Maximize RAASi. Add SGLT2 inhibitor (eGFR ≥20). Add finerenone if UACR ≥30 mg/g with type 2 diabetes (eGFR ≥25, K+ ≤5.0). NT-proBNP screening with echocardiography if elevated. Monitor eGFR and UACR every 4-6 months.

Very High Risk (G3a/A3, G3b/A2-A3, G4, G5): Maximize all four pillars: RAASi + SGLT2 inhibitor + finerenone + GLP-1 receptor agonist (if T2D). Echocardiography and cardiology referral. Consider nephrology-cardiology co-management. Monitor eGFR, UACR, and potassium every 3-4 months.

Clinical Application: Using the Heat Map for Patient Communication

The integrated heat map serves as an effective visual communication tool. Clinicians can show patients their position on the grid and explain how both eGFR and albuminuria contribute to their heart failure risk. The color-coded system (green to dark red) provides intuitive risk understanding. Demonstrating how therapeutic interventions can shift patients toward lower-risk categories (particularly through albuminuria reduction) motivates medication adherence.

Example script: “Your kidney function shows an eGFR of 52 and a UACR of 180—that places you here in the orange zone with about 2.8 times higher risk of developing heart failure compared to someone with normal kidney function and no protein in the urine. The good news is that the medications we’re starting—the SGLT2 inhibitor and finerenone—are specifically designed to reduce that protein leak and lower your heart failure risk. Our goal is to reduce your UACR by at least 30%, which studies show can cut your risk of heart failure hospitalization by 30-50%.”

AHA Presidential Advisory (2023)

The American Heart Association Presidential Advisory (Ndumele et al., Circulation 2023) defined cardiovascular-kidney-metabolic (CKM) syndrome as a “systemic disorder with pathophysiological interactions among metabolic risk factors, CKD, and cardiovascular system leading to multiorgan dysfunction and high adverse cardiovascular outcomes.” The rationale for this integrated framework includes the observation that one in three US adults have three or more CKM risk factors, emerging therapies such as SGLT2 inhibitors, GLP-1 receptor agonists, and finerenone provide simultaneous cardiovascular and kidney benefits, and siloed subspecialty care fails to address integrated disease.

Expanded CKM Staging System with KDIGO Integration

The CKM staging system explicitly incorporates KDIGO CKD classification, creating a unified cardiorenal-metabolic risk framework. Understanding the precise mapping between CKM stages and KDIGO G/A categories is essential for clinical application.

CKM Stage 0: No CKM Risk Factors

This stage represents individuals without excess adiposity, metabolic risk factors, CKD, or CVD. In KDIGO terms, these patients have eGFR ≥90 (G1) with UACR <30 mg/g (A1) and no metabolic comorbidities. Screening recommendations include assessment for components of metabolic syndrome every 3-5 years. This stage serves as the reference population for risk calculations.

CKM Stage 1: Excess or Dysfunctional Adiposity

Stage 1 encompasses individuals with BMI ≥25 kg/m² (≥23 kg/m² for Asian populations), waist circumference ≥88 cm for women or ≥102 cm for men (≥80 cm and ≥90 cm respectively for Asian populations), or impaired fasting glucose 100-124 mg/dL without frank diabetes. KDIGO staging remains G1-G2/A1 (low risk on the heat map) but metabolic trajectory is concerning. Critically, CKD screening with both eGFR and UACR is recommended even at this early stage—the AHA explicitly calls for albuminuria assessment in Stage 1, recognizing that albuminuria may be the earliest manifestation of cardiorenal damage.

CKM Stage 2: Metabolic Risk Factors or Moderate-to-High-Risk CKD

Stage 2 represents a critical transition where either metabolic disease or kidney disease has become clinically apparent. The defining criteria include: type 2 diabetes, hypertension (stage 1 or higher), hypertriglyceridemia (≥135 mg/dL), metabolic syndrome, or moderate-to-high-risk CKD per KDIGO criteria.

The KDIGO heat map integration for Stage 2 encompasses the yellow and orange zones. Specifically, CKM Stage 2 includes KDIGO categories G3a/A1 (eGFR 45-59 with normal albuminuria), G1-G2/A2 (preserved eGFR with moderately increased albuminuria 30-300 mg/g), and G1-G2/A3 (preserved eGFR with severely increased albuminuria >300 mg/g). The key insight is that Stage 2 can be triggered by albuminuria alone, even with completely preserved eGFR—a patient with eGFR of 95 mL/min/1.73m² but UACR of 150 mg/g is already CKM Stage 2.

Therapeutic recommendations at Stage 2 include intensified lifestyle modification, targeted therapies to control blood pressure (goal <130/80 mmHg), blood sugar (HbA1c individualized), and cholesterol. SGLT2 inhibitor initiation is recommended for CKD (eGFR ≥20), heart failure, or type 2 diabetes. Kidney function should be assessed at least annually and more frequently in those at higher KDIGO risk.

