Exercise Oscillatory Ventilation and Prognosis in Heart Failure Patients with Reduced and Mid-Range Ejection Fraction
Bibliographic record
Abstract
AIMS: Exercise oscillatory ventilation (EOV) is a pivotal cardiopulmonary exercise test parameter for the prognostic evaluation of patients with chronic heart failure (HF). It has been described in patients with HF with reduced ejection fraction (<40%, HFrEF) and with HF with preserved ejection fraction (>50%, HFpEF), but no data are available for patients with HF with mid-range ejection fraction (40-49%, HFmrEF). The aim of the study was to evaluate the prognostic role of EOV in HFmrEF patients. METHODS AND RESULTS: We analysed 1239 patients with HFmrEF and 4482 patients with HFrEF, enrolled in the MECKI score database, with a 2-year follow-up. The study endpoint was the composite of cardiovascular death, urgent heart transplant, and ventricular assist device implantation. We identified EOV in 968 cases (16% and 17% of cases in HFmrEF and HFrEF, respectively). HFrEF EOV+ patients were significantly older, and their parameters suggested a more severe HF than HFrEF EOV- patients. A similar behaviour was found in HFmrEF EOV+ vs. EOV- patients. Kaplan-Meier analysis, irrespective of ejection fraction, showed that EOV is associated with a worse survival, and that patients with HFrEF and HFmrEF EOV+ had a significantly worse outcome than the EOV- of the same ejection fraction groups. EOV-associated survival differences in HFmrEF patients started after 18 months of follow-up. CONCLUSION: Exercise oscillatory ventilation has a similar prevalence and ominous prognostic value in both HFmrEF and HFrEF patients, indicating a group of patients in need of a more intensive follow-up and a more aggressive therapy. In HFmrEF, the survival curves between EOV+ and EOV- patients diverged only after 18 months.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".