Synergistic Impact of Systolic Blood Pressure and Perfusion Status on Mortality in Acute Heart Failure
Bibliographic record
Abstract
Background: Physical examination remains the cornerstone in the assessment of acute heart failure. There is a lack of adequately powered studies assessing the combined impact of both systolic blood pressure (SBP) and hypoperfusion on short-term mortality. Methods: Patients with acute heart failure from 41 Spanish emergency departments were recruited consecutively in 3 time periods between 2011 and 2016. Logistic regression models were used to assess the association of 30-day mortality with SBP (<90, 90–109, 110–129, and ≥130 mm Hg) and with manifestations of hypoperfusion (cold skin, cutaneous pallor, delayed capillary refill, livedo reticularis, and mental confusion) at admission. Results: Among 10 979 patients, 1143 died within the first 30 days (10.2%). There was an inverse association between 30-day mortality and initial SBP (35.4%, 18.9%, 12.4%, and 7.5% for SBP<90, SBP 90–109, SBP 110–129, and SBP≥130 mm Hg, respectively; P <0.001) and a positive association with hypoperfusion (8.0%, 14.8%, and 27.6% for those with none, 1, ≥2 signs/symptoms of hypoperfusion, respectively; P <0.001). After adjustment for 11 risk factors, the prognostic impact of hypoperfusion on 30-day mortality varied across SBP categories: SBP≥130 mm Hg (odds ratio [OR]=1.03 [95% CI, 0.77–1.36] and OR=1.18 [95% CI, 0.86–1.62] for 1 and ≥2 compared with 0 manifestations of hypoperfusion), SBP 110 to 129 mm Hg (OR=1.23 [95% CI, 0.86–1.77] and OR=2.18 [95% CI, 1.44–3.31], respectively), SBP 90 to 109 mm Hg (OR=1.29 [95% CI, 0.79–2.10] and OR=2.24 [95% CI, 1.36–3.66], respectively), and SBP<90 mm Hg (OR=1.34 [95% CI, 0.45–4.01] and OR=3.22 [95% CI, 1.30–7.97], respectively); P -for-interaction =0.043. Conclusions: Hypoperfusion confers an incremental risk of 30-day all-cause mortality not only in patients with low SBP but also in normotensive patients. On admission, physical examination plays a major role in determining prognosis in patients with acute heart failure.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".