Efficacy of empagliflozin in heart failure with preserved ejection fraction according to frailty status in EMPEROR‐Preserved
Bibliographic record
Abstract
BACKGROUND: Frailty is a severe, common co-morbidity associated with heart failure (HF) with preserved ejection fraction (HFpEF). The impact of frailty on HFpEF outcomes may affect treatment choices in HFpEF. The impact of frailty on HFpEF patients and any impact on the clinical benefits of sodium glucose co-transporter 2 (SGLT2) inhibition in HFpEF have been described in only a limited number of trials. Whether the SGLT2 inhibitor empagliflozin would improve or worsen frailty status when given to HFpEF patients is also not known. The aims of this study were, therefore, to evaluate, in HFpEF patients enrolled in the EMPEROR-Preserved trial (Empagliflozin Outcome Trial in Patients With Chronic Heart Failure With Preserved Ejection Fraction), the impact of frailty on clinical outcomes, and on the effects of empagliflozin, as well as the effect of empagliflozin on frailty status during treatment period. METHODS: We calculated a cumulative deficit-derived frailty index (FI) using 44 variables including clinical, laboratory and quality of life parameters recorded in EMPEROR-Preserved. Patients were classified into four groups: non-frail (FI < 0.21), mild frailty (0.21 to <0.30), moderate frailty (0.30 to <0.40) and severe frailty (≥0.40). Clinical outcomes and health-related quality of life were evaluated according to baseline FI along with the effect of empagliflozin on chronological changes in FI (at 12, 32 and 52 weeks). RESULTS: The patient distribution was 1514 (25.3%), 2100 (35.1%), 1501 (25.1%) and 873 (14.6%) in non-frail, mild frailty, moderate frailty and severe frailty, respectively. Severe frailty patients tended to be female and have low Kansas City Cardiomyopathy Questionnaire (KCCQ) scores, more co-morbidities and more polypharmacy. Incidence rates of the primary outcome of cardiovascular death or HF hospitalization increased as frailty worsened (hazard ratio [HR] of each FI category compared with the non-frail group: 1.10 [95% confidence interval, CI, 0.89-1.35], 2.00 [1.63-2.47] and 2.61 [2.08-3.27] in the mild frailty, moderate frailty and severe frailty groups, respectively; P trend < 0.001). Compared with placebo, empagliflozin reduced the risk for the primary outcome across the four FI categories, HR: 0.59 [95% CI 0.42-0.83], 0.79 [0.61-1.01], 0.77 [0.61-0.96] and 0.90 [0.69-1.16] in non-frail to severe frailty categories, respectively (P value for trend = 0.097). Empagliflozin also improved other clinical outcomes and KCCQ score across frailty categories. Compared with placebo, empagliflozin-treated patients had a higher likelihood of being in a lower FI category at Weeks 12, 32 and 52 (P < 0.05), odds ratio: 1.12 [95% CI 1.01-1.24] at Week 12, 1.21 [1.09-1.34] at Week 32 and 1.20 [1.09-1.33] at Week 52. CONCLUSIONS: Empagliflozin improved key efficacy outcomes with a possible diminution of effect in very frail patients. Empagliflozin also improved frailty status during follow-up.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".