Hemodynamically-Guided Management of Heart Failure Across the Ejection Fraction Spectrum
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Hemodynamically-guided management using an implanted pulmonary artery pressure sensor is indicated to reduce heart failure (HF) hospitalizations in patients with New York Heart Association (NYHA) functional class II-III with a prior HF hospitalization or those with elevated natriuretic peptides. OBJECTIVES: The authors sought to evaluate the effect of left ventricular ejection fraction (EF) on treatment outcomes in the GUIDE-HF (Hemodynamic-GUIDEd management of Heart Failure) randomized trial. METHODS: The GUIDE-HF randomized arm included 1,000 NYHA functional class II-IV patients (with HF hospitalization within the prior 12 months or elevated natriuretic peptides adjusted for EF and body mass index) implanted with a pulmonary artery pressure sensor, randomized 1:1 to a hemodynamically-guided management group (treatment) or a control group (control). The primary endpoint was the composite of HF hospitalizations, urgent HF visits, and all-cause mortality at 12 months. The authors assessed outcomes by EF in guideline-defined subgroups ≤40%, 41%-49%, and ≥50%, within the trial specified pre-COVID-19 period cohort. RESULTS: There were 177 primary events (0.553/patient-year) in the treatment group and 224 events (0.682/patient-year) in the control group (HR: 0.81 [95% CI: 0.66-1.00]; P = 0.049); HF hospitalization was lower in the treatment vs control group (HR: 0.72 [95% CI: 0.57-0.92]; P = 0.0072). Within each EF subgroup, primary endpoint and HF hospitalization rates were lower in the treatment group (HR <1.0 across the EF spectrum). Event rate reduction by EF in the treatment groups was correlated with reduction in pulmonary artery pressures and medication changes. CONCLUSIONS: Hemodynamically-guided HF management decreases HF-related endpoints across the EF spectrum in an expanded patient population of patients with HF. (Hemodynamic-GUIDEd Management of Heart Failure [GUIDE-HF]; NCT03387813).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 it