Room-Air Versus Oxygen Administration for Resuscitation of Preterm Infants: The ROAR Study
Bibliographic record
Abstract
OBJECTIVE: We conducted a blinded, prospective, randomized control trial to determine which oxygen-titration strategy was most effective at achieving and maintaining oxygen saturations of 85% to 92% during delivery-room resuscitation. METHODS: Infants born at 32 weeks' gestation or less were resuscitated either with a static concentration of 100% oxygen (high-oxygen group) or using an oxygen-titration strategy starting from a concentration of 100% (moderate-oxygen group), or 21% oxygen (low-oxygen group). In the moderate- and low-oxygen groups, the oxygen concentration was adjusted by 20% every 15 seconds to reach a target oxygen saturation range of 85% to 92%. Treatment failure was defined as a heart rate slower than 100 beats per minute for longer than 30 seconds. RESULTS: The moderate-oxygen group spent a greater proportion of time in the target oxygen saturation range (mean: 0.21 [95% confidence interval: 0.16-0.26]) than the high-oxygen group (mean: 0.11 [95% confidence interval: 0.09-0.14]). Infants in the low-oxygen group were 8 times more likely to meet the criteria for treatment failure than those in the high-oxygen group (24% vs 3%; P = .022). The 3 groups did not differ significantly in the time to reach the target oxygen saturation range. CONCLUSIONS: Titrating from an initial oxygen concentration of 100% was more effective than giving a static concentration of 100% oxygen in maintaining preterm infants in a target oxygen saturation range. Initiating resuscitation with 21% oxygen resulted in a high treatment-failure rate.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".