Systolic Blood Pressure and Cardiovascular Outcomes in Heart Failure with Preserved Ejection Fraction: An Analysis of the TOPCAT trial
Bibliographic record
Abstract
AIMS: Recent guidelines have advocated for stricter systolic blood pressure (SBP) control in heart failure with preserved ejection fraction (HFpEF), though data regarding the optimal SBP in HFpEF are sparse. METHODS AND RESULTS: We analysed participants from the Americas from the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) study with available baseline and 8-week visit SBP data (n = 1645). We related baseline SBP to several efficacy and safety outcomes. To determine whether blood pressure lowering was responsible for the potential beneficial effects of spironolactone observed in the Americas, we assessed the randomized treatment adjusting for baseline and change in 8-week SBP. The average age was 71.7 ± 9.7 years, 50% were women, and 79% were White. Patients in the lowest baseline SBP quartile were less often female, more often White, had lower body mass index, lower baseline diastolic blood pressure and pulse pressure, and more often had atrial fibrillation. After multivariable adjustment, there was no relationship observed between baseline SBP quartiles and any outcome. Spironolactone reduced SBP by 4.4 ± 0.6 mmHg compared with placebo (and consistently across baseline SBP quartiles). There was minimal change in the treatment effect for all outcomes after adjusting for baseline SBP and 8-week change in SBP. CONCLUSION: No relationship was observed between baseline SBP quartiles and outcomes in TOPCAT. The anti-hypertensive effects of spironolactone did not account for the potential benefit in cardiovascular outcomes in the Americas.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".