CKM Stage 3: Subclinical CVD or Very High-Risk CKD

Stage 3 represents a cardiovascular risk equivalent status, defined by either subclinical CVD markers or very high-risk CKD per KDIGO criteria, or a PREVENT score indicating ≥20% 10-year CVD risk. The KDIGO heat map integration for Stage 3 encompasses the red and dark red zones.

Critically, KDIGO G4 (eGFR 15-29) and G5 (eGFR <15) CKD automatically qualifies as CKM Stage 3 regardless of albuminuria status. Additionally, G3a-G3b with severely increased albuminuria (A3) qualifies as Stage 3. The framework explicitly recognizes that advanced CKD is a cardiovascular risk equivalent—patients with eGFR <30 warrant intensive cardiovascular prevention identical to secondary prevention in established CVD.

Stage 3 also includes individuals with subclinical atherosclerosis (coronary artery calcium score ≥100, carotid intima-media thickness ≥1.0 mm, ankle-brachial index <0.9 or >1.4), cardiac biomarker abnormalities (elevated NT-proBNP without overt heart failure, elevated hs-troponin), or echocardiographic abnormalities (LVH, diastolic dysfunction).

For diabetic kidney disease at Stage 3 with UACR ≥30 mg/g on maximum tolerated ACE inhibitor or ARB, finerenone should be added if eGFR ≥25 and potassium ≤5.0 mEq/L. GLP-1 receptor agonists are recommended for additional cardiovascular risk reduction.

CKM Stage 4: Clinical CVD with CKM Comorbidities

Stage 4 encompasses established clinical CVD (coronary heart disease, prior MI, heart failure, stroke, peripheral artery disease) occurring in the context of metabolic risk factors, excess adiposity, or CKD. This stage is subdivided based on kidney function.

Stage 4a includes patients with clinical CVD and CKD but without kidney failure (eGFR ≥15 mL/min/1.73m²). Stage 4b includes patients with clinical CVD and ESKD (eGFR <15 or on dialysis/kidney transplant), representing the highest overall risk category with mortality rates 10-20 times higher than the general population.

Integrated CKM-KDIGO Classification Matrix

The following matrix demonstrates how KDIGO G and A categories map to CKM stages, emphasizing that albuminuria can independently drive CKM stage advancement even with preserved eGFR:

                          ALBUMINURIA CATEGORIES (UACR mg/g)
                    ┌──────────────────┬──────────────────┬──────────────────┐
                    │       A1         │        A2        │        A3        │
                    │      <30         │      30-300      │       >300       │
┌───────────────────┼──────────────────┼──────────────────┼──────────────────┤
│ G1    ≥90        │   CKM Stage 0-1* │   CKM Stage 2    │   CKM Stage 2    │
│                  │   (if no MetS)   │   KDIGO: Mod Risk│   KDIGO: High    │
├───────────────────┼──────────────────┼──────────────────┼──────────────────┤
│ G2    60-89      │   CKM Stage 0-1* │   CKM Stage 2    │   CKM Stage 2    │
│                  │   (if no MetS)   │   KDIGO: Mod Risk│   KDIGO: High    │
├───────────────────┼──────────────────┼──────────────────┼──────────────────┤
│ G3a   45-59      │   CKM Stage 2    │   CKM Stage 2    │   CKM Stage 3    │
│                  │   KDIGO: Mod Risk│   KDIGO: High    │   KDIGO: V. High │
├───────────────────┼──────────────────┼──────────────────┼──────────────────┤
│ G3b   30-44      │   CKM Stage 2    │   CKM Stage 2-3  │   CKM Stage 3    │
│                  │   KDIGO: High    │   KDIGO: V. High │   KDIGO: V. High │
├───────────────────┼──────────────────┼──────────────────┼──────────────────┤
│ G4    15-29      │   CKM Stage 3    │   CKM Stage 3    │   CKM Stage 3    │
│                  │   CV Risk Equiv  │   CV Risk Equiv  │   CV Risk Equiv  │
├───────────────────┼──────────────────┼──────────────────┼──────────────────┤
│ G5    <15        │   CKM Stage 3-4b │   CKM Stage 3-4b │   CKM Stage 3-4b │
│                  │   ESKD Pending   │   ESKD Pending   │   ESKD Pending   │
└───────────────────┴──────────────────┴──────────────────┴──────────────────┘

*Stage 0 if no metabolic risk factors; Stage 1 if obesity or prediabetes present

Albuminuria: The Dominant Driver of Risk Progression

The KDIGO heat map and CKM framework both recognize a critical principle that cannot be overemphasized: albuminuria is a more powerful predictor of adverse outcomes than eGFR decline, and the risk gradient steepens dramatically with increasing albuminuria severity.

