We prospectively evaluated a consecutive cohort of patients who attended a routine follow-up visit in Spanish HF clinics at 13 tertiary hospitals, regardless of baseline estimated glomerular filtration rate (eGFR) from October 2021 to February 2022. Diagnosis of HF was performed according to current European guidelines.11 The only exclusion criterion was refusal to participate.

Data were collected on patient demographics, medical history, medical and device therapy at baseline, vital signs, and physical examination. Clinical congestion was assessed by the composite congestion score (CCS), which included orthopnea (0-3), leg edema (0-3), and jugular engorgement (0-3).12 All the variables were previously specified and communicated to the research team, who had training meetings prior to the start of the study. Data on medical treatment were obtained directly from the patient's history and was verified with the electronic prescription data.

This study complied with the Declaration of Helsinki and was approved by the ethics committees of participating centers. Informed consent was obtained from all patients.

Blood and urine tests were assessed at baseline (within a 48-hour window from inclusion) and were analyzed in the local laboratory at each center. eGFR was calculated based on creatinine levels using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation and stratified according to KDIGO 2012 classification into 4 clinical strata: <30 mL/min/1.73 m2 (G4-G5); 30-44 mL/min/1.73 m2 (G3b), 45-59 mL/min/1.73 m2 (G3a), or ≥ 60 mL/min/1.73 m2.13 All patients had a prior eGFR assessment available in their medical chart for eGFR confirmation. The urine albumin-creatinine ratio was assessed in the first-morning urine sample, and albuminuria was stratified into 3 categories: A1 (normal to mildly increased): <30mg/g, A2 (moderately increased): 30-300mg/g, and A3 (severely increased):> 300mg/g.

Continuous variables are presented as median [interquartile range (IQR)]. Categorical variables are expressed as percentages. Comparisons across eGFR categories were performed by the chi-square test for categorical variables. For continuous variables, 1 -way analysis of variance (ANOVA) and the Kruskal-Wallis test were used for variables with normal and nonnormal distribution, respectively. The variables associated with eGFR were evaluated by multivariate linear regression analysis. The contribution of the exposures to the proportion of the dependent variable variation was evaluated by R2. We simultaneously tested the linearity assumption for all continuous variables, and the variables were transformed with fractional polynomials when appropriate. Next, we derived a reduced and parsimonious model using backward step-down selection on prior knowledge/biological plausibility, independent of the P-value. We set a 2 -sided P <.05 as the threshold for statistical significance. The covariates included in the final model were age, sex, hypertension, smoking, chronic obstructive pulmonary disease (COPD), ictus, dementia, baseline baselinediastolic blood pressure, left ventricular ejection fraction (LVEF), CA125 levels, renin-angiotensin system inhibitor (RASi), sodium-glucose cotransporter inhibitors (SGLT2i), mineralcorticoid receptor antagonists (MRA), beta-blockers, and baseline baselinefurosemide dose. Multinomial logistic regression analysis was performed to evaluate the association between HF with reduced ejection fraction (HFrEF) therapies according to eGFR. This model was adjusted for age, sex, tobacco use, hypertension, dyslipidemia, diabetes mellitus, ischemic cardiomyopathy, valvular disease, atrial fibrillation, COPD, ictus, cancer, CKD, dementia, heart rate, and systolic and diastolic blood pressure. Stata 15.1 (Stata Statistical Software, Release 15, 2017; StataCorp LP, United States) was used for these analyses.

