Chest Compressions During Sustained Inflation During Cardiopulmonary Resuscitation in Newborn Infants Translating Evidence From Animal Studies to the Bedside
Bibliographic record
Abstract
Newborn infants receiving chest compressions in the delivery room have a high incidence of mortality (41%) and short-term neurological morbidity (e.g., 57% hypoxic-ischemic encephalopathy and seizures). Furthermore, infants who have no signs of life at 10 min despite chest compressions have 83% mortality, with 93% of survivors experiencing moderate-to-severe disability. The poor prognosis associated with receiving chest compressions in the delivery room raises questions as to whether improved cardiopulmonary resuscitation methods specifically tailored to the newborn could improve outcomes. Combining chest compressions during sustained inflation (CC+SI) has recently been shown to improve morbidity and mortality outcomes during cardiopulmonary resuscitation. Overall, CC+SI accomplishes the following: 1) significantly reduces time to return of spontaneous circulation, mortality, and epinephrine administration, and improves systemic and regional hemodynamic recovery; 2) significantly increases tidal volume and minute ventilation, and therefore alveolar oxygen delivery; 3) allows for passive ventilation during chest compression; and 4) does not increase lung or brain injury markers compared with the current standard of using 3:1 compression:ventilation ratio. A randomized trial comparing CC+SI versus a 3:1 compression:ventilation ratio during cardiopulmonary resuscitation in the delivery room is therefore warranted.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".