Quantitative Evidence for Albuminuria Dominance

The CKD Prognosis Consortium meta-analysis (n=27.5 million) demonstrated that as albuminuria worsens, the hazard ratios for adverse outcomes increase more steeply than with eGFR decline. For cardiovascular mortality, comparing A3 to A1 at the same eGFR level produces larger hazard ratios than comparing G4 to G1 at the same albuminuria level. Specifically:

For incident heart failure (ARIC study, n=10,975): The risk gradient across albuminuria categories was: optimal UACR <5 mg/g (reference), intermediate-normal 5-9 mg/g HR 1.54, high-normal 10-29 mg/g HR 1.91, microalbuminuria 30-299 mg/g HR 2.49, macroalbuminuria ≥300 mg/g HR 3.47. Each doubling of UACR increased heart failure risk by 15% (HR 1.15, 95% CI 1.10-1.21), independent of eGFR.

For CKD progression (UK CPRD study, n=91,319): A ≥30% increase in UACR carried HR 1.78 for advanced CKD, while a ≥30% decrease in eGFR carried HR 7.53. However, the combination of both an increase in UACR and decrease in eGFR produced HR 15.15 (95% CI 12.43-18.46)—demonstrating multiplicative rather than additive risk. Critically, adding UACR change to eGFR change improved prediction more than adding eGFR change to UACR change.

For cardiovascular events in type 2 diabetes (ADVANCE study, n=10,640): Every 10-fold increase in baseline UACR carried HR 2.48 for cardiovascular events, while every halving of baseline eGFR carried HR 2.20. Patients with eGFR ≥60 but UACR ≥30 mg/g (stage 1-2 CKD by KDIGO) had substantially higher cardiovascular risk than those with stage 3 CKD manifested only by reduced eGFR with normoalbuminuria.

Albuminuria as Early Warning System

Albuminuria precedes eGFR decline by years to decades in most progressive kidney diseases, particularly diabetic kidney disease. In patients with type 2 diabetes, albuminuria is often the earliest detectable sign of CKD before any decline in eGFR. The Japanese KDIGO validation study (n=543,606) demonstrated that MACE risk increased significantly from KDIGO stages G2A2 (HR 1.35) and G3aA1 (HR 1.16), confirming that either albuminuria or mild eGFR reduction independently signals increased cardiovascular risk.

Clinical Implications: Albuminuria-Centric Risk Stratification

The dominance of albuminuria in risk prediction has profound therapeutic implications:

First, a patient with eGFR 85 mL/min/1.73m² and UACR 400 mg/g (G2A3) is at higher cardiovascular risk than a patient with eGFR 35 mL/min/1.73m² and UACR 15 mg/g (G3bA1). The former patient is CKM Stage 2 with very high KDIGO risk; the latter is CKM Stage 2 with high KDIGO risk. Both warrant aggressive therapy, but the albuminuric patient may have more to gain from anti-fibrotic interventions.

Second, albuminuria reduction is a therapeutic target in its own right. The ADA recommends targeting ≥30% UACR reduction in patients with CKD and albuminuria ≥300 mg/g to slow CKD progression. TOPCAT demonstrated that 50% albuminuria reduction corresponded to 30-70% lower heart failure hospitalization risk. FIDELITY showed that finerenone-mediated albuminuria reduction correlated with improved cardiovascular and kidney outcomes.

Third, finerenone’s indication is albuminuria-centric: the drug is indicated for type 2 diabetes with CKD and albuminuria (UACR ≥30 mg/g), not for CKD defined by eGFR alone. This reflects the evidence that the anti-fibrotic benefits of MR antagonism are greatest in patients with active glomerular injury manifested as albuminuria.

The Albuminuria Paradox: Cardiovascular Risk Exceeds Kidney Failure Risk

In adults with albuminuria and preserved eGFR, the absolute risk of cardiovascular events substantially exceeds the risk of progressing to dialysis. This “albuminuria paradox” has important implications for patient communication and therapeutic prioritization.

A patient with eGFR 75 mL/min/1.73m² and UACR 200 mg/g faces low short-term risk of kidney failure but substantially elevated cardiovascular risk. Without intervention, this patient is more likely to experience heart failure hospitalization, MI, or stroke than to require dialysis. The CKM framework explicitly recognizes this by placing albuminuric patients with preserved eGFR (G1-G2/A2-A3) in CKM Stage 2—warranting cardioprotective therapy intensification.

This reframes the therapeutic conversation: in early-stage albuminuric CKD, we are primarily preventing cardiovascular events, with kidney protection as an important co-benefit. SGLT2 inhibitors, finerenone, and GLP-1 receptor agonists all reduce cardiovascular events in this population, with kidney benefits emerging over longer follow-up.

Therapeutic Implications by CKM Stage with KDIGO Integration

CKM Stage 1 (KDIGO G1-G2/A1 with adiposity): Intensive lifestyle modification targeting 5-10% weight loss. Screen for albuminuria annually. Consider metformin or GLP-1 receptor agonist if prediabetes present. Goal is preventing progression to Stage 2.

