Dataset Information

Eligibility of Dapagliflozin and Empagliflozin in a Real-World Heart Failure Population.

ABSTRACT:

Aims

This study is aimed at investigating the eligibility in a real-world heart failure population for the DAPA-HF (testing dapagliflozin) and EMPEROR-reduced (testing empagliflozin) trials, comparing the eligible real-world patients to trial participants and to characterize the noneligible patients.

Methods

Medical records of all heart failure patients who had a diagnosis of heart failure from the Heart Centre or Department of Internal Medicine at Umeå University Hospital were reviewed.

Results

2433 of the hospital's uptake population of 150 000 had a diagnosis of heart failure. 681 patients had left ventricle ejection fraction ≤ 40%, and of these 352 (52%) and 268 (39%) patients met eligibility criteria for DAPA-HF and EMPEROR-reduced, respectively. Comparing eligible patients in our population with the DAPA-HF- and EMPEROR-reduced trial populations, we found that eligible real-world patients were older (79.0 vs. 66.2 years and 80.3 vs. 67.2 years, respectively), had worse renal function (eGFR 54.4 vs. 66.0 ml/min/1.73m² and 49.5 vs. 61.8 ml/min/1.73m², respectively), higher prevalence of atrial fibrillation (56.0% vs. 36.1% and 53.0% vs. 35.6%, respectively), and lower prevalence of diabetes mellitus (21.0% vs. 41.8% and 26.1% vs. 49.8%, respectively). The main reasons for ineligibility were low NT-proBNP or low eGFR. Noneligible patients differed according to reason for ineligibility, where patients with low NT-proBNP were generally younger and healthier, and patients with low eGFR were older and had more comorbidities.

Conclusions

39-52% of patients with heart failure and reduced ejection fraction in this real-world heart failure population were eligible for SGLT2-inhibitor treatment, corresponding to 11-14% of all heart failure patients. Compared to trial participants, eligible real-world patients were significantly older with worse renal function, more atrial fibrillation, and less diabetes mellitus. Trial entry criteria exclude comparatively young and healthy patients, as well as comparatively old patients with more comorbid conditions.

SUBMITTER: Hakansson E

PROVIDER: S-EPMC8720587 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:PurposeGiven known differences between real-world and clinical trial populations, we characterized demographics, clinical characteristics, and outcomes using real-world (RW) data for patients with heart failure with reduced ejection fraction (HFrEF), including those similar to subjects enrolled in an HFrEF clinical trial to better understand patient populations that could benefit from novel therapies.Patients and methodsUsing Vanderbilt University Medical Center electronic health records (2006-2019), two RW cohorts of HFrEF patients were identified. The "Clinical Cohort" was based on a validated HFrEF algorithm and left ventricular ejection fraction (LVEF) ≤40%. The "GALACTIC-HF-like Cohort" mirrored enrollment requirements of the GALACTIC-HF clinical trial including hospitalizations, medications, laboratory values, and LVEF ≤35%.ResultsMedian age at index for the Clinical Cohort (N = 3954) and GALACTIC-HF-like Cohort (N = 1541) were 65 and 61 years, respectively; both were 67% male and 80% white. Over half had coronary artery disease (55% Clinical vs 64% GALACTIC-HF-like); hypercholesterolemia was common (69% Clinical vs 74% GALACTIC-HF-like). Chronic kidney disease (31 vs 21%), atrial fibrillation (32 vs 29%), and cardiac resynchronization or implantable cardioverter defibrillator (26 vs 23%) were higher in the GALACTIC-HF-like Cohort. ACE inhibitor use was high in both groups but more common in the GALACTIC-HF-like Cohort (71% and 82%, respectively). Beta-blockers or loop diuretics were used by >90% of both cohorts. HF hospitalization rates were 261 (95% CI 224, 297) per 1000 person-years in Clinical versus 523 (484, 562) in GALACTIC-HF-like Cohort (median follow-up of 2.9 and 4.2 years, respectively).ConclusionApproximately 40% of RW HFrEF patients met criteria for the GALACTIC-HF trial. While findings of ongoing clinical trials may be directly generalizable to this sizable proportion of patients, future trials should examine whether the majority of patients with lower prevalence of comorbidities and rate of HF hospitalization could benefit from emerging HF treatments.

Project description:AimsThe prognostic significance of renal function variability has not been fully elucidated in heart failure (HF). This multicentre, prospective cohort study aimed to evaluate the usefulness of visit-to-visit variability in estimated glomerular filtration rate (eGFR) for predicting patients' outcomes in a real-world HF population.MethodsA total of 564 patients who had survived HF hospitalization were randomly assigned with a 2:1 ratio to derivation and validation cohorts, and they were then followed after discharge. Using the data for 6 months after discharge, each patient's visit-to-visit eGFR variability (EGV) was estimated. In the derivation cohort, Cox regression analyses were performed to assess the association of EGV with a subsequent composite event (death and HF hospitalization). In the validation cohort, the predictive performance was compared among Cox regression models with EGV, those with B-type natriuretic peptide (BNP) and those with eGFR.ResultsIn the derivation cohort (376 patients), median age, left ventricular ejection fraction (LVEF), BNP and eGFR at discharge were 72 years, 53.3%, 134.8 pg/mL and 58.7 mL/min/1.73 m2 , respectively. During a median follow-up of 2.2 years, higher EGV was associated with an increased risk of the composite event (adjusted hazard ratio [per standard deviation increase in log-transformed EGV], 1.5; 95% confidence interval, 1.1-2.0). A similar finding was observed in a stratified analysis by LVEF. In the validation cohort (188 patients), better model fit, discrimination, reclassification and calibration were observed for EGV than for 6-month averaged BNP or eGFR for predicting the composite event when added to HF risk prediction models. Adding EGV to models with BNP or eGFR improved model discrimination and reclassification.ConclusionsEGV predicts HF outcomes regardless of LVEF. Risk prediction models with EGV have good performance in real-world HF patients. The study findings highlight the clinical importance of observing visit-to-visit fluctuations in renal function in this population.