Demographics, baseline characteristics, and pharmacological treatment stratified according to eGFR categories are summarized in table 1. The distribution of the sample across eGFR categories was: 453 (40.9%) G1 and G2 categories, 208 (18.8%) G3a category, 267 (24.1%) G3b category, and 179 (16.2%) G4 and G5 categories. Of note, 122 (11%) patients with eGFR ≥ 60 mL/min/1.73m2 had a UACR ≥ 30 mg/g (table 2). Overall, the baseline risk profile worsened from higher to lower eGFR. Similarly, patients with severely reduced eGFR (< 30 mL/min/1.73 m2) showed higher NTproBPN [3595 (1411-8591) vs 1213 (508-2776); P <.001] and CA125 [25 (13-63) vs 14 (9-24), P <.001)] plasma levels and were more likely to have anemia (P <.001) and hyperkalemia (serum potassium ≥ 5.5 mEq/L) (P <.001). The HF phenotype also differed across eGFR strata. LVEF progressively increased from higher to lower eGFR categories. In fact, more than half (54.2%) of the patients with severely reduced eGFR (G4 and G5 categories) had a preserved LVEF.

Multivariate analysis revealed that independent variables associated with lower eGFR were, in order of importance (and explaining up to 82% of the model variability): age (negative, R2: 62%, P <.001) and furosemide dose (negative, R2: 21%, P <.001). Among other covariates associated with lower eGFR, CA125 showed an inverse and linear relationship with eGFR (R2: 1%, P=.002), whereas the association was positive and linear for diastolic blood pressure and LVEF (R2: 2%, P <.001 and R2: 1%, P <.001, respectively) (figure 2). The R2 value of the model was 47%.

Figure 2.

Predictors of eGFR after multivariate analysis. CA125, cancer antigen 125; CKD, chronic kidney disease; DBP, diastolic blood pressure; DM, diabetes mellitus; eGFR, estimated glomerular filtration rate; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonists; RASi, renin-angiotensin system inhibitors.

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In the overall population (regardless of LVEF), the prescription of loop diuretics and thiazides progressively increased from higher to lower eGFR categories. Almost 30% of patients with an eGFR <30 mL/min/1.73 m2 were on furosemide plus thiazides at inclusion in the registry. A similar pattern was observed with furosemide equivalent doses, with higher doses in patients with lower eGFR.

Of the entire sample, 526 patients (48%) had HFrEF (LVEF ≤ 40%). When we analyzed the prescription of guideline-directed therapy across eGFR strata among patients with HFrEF, we observed that the percentage of patients prescribed renin-angiotensin system inhibitors (RASi), angiotensin receptor-neprilysin inhibitors (ARNI), sodium-glucose cotransporter inhibitors (SGLT2i), or mineralocorticoid receptor antagonist (MRA) progressively decreased from higher to lower eGFR categories (figure 3). Among patients with eGFR ≥ 45 mL/min/1.73 m2, implementation therapy was similar, with more than 90% prescribed RASi or ARNI, 80% MRAs, and 70% SGLT2i. In patients with eGFR <45 mL/min/1.73 m2, the proportions of patients receiving these therapies were lower but was higher than 50%. When evaluating the proportions of patients on triple or quadruple therapy, we found high implementation in patients with eGFR ≥ 45 mL/min/1.73 m2 (more than 70% and 60% respectively), and moderate implementation (> 40% and> 30% respectively) in those with eGFR <45 mL/min/1.73m2. These differences persisted after adjustment for comorbidities and medication use in the multivariable analysis compared with patients with eGFR>60 mL/min/1.73 m2 (reference category) (table 3).

Figure 3.

Percentage of treatments by estimated glomerular filtration rate (eGFR) strata among patients with heart failure with reduced ejection fraction (HFrEF). ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin II receptor blockers; ARNi, angiotensin receptor-neprilysin inhibitors; MRA, mineralocorticoid receptor antagonists; SLGT2i, sodium-glucose cotransporter inhibitors.

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On the other hand, 419 patients (37.9%) and 162 patients (14.6%) had HFpEF and HF with mildly reduced ejection fraction, respectively. Patterns of use of guideline-directed medical therapies in patients with HFmrEF were closer to HFrEF patients, whereas lower rates were noted in patients with HFpEF (figure 4).

Figure 4.

Percentage of treatments by estimated glomerular filtration rate (eGFR) strata among patients with heart failure with mildly reduced ejection fraction (HFmrEF) and preserved ejection fraction (HFpEF). ACEI, angiotensin-converting enzyme inhibitors; ARB, angiotensin II receptor blockers; ARNi, angiotensin receptor-neprilysin inhibitors; MRA, mineralocorticoid receptor antagonists; SLGT2i, sodium-glucose cotransporter inhibitors.