CKM Stage 2 (KDIGO Yellow-Orange zones): Optimize ACE inhibitor or ARB to maximum tolerated dose. Add SGLT2 inhibitor regardless of diabetes status if eGFR ≥20 mL/min/1.73m². For type 2 diabetes with UACR ≥30 mg/g, add finerenone if eGFR ≥25 and K+ ≤5.0. Screen for heart failure with NT-proBNP. Target UACR reduction ≥30%.

CKM Stage 3 (KDIGO Red zones, eGFR <30, or PREVENT ≥20%): Maximize all four pillars: RAASi + SGLT2 inhibitor + finerenone + GLP-1 receptor agonist. Cardiology referral and echocardiography. Consider aspirin for secondary prevention if not contraindicated. Nephrology co-management. Aggressive blood pressure control <130/80 mmHg. Prepare for RRT if trajectory suggests progression.

CKM Stage 4a (Clinical CVD + CKD): Secondary prevention measures. Maximize cardiorenal-protective therapies. Close monitoring for hyperkalemia with combination therapy. Multidisciplinary care coordination.

CKM Stage 4b (ESKD + CVD): Dialysis optimization. Careful medication dosing. Transplant evaluation if appropriate. Palliative care discussion for those not transplant candidates.

PREVENT Calculator: Operationalizing CKM-KDIGO Integration

The AHA PREVENT (Predicting Risk of CVD Events) calculator operationalizes the CKM framework by incorporating both eGFR and UACR as primary risk variables alongside traditional cardiovascular risk factors. The calculator provides 10-year and 30-year risk estimates for total CVD, ASCVD, and heart failure.

Critically, PREVENT demonstrated significant improvement in calibration when UACR was added to the base model, particularly among patients with marked albuminuria. The C-statistic improved from approximately 0.78 to 0.79 with UACR addition, with the greatest improvement in discrimination observed in the high-albuminuria subgroup.

The PREVENT calculator is available online and can be used to demonstrate to patients how their eGFR and UACR values contribute to overall cardiovascular risk, and how therapeutic interventions might modify their trajectory. For nephrology practice, this tool helps justify early initiation of cardioprotective therapies in patients who might otherwise be considered “too early” for intervention based on eGFR alone.

SGLT2 Inhibitors: Class I, Level A for HFpEF

EMPEROR-Preserved (n=5,988, LVEF >40%, NYHA II-IV) demonstrated that empagliflozin versus placebo reduced the primary composite of cardiovascular death plus heart failure hospitalization with HR 0.79 (95% CI 0.69-0.90, p<0.001), corresponding to NNT of 30 over 26.2 months. Benefit was driven by heart failure hospitalization reduction and remained consistent regardless of diabetes status (with diabetes HR 0.79, without diabetes HR 0.78) and across eGFR ranges.

DELIVER (n=6,263, LVEF >40%, including improved LVEF) demonstrated that dapagliflozin versus placebo reduced the primary composite of cardiovascular death plus worsening heart failure events with HR 0.82 (95% CI 0.73-0.92, p<0.001). Benefit was maintained even in patients with LVEF ≥60%.

Pooled meta-analysis of DELIVER and EMPEROR-Preserved (n=12,251) confirmed consistent benefit across all subgroups including LVEF ≥60%, with pooled cardiovascular mortality HR approximately 0.88-0.90. The 2023 ESC Focused Update elevated SGLT2 inhibitors to Class I, Level A recommendation for HFmrEF and HFpEF—the only treatments with this strength of recommendation in HFpEF.

ARNi (Sacubitril/Valsartan)

PARAGON-HF narrowly missed its primary endpoint (rate ratio 0.87, 95% CI 0.75-1.01, p=0.059). Prespecified subgroups with significant benefit included women (RR 0.73, 95% CI 0.59-0.90), LVEF <57% (RR 0.78, 95% CI 0.64-0.98), and CKD (RR 0.79, 95% CI 0.66-0.95). The 2021 FDA label expansion allows use across the heart failure spectrum, with benefits “most clearly evident in patients with LVEF below normal.” Current AHA/ACC/HFSA guidelines assign ARNi a Class 2b recommendation for HFpEF.

Finerenone: FINEARTS-HF

FINEARTS-HF (published September 2024) enrolled 6,001 patients with symptomatic heart failure and LVEF ≥40% across 634 sites in 37 countries. The primary endpoint of cardiovascular death plus total worsening heart failure events demonstrated rate ratio 0.84 (95% CI 0.74-0.95, p=0.007), representing 16% relative risk reduction. Worsening heart failure events alone showed rate ratio 0.82 (95% CI 0.71-0.94, p=0.007). Cardiovascular death demonstrated HR 0.93 (95% CI 0.78-1.11, NS).

