Systolic Blood Pressure and Mortality in Patients with Atrial Fibrillation and Heart Failure: Insights from the AFFIRM and AF-CHF Studies
Bibliographic record
Abstract
AIMS: To investigate the association between baseline systolic blood pressure levels and mortality in patients with AF with or without LV dysfunction. Hypertension leads to cardiovascular disease but, in specific groups, low blood pressure has been associated with a paradoxical increase in mortality. In patients with AF and heart failure, the relationship between blood pressure and death remains largely unknown. METHODS AND RESULTS: We conducted a post-hoc combined analysis on pooled data from AFFIRM and AF-CHF trials and assessed the relationship between baseline systolic blood pressure (SBP) and mortality and hospitalizations. Patients were classified according to LVEF (>40%, ≤40%) and baseline SBP (<120 mmHg, 120-140 mmHg, >140 mmHg). A total of 5436 patients with non-permanent AF were followed for 41 ± 16 months. In patients with LVEF >40%, baseline SBP was not related to mortality using multivariate Cox regression analyses to adjust for baseline differences (P = 0.563). In contrast, in patients with LVEF ≤40% (n = 1980), SBP <120 mmHg and SBP >140 mmHg were both associated with a significant increase in total mortality compared with SBP 120-140 mmHg [hazard ratio (HR) 1.75, 95% confidence interval (CI) 1.41-2.17; and HR 1.40, 95% CI 1.04-1.90, respectively]. Hospitalizations were unrelated to SBP regardless of LVEF. CONCLUSIONS: Mortality is modulated by baseline SBP levels in patients with AF and depressed EF but not in patients with normal EF. Targeted therapy of AF patients based on SBP merits further prospective investigation.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".