A comparative post hoc analysis of finerenone and spironolactone in resistant hypertension in moderate-to-advanced chronic kidney disease
Bibliographic record
Abstract
ABSTRACT Background Mineralocorticoid receptor antagonists (MRAs) reduce systolic blood pressure (SBP) and increase serum potassium concentration ([K+]). This indirect comparison investigated any differences in SBP-lowering and hyperkalemia risk between finerenone, a nonsteroidal MRA, and the steroidal MRA spironolactone ± a potassium binder. Methods In FIDELITY (a pooled analysis of FIDELIO-DKD and FIGARO-DKD), a subgroup of patients with treatment-resistant hypertension (TRH) and chronic kidney disease meeting eligibility criteria of the AMBER trial were identified (FIDELITY-TRH). The main outcomes were mean change in SBP, incidence of serum [K+] ≥5.5 mmol/L and hyperkalemia-associated treatment discontinuation. Results at ∼17 weeks were compared with 12 weeks from AMBER. Results In 624 FIDELITY-TRH patients and 295 AMBER patients, the least squares mean change in SBP (mmHg) from baseline was −7.1 for finerenone and −1.3 for placebo {between-group difference −5.74 [95% confidence interval (CI) −7.99 to −3.49], P < .0001} versus −11.7 for spironolactone + patiromer and −10.8 for spironolactone + placebo [between-group difference −1.0 (95% CI −4.4–2.4), P = .58]. The incidence of serum [K+] ≥5.5 mmol/L was 12% for finerenone and 3% for placebo versus 35% with spironolactone + patiromer and 64% with spironolactone + placebo. Treatment discontinuation due to hyperkalemia was 0.3% for finerenone and 0% for placebo versus 7% for spironolactone + patiromer and 23% for spironolactone + placebo. Conclusions In patients with TRH and chronic kidney disease compared with spironolactone with or without patiromer, finerenone was associated with a lower SBP reduction and lower risk of hyperkalemia and treatment discontinuation. Trial Registration: AMBER (NCT03071263), FIDELIO-DKD (NCT02540993), FIGARO-DKD (NCT02545049)
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".