High vs. Low Oxygen Therapy in Patients with Acute Heart Failure: HiLo-HF Pilot Trial
Bibliographic record
Abstract
Abstract Aims Most patients with acute heart failure (AHF) are treated with supplemental oxygen during hospitalization. In this study, we investigated the effect of oxygen titrated to high vs. low pulse oximetry targets in patients hospitalized with AHF. Methods and results In a pilot, open-label randomized controlled trial (RCT), 50 patients who were admitted with AHF were randomized to either high (≥96%) or low (90–92%) SpO2 targets. Oxygen was manually titrated to the assigned target ranges for 72 h. The primary endpoint was the change in N-terminal pro-brain-type natriuretic peptide (NT-proBNP) from randomization to 72 h, and secondary endpoints included patient-reported dyspnoea by visual analogue scale (VAS), patient global assessment (PGA), peak expiratory flow (PEF) within 72 h, and clinical outcomes up to 30 days following hospital discharge. The median age was 73.5 years, and 42% were women. The change in NT-proBNP was −6963 (−13 345, −1253) pg/mL in the high SpO2 group and −2093 (−5692, −353) pg/mL in the low SpO2 group (P = 0.46), and the 72 h to baseline NT-proBNP ratio was similar between groups (0.7 vs. 0.6, P = 0.51). There were no differences between arms in change in dyspnoea VAS (P = 0.86), PGA (P = 0.91), PEF (P = 0.52), in-hospital mortality (4.0% vs. 8.0%, P = 0.50), or 30 day heart failure readmission rates (20.8% vs. 8.7%, P = 0.22). Conclusions In this study, no differences were observed in the primary or secondary outcomes for patients randomized to high vs. low SpO2 targets. Further RCTs with larger sample sizes are warranted to determine the efficacy and safety of oxygen therapy in patients with AHF.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".