The importance of maintaining normal perioperative physiological parameters in children during anaesthesia
Bibliographic record
Abstract
Every year, millions of neonates, infants and young children need general anesthesia for a variety of procedures. As pediatric anesthesia remains at high risk of perioperative morbidity and mortality, attention has been directed towards the anesthesia training and the anesthetics safety. We are now reassured about the relatively safeness of the anesthetic drugs, but the safest intraoperative conduct has still to be determined. In the absence of clear evidence, it appears logical to prevent