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Guideline-directed medical therapy has been shown to reduce morbidity and mortality in patients with HFrEF and is recommended as a class I indication in clinical practice guidelines for patients with HFrEF.11 However, patients with advanced CKD have been traditionally excluded from cardiovascular clinical trials. Since these drugs may induce an initial eGFR decline, clinicians often struggle to initiate or up-titrate these therapies, as any deterioration in kidney function is often perceived as deleterious.18–20 Indeed, the presence of kidney disease is one of the main reasons for ineffective drug implementation in HF patients, even in patients with mild to moderate CKD.8,10

This trend was also observed in the present cohort, in which the proportion of patients receiving guideline-directed medical therapy (GDMT) decreased in parallel to the eGFR decline. Nonetheless, it is important to highlight that the implementation of GDMT across eGFR strata is among the highest reported in the literature. For instance, the Swedish HF registry has recently published the prescription of guideline-recommended therapies in 31 668 patients with HF, according to eGFR.8 In this registry, the proportions receiving triple therapy (combination of RASi/ARNI+MRA+beta-blockers) were 38%, 35%, 28%, and 15% for eGFR ≥ 60, 45-59, 30-44, and <30 mL/min/1.73 m2, respectively. Although the baseline characteristics were slightly different, these implementation rates are far from the proportions of GDMT achieved in our study, in which the patients receiving triple therapy were significantly higher, even in those with advanced CKD. Finally, the proportion of devices is higher than that reported in other registries or contemporaneous HFrEF trials such as the DAPA HF trial, in which the use of ICDs was 26%.21

On the other hand, the 2021 European Society of Cardiology guidelines included treatment recommendations for patients with HF and mildly reduced LVEF (class IIb recommendations),11 whereas no specific treatment for HFpEF was updated. We describe prescriptions patterns in both the HFmrEF and HFpEF populations. Implementation therapy was similar to that in previous reports with the use of RASi and beta-blockers.22,23 However, MRNA use was higher. In addition, about 40% of our HFpEF patients were on SGLT2i therapy, regardless of kidney function. The use of SGLT2i in this population was probably partly due to the prevalence of diabetes mellitus and the novel evidence of the benefits of this therapy in HFpEF.24.

Another possible explanation for all these differences might be that this population comes from specific HF programs, which may be a potential source of bias but also highlights the possible advantages of these structured and specialized models of care.

The present registry reinforces the message that the prevalence of kidney disease in real-life patients with HF is remarkably high. Population longevity, the increased prevalence of cardiovascular risk factors, and associated comorbidities have probably contributed to the growth of this phenotype of cardiorenal disease, characterized by older age, a high burden of comorbidities and congestion, and preserved LVEF. Therefore, clinicians should be aware of this emerging entity and its clinical implications. Early diagnosis and multidisciplinary teamwork could lead to the early initiation of disease-modifying therapies and a more personalized and structured approach. In addition, developing specific coordinated cardiorenal management programs to improve diagnosis and offer appropriate evidence-based therapies, education, and suitable follow-up may improve outcomes in this increasingly complex population.25

This study has some limitations. First, although all patients had a prior eGFR assessment available in their medical chart, this measurement was not prespecified within a specific time interval. Accordingly, the measurement at the moment of inclusion may have misclassified some patients. However, this is the information commonly available in routine clinical practice. In addition, albuminuria was not determined in 17% of the patients, which could have modified the classification of CKD in some patients. Second, patients were enrolled in specialized HF clinics. Therefore, extrapolation to other follow-up approaches, countries, or health care systems needs to be performed with caution. Third, even though the registry protocol required consecutive enrolment, we cannot guarantee that this requirement was respected in all centers, and information on refusal to participate was not collected. Fourth, we acknowledge that the information on pharmacy fills may not necessarily mean that the pills are being ingested.