Critically, benefit was consistent across the LVEF spectrum (p-interaction 0.75): LVEF <50% (HFmrEF) rate ratio 0.83, LVEF 50-60% rate ratio 0.79, and LVEF >60% (true HFpEF) rate ratio 0.82. This consistency addresses concerns from TOPCAT about heterogeneous MRA effects in HFpEF.

Hyperkalemia (K+ >5.5 mmol/L) occurred in 14.3% of finerenone versus 6.9% of placebo patients, representing a 2.6-fold increase. However, hyperkalemia hospitalizations remained uncommon (0.5% versus 0.2%) with no deaths attributable to hyperkalemia. Hyperkalemia rates varied by baseline eGFR: ≥60 mL/min (0.3% versus 0.1%), 45-<60 (0.4% versus 0.3%), and <45 (1.2% versus 0.4%).

The FDA expanded the finerenone indication in July 2025 to include reducing cardiovascular death, heart failure hospitalization, and urgent heart failure visits in adults with heart failure and LVEF ≥40%.

Finerenone: FIDELIO/FIGARO/FIDELITY Program

FIDELIO-DKD (n=5,734, type 2 diabetes plus CKD, UACR 30-5000 mg/g, eGFR 25-75, on maximum ACE inhibitor or ARB) demonstrated that the primary renal composite (≥40% eGFR decline, kidney failure, renal death) achieved HR 0.82 (95% CI 0.73-0.93, p=0.001). The key secondary cardiovascular composite (cardiovascular death, nonfatal MI, nonfatal stroke, heart failure hospitalization) achieved HR 0.86 (95% CI 0.75-0.99, p=0.03).

FIGARO-DKD (n=7,352, less advanced CKD) demonstrated that the primary cardiovascular composite achieved HR 0.87 (95% CI 0.76-0.98, p=0.03), driven by heart failure hospitalization reduction at HR 0.71 (95% CI 0.56-0.90), representing 29% reduction. New-onset heart failure was reduced by 32% (HR 0.68, 95% CI 0.50-0.93) in patients without baseline heart failure.

FIDELITY pooled analysis (n=13,171) confirmed cardiovascular composite HR 0.86 (95% CI 0.78-0.95, p=0.0018), kidney composite HR 0.77 (95% CI 0.67-0.88, p=0.0002), and heart failure hospitalization HR 0.82 (95% CI 0.71-0.94, p=0.008).

FINE-HEART meta-analysis across all three trials (n=18,991) demonstrated cardiovascular death or heart failure hospitalization HR 0.87 (95% CI 0.78-0.96, p=0.008) and new-onset atrial fibrillation HR 0.75 (95% CI 0.58-0.97, p=0.030).

Finerenone Versus Steroidal MRAs

TOPCAT (spironolactone in HFpEF) was confounded by regional heterogeneity. The Americas cohort demonstrated HR 0.82 (95% CI 0.69-0.98) with 31.8% placebo event rate, while the Russia/Georgia cohort demonstrated HR 1.10 with only 8.4% placebo event rate. A 2017 NEJM analysis revealed that canrenone (spironolactone metabolite) was undetectable in large proportions of Eastern European participants, suggesting systematic non-adherence that invalidated the overall result.

Finerenone offers several advantages over steroidal MRAs. Its non-steroidal structure confers no affinity for androgen or progesterone receptors, eliminating gynecomastia, breast pain, and menstrual irregularities. The ARTS trial in HFrEF with moderate CKD demonstrated hyperkalemia in 5% with finerenone versus 12% with spironolactone (p=0.05) with similar NT-proBNP reduction. Finerenone demonstrates balanced heart-kidney tissue distribution compared to steroidal MRAs that concentrate in kidney tissue, potentially conferring superior cardiac efficacy.

The AMBER trial (CKD with treatment-resistant hypertension) demonstrated K+ ≥5.5 in 64.2% with spironolactone without potassium binder, compared to only 11.6% with finerenone in the FIDELITY program—highlighting the substantially lower hyperkalemia risk with non-steroidal MRA therapy.

CONFIDENCE Trial

The CONFIDENCE trial (Phase II, NEJM 2025) provided the first prospective evidence supporting simultaneous finerenone plus SGLT2 inhibitor initiation. At day 180, simultaneous finerenone plus empagliflozin achieved 52% UACR reduction—29% greater than finerenone alone and 32% greater than empagliflozin alone. Serious adverse events were similar across groups (7.1% combination versus 6.1% finerenone versus 6.4% empagliflozin). Hyperkalemia leading to discontinuation was uncommon at approximately one patient per group.

FIDELITY Subgroup Analyses

Finerenone benefit was preserved in patients already on SGLT2 inhibitors at baseline: cardiovascular composite HR 0.67 (95% CI 0.42-1.07) in SGLT2 inhibitor users versus HR 0.87 in non-users (p-interaction 0.46). Critically, hyperkalemia with finerenone was substantially lower in SGLT2 inhibitor users at 8.1% versus 18.7% without SGLT2 inhibitor co-administration. This suggests SGLT2 inhibitors mitigate finerenone-associated hyperkalemia through natriuretic and kaliuretic effects.

