Gastric insufflation during cardiopulmonary resuscitation: A study in human cadavers
Bibliographic record
Abstract
Introduction Bag-valve-mask ventilation is the first-line ventilation method during cardiopulmonary resuscitation (CPR). Risks include excessive volume delivery and gastric insufflation, the latter increasing the risk of pneumonia. The efficacy of ventilation can also be reduced by airway closure. We hypothesized that continuous chest compression (CC) could limit the risk of gastric insufflation compared to the recommended 30:2 interrupted CC strategy. This experimental study was performed in human "Thiel" cadavers to assess the respective impact of discontinuous vs. continuous chest compressions on gastric insufflation and ventilation during CPR. Methods The 30:2 interrupted CC technique was compared to continuous CC in 5 non-intubated cadavers over a 6 min-period. Flow and Airway Pressure were measured at the mask. A percutaneous gastrostomy allowed measuring the cumulative gastric insufflated volume. Two additional cadavers were equipped with esophageal and gastric catheters instead of the gastrostomy. Results For the 7 cadavers studied (4 women) median age of death was 79 [74–84] years. After 6 min of CPR, the cumulative gastric insufflation measured in 5 cadavers was markedly reduced during continuous CC compared to the interrupted CC strategy: (1.0 [0.8–4.1] vs. 5.9 [4.0–5.6] L; p < 0.05) while expired minute ventilation was slightly higher during continuous than interrupted CC (1.9 [1.4–2.8] vs. 1.6 [1.1–2.7] L/min; P < 0.05). In 2 additional cadavers, the progressive rise in baseline gastric pressure was lower during continuous CC than interrupted CC (1 and 2 cmH 2 O vs. 12 and 5.8 cmH 2 O). Conclusion Continuous CC significantly reduces the volume of gas insufflated in the stomach compared to the recommended 30:2 interrupted CC strategy. Ventilation actually delivered to the lung is also slightly increased by the strategy.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".