Chest Compressions during Sustained Inflations Improve Recovery When Compared to a 3:1 Compression:Ventilation Ratio during Cardiopulmonary Resuscitation in a Neonatal Porcine Model of Asphyxia
Bibliographic record
Abstract
BACKGROUND: Recently, sustained inflations (SI) during chest compression (CC) (CC+SI) have been suggested as an alternative to the current approach during neonatal resuscitation. No previous study compared CC+SI using CC rates of 90/min to the current 3:1 compression:ventilation ratio (C:V). OBJECTIVE: To determine whether CC+SI versus a 3:1 C:V reduces the time to the return of spontaneous circulation (ROSC) and improves hemodynamic recovery in newborn piglets with asphyxia-induced bradycardia. INTERVENTION AND MEASUREMENTS: Term newborn piglets were anesthetized, intubated, instrumented, and exposed to 45-min normocapnic hypoxia followed by asphyxia. Cardiopulmonary resuscitation (CPR) was initiated when the heart rate decreased to 25% of baseline. Piglets were randomized into 3 groups: CC during SI at a rate of 90 CC/min (SI+CC 90, n = 8), a 3:1 C:V using 90 CC and 30 inflations (3:1, n = 8), or a sham group (n = 6). Cardiac function, carotid blood flow, cerebral oxygenation, and respiratory parameters were continuously recorded throughout the experiment. RESULTS: CC+SI significantly reduced the median (IQR) time of ROSC, i.e., 34 s (28-156 s) versus 210 s (72-300 s) in the 3:1 group (p = 0.048). CC+SI also significantly reduced the requirement for 100% oxygen, improved respiratory parameters, and resulted in a similar hemodynamic recovery. CONCLUSIONS: CC+SI during CPR significantly improved ROSC in a porcine model of neonatal resuscitation. This is of considerable clinical relevance because improved respiratory and hemodynamic parameters potentially minimize morbidity and mortality in newborn infants.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".