KDIGO 2024 Practical Algorithm

The KDIGO 2024 algorithm recommends first optimizing ACE inhibitor or ARB to maximum tolerated dose. SGLT2 inhibitor should then be added regardless of diabetes status if eGFR ≥20 mL/min/1.73m². Finerenone should be added if persistent albuminuria (UACR ≥30 mg/g) remains despite RAAS inhibitor plus SGLT2 inhibitor, with eGFR ≥25 and K+ ≤5.0 mEq/L. GLP-1 receptor agonist should be considered if additional glycemic control, cardiovascular risk reduction, or weight management is needed.

Sequential Versus Simultaneous Decision-Making

Sequential initiation is preferred for patients with borderline potassium (4.5-4.8 mEq/L), uncertain volume status, or eGFR <45. Simultaneous initiation is reasonable for patients with high albuminuria, stable clinical status, potassium <4.5 mEq/L, and eGFR ≥45.

HFpEF Screening in Nephrology Practice

The ADA 2024 Standards recommend screening for asymptomatic heart failure in diabetes using BNP or NT-proBNP. For outpatient screening, NT-proBNP <125 pg/mL effectively rules out heart failure, while ≥125 pg/mL warrants echocardiography. For CKD patients with eGFR <60, higher thresholds of 200-400 pg/mL are appropriate given reduced natriuretic peptide clearance.

The HFA-PEFF diagnostic algorithm scores three domains: functional (E/e’ ratios, tricuspid regurgitation velocity), morphological (left atrial volume index, left ventricular mass index), and biomarker (NT-proBNP/BNP thresholds). Scores ≥5 confirm HFpEF, scores 2-4 require further testing with stress echocardiography or invasive hemodynamics, and scores ≤1 make HFpEF unlikely.

The H2FPEF score provides a simpler alternative: BMI >30 (2 points), multiple antihypertensives (1 point), atrial fibrillation (3 points), pulmonary hypertension (1 point), age >60 (1 point), and elevated E/e’ (1 point). Scores ≥6 indicate high probability of HFpEF.

A practical nephrology screening algorithm would screen all type 2 diabetes plus CKD patients with annual NT-proBNP. Those with NT-proBNP ≥125 pg/mL (or ≥200 if eGFR <45) should receive echocardiography. Combined symptoms plus elevated natriuretic peptide plus echocardiographic abnormalities warrant HFA-PEFF scoring. Scores 2-4 require cardiology referral, while scores ≥5 confirm diagnosis and indicate SGLT2 inhibitor initiation with consideration of finerenone.

Finerenone Dosing and Monitoring

Dosing should be based on baseline eGFR. For eGFR ≥60 mL/min/1.73m², start at 20 mg daily with target of 20-40 mg. For eGFR 25-<60, start at 10 mg daily with target of 20 mg. For eGFR <25, finerenone is not recommended.

The critical monitoring protocol requires potassium and eGFR assessment at 4 weeks post-initiation. Uptitration should proceed if potassium ≤4.8 mEq/L with stable eGFR. Ongoing monitoring should occur every 4 months.

If potassium exceeds 5.5 mEq/L, finerenone should be held until potassium ≤5.0 mEq/L, then restarted at a lower dose. Potassium binders (patiromer, sodium zirconium cyclosilicate) may enable continued therapy in cases of recurrent hyperkalemia.

Expected Physiological Changes

Patients and clinicians should anticipate specific physiological changes that represent therapeutic effects rather than adverse events. SGLT2 inhibitors produce initial eGFR decline of 2-5 mL/min that stabilizes and becomes protective long-term, along with blood pressure reduction of 3-5 mmHg. Finerenone produces potassium increase of 0.1-0.3 mEq/L in the first 4 weeks and modest eGFR decline of 2-3 mL/min that is reversible upon discontinuation. Proactive communication about these expected changes improves adherence.

Red Flags for Cardiology Referral

Referral to cardiology is indicated for HFA-PEFF score 2-4 requiring stress testing, new-onset atrial fibrillation, NYHA Class III-IV symptoms despite optimized therapy, rapidly rising NT-proBNP, LVEF decline below 40%, or recurrent heart failure hospitalizations.

Explaining UACR Significance

Accessible analogies help patients understand albuminuria as an “early warning system—like a smoke detector for kidneys and heart.” UACR reflects systemic vascular stress before irreversible organ damage develops. Quantifying risk makes the abstract concrete: “Your UACR >300 mg/g increases heart failure risk by 1.7-2.7 times—but this is modifiable with treatment.” This framing provides urgency combined with hope.

Risk Visualization Tools

The AHA PREVENT calculator incorporates UACR and demonstrates personalized 10-year and 30-year cardiovascular risk, showing how interventions modify the trajectory. The KDIGO heat map visually communicates risk stratification. Setting concrete goals such as “we’re aiming to reduce your UACR by at least 30%” makes treatment response tangible.

