Changes in pCO<sub>2</sub> During Air-Medical Transport of Children with Closed Head Injuries
Bibliographic record
Abstract
Introduction: Inappropriate management of pCO 2 following head-injury can adversely affect outcome.We studied whether the optimal pCO 2 level was maintained in ventilated children with closed-head injuries transported by paramedics, and whether hand-bagging or mechanical ventilation resulted in better pCO 2 levels.Methods: Hospital charts and transport records were reviewed for all head-injured children transported by a specialized paramedic team to tertiary care over a 12month period.All of the children were intubated and mechanically or manually ventilated.Outcome measures were final pCO 2 prior to transport and first pCO 2 on arrival in the ICU.Results: 29 children (age 0.6 to 16 years, median 6 years) met the criteria, 14 hand bagged (HB) and 15 mechanically ventilated (MV).11 patients started in the target pCO 2 range of 35-45 mmHg: 5 HB and 6 MV.Following transport, 1 hand-bagged patient and 9 mechanically-ventilated patients had pCO 2 values within the target range.The duration of transport (range 15-200 minutes) did not contribute to final pCO 2 level.Conclusions: Mechanical ventilation is preferable to hand-bagging.Those managing head-injured patients in a disaster need to be aware that hand-bagging significantly increases the incidence of sub-optimal pCO 2 levels and the risk of sub-optimal cerebral blood flow, and that monitoring of CO 2 (e.g., by point-of-care testing) is desirable.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".