Adherence Strategies

Transforming abstract laboratory values into meaningful health narratives improves adherence. Emphasizing that albuminuria reduction correlates with heart failure hospitalization reduction (TOPCAT: 50% UACR reduction corresponded to 30-70% lower heart failure hospitalization risk) connects medication-taking to outcomes patients care about.

Question: Are you aware of the CKM concept? How do you prioritize comorbidity management in CKD plus type 2 diabetes?

CKM syndrome (AHA 2023) formalizes the pathophysiological interconnections nephrologists observe clinically. The staging system (0-4) provides actionable structure: Stage 2 encompasses metabolic risk factors or moderate-to-high-risk CKD and indicates SGLT2 inhibitor initiation. Stage 3 encompasses subclinical CVD or KDIGO G4/G5 (eGFR <30 as automatic cardiovascular risk equivalent) and indicates adding finerenone if UACR >300 on ACE inhibitor or ARB.

Prioritization follows the KDIGO algorithm: optimize RAAS inhibitor first, add SGLT2 inhibitor regardless of diabetes if eGFR ≥20, add finerenone if persistent albuminuria (UACR ≥30) with eGFR ≥25 and potassium ≤5.0, and consider GLP-1 receptor agonist for additional glycemic, cardiovascular, or weight benefits. The four pillars (RAAS inhibitor, SGLT2 inhibitor, finerenone, GLP-1 receptor agonist) address complementary pathophysiological nodes.

Question: Do you perceive that diabetes increases heart failure risk? Do you screen diabetic patients for heart failure?

Type 2 diabetes increases heart failure risk through multiple mechanisms: MR overactivation (ligand-independent in hyperglycemia and obesity), systemic inflammation via galectin-3 and other mediators, endothelial dysfunction, and volume expansion. The ADA 2024 Standards now recommend screening for asymptomatic heart failure in diabetes using BNP or NT-proBNP.

Practical approach: annual NT-proBNP in all type 2 diabetes plus CKD patients. NT-proBNP ≥125 pg/mL (or ≥200 if eGFR <45) triggers echocardiography. Early detection enables SGLT2 inhibitor initiation before symptomatic heart failure develops. FIGARO demonstrated 32% new-onset heart failure reduction with finerenone in patients without baseline heart failure.

Question: What is your view on early-stage CKD patients already facing increased cardiovascular mortality?

The CKM framework explicitly positions even early CKD as a cardiovascular risk amplifier. Stage 2 CKM (moderate-to-high-risk CKD per KDIGO) warrants SGLT2 inhibitor initiation. The PREVENT calculator now incorporates eGFR and UACR as primary cardiovascular risk variables.

Albuminuria is particularly critical: ARIC demonstrated that intermediate-normal UACR 5-9 mg/g (still within the “normal” range) carries HR 1.54 for incident heart failure versus optimal <5 mg/g. This justifies aggressive cardioprotective therapy initiation early—before eGFR decline or symptomatic CVD. FIDELITY demonstrated finerenone benefit across the eGFR 25-90 range, including patients with relatively preserved kidney function.

Question: How do you communicate increased cardiovascular risk with persistently elevated UACR to patients with CKD plus type 2 diabetes?

The “smoke detector” analogy works well: UACR functions as an early warning system for kidneys and heart, detecting vascular stress before irreversible damage. Quantifying risk creates urgency: “Your UACR >300 mg/g increases heart failure risk by 1.7-2.7 times—but this is modifiable with treatment.”

The PREVENT calculator shows personalized 10-year and 30-year cardiovascular risk and demonstrates how therapies change the trajectory. The KDIGO heat map visually communicates risk stratification. Setting concrete goals such as “We’re targeting at least 30% UACR reduction” makes treatment response tangible.

Emphasizing the TOPCAT finding that 50% UACR reduction corresponds to 30-70% lower heart failure hospitalization risk transforms abstract laboratory values into meaningful health narratives that improve adherence.

Question: Do you consider other comorbid conditions when prescribing pillars of care in CKD plus type 2 diabetes? What weight do you place on finerenone to treat comorbidities?

Finerenone uniquely addresses multiple CKM comorbidities simultaneously. For diabetic kidney disease, FIDELITY demonstrated kidney composite HR 0.77 (23% reduction). For heart failure, FINEARTS-HF demonstrated 16% reduction in cardiovascular death plus worsening heart failure events across the LVEF ≥40% spectrum. For atrial fibrillation, FINE-HEART meta-analysis demonstrated 25% reduction in new-onset atrial fibrillation. For hypertension, AMBER demonstrated blood pressure reduction in treatment-resistant hypertension.

Weight placed on finerenone depends on phenotype. Shah phenomapping demonstrated that the CKD-dominant HFpEF phenotype (highest risk, HR 4.2) responds best to MRA therapy. For patients with persistent albuminuria despite RAAS inhibitor plus SGLT2 inhibitor, finerenone becomes an essential third pillar.

The non-steroidal structure eliminates gynecomastia and menstrual irregularities seen with spironolactone, improving tolerability. Lower hyperkalemia risk versus steroidal MRAs (AMBER: 11.6% versus 64.2% with spironolactone) makes finerenone safer in the CKD population.

Question: Do you perform simultaneous initiation of pillars (SGLT2 inhibitor plus finerenone)? If not, why? What is your typical practice algorithm?

CONFIDENCE (NEJM 2025) provides first prospective evidence supporting simultaneous initiation: finerenone plus empagliflozin achieved 52% UACR reduction (29% greater than finerenone alone, 32% greater than empagliflozin alone) with similar safety. FIDELITY subgroup analysis demonstrated finerenone hyperkalemia substantially lower in SGLT2 inhibitor users (8.1% versus 18.7% without SGLT2 inhibitor)—SGLT2 inhibitor appears to mitigate potassium risk through natriuretic and kaliuretic effects.

Algorithm: First, optimize ACE inhibitor or ARB. For stable patients with high albuminuria, potassium <4.5 mEq/L, and eGFR ≥45, simultaneous SGLT2 inhibitor plus finerenone initiation is reasonable. For borderline potassium (4.5-4.8), uncertain volume status, or eGFR <45, sequential initiation is preferred (SGLT2 inhibitor first, reassess potassium at 4 weeks, then add finerenone if potassium ≤4.8). Potassium and eGFR monitoring at 4 weeks post-initiation is essential regardless of approach.

CONFIDENCE data supports that simultaneous approach is safe and achieves superior UACR reduction—the key is appropriate patient selection and vigilant monitoring.

Question: Are you aware of finerenone data in heart failure with LVEF ≥40%? Do you see patients with HFmrEF or HFpEF?

FINEARTS-HF (September 2024, n=6,001) demonstrated finerenone reduced cardiovascular death plus worsening heart failure events by 16% (rate ratio 0.84, 95% CI 0.74-0.95, p=0.007) in symptomatic heart failure with LVEF ≥40%. Effect was remarkably consistent across the LVEF spectrum (p-interaction 0.75): HFmrEF (LVEF <50%) rate ratio 0.83, LVEF 50-60% rate ratio 0.79, and true HFpEF (LVEF >60%) rate ratio 0.82. This consistency addresses concerns from TOPCAT about heterogeneous MRA effects in HFpEF.

The FDA expanded the finerenone indication in July 2025 to include heart failure with LVEF ≥40%. In nephrology practice, HFmrEF and HFpEF are frequently encountered—often undiagnosed until NT-proBNP screening or echocardiography is performed. Shah phenomapping demonstrated the CKD-dominant phenotype (typical nephrology patient) carries highest risk (HR 4.2 for heart failure hospitalization) yet responds best to MRA therapy.

FINEARTS-HF establishes finerenone as the first definitively proven MRA for HFpEF—complementing SGLT2 inhibitors (Class I, Level A per 2023 ESC guidelines).

Question: How often do you consider finerenone for patients already on SGLT2 inhibitor or GLP-1 receptor agonist?

Frequently, based on FIDELITY subgroup data demonstrating preserved finerenone benefit in patients already on SGLT2 inhibitor (cardiovascular composite HR 0.67 in SGLT2 inhibitor users versus HR 0.87 in non-users, p-interaction 0.46). The key decision point is persistent albuminuria (UACR ≥30 mg/g) despite RAAS inhibitor plus SGLT2 inhibitor.

CONFIDENCE demonstrated simultaneous finerenone plus SGLT2 inhibitor achieved 52% UACR reduction—superior to either alone. For patients on GLP-1 receptor agonist, finerenone addresses complementary mechanisms: GLP-1 receptor agonist provides glycemic control, weight reduction, and cardiovascular protection through incretin pathways, while finerenone targets MR-mediated inflammation and fibrosis, reduces albuminuria, and prevents heart failure progression.

KDIGO 2024 positions finerenone as third pillar after RAAS inhibitor plus SGLT2 inhibitor if albuminuria persists. Practical approach: if patient on SGLT2 inhibitor or GLP-1 receptor agonist (or both) still has UACR ≥30 mg/g, eGFR ≥25, and potassium ≤5.0 mEq/L, add finerenone. Monitor potassium at 4 weeks. SGLT2 inhibitor co-administration actually reduces hyperkalemia risk (8.1% versus 18.7% without SGLT2 inhibitor in FIDELITY)—making the combination safer.

The four-pillar approach (RAAS inhibitor plus SGLT2 inhibitor plus finerenone plus GLP-1 receptor agonist) addresses different pathophysiological nodes for comprehensive cardiorenal-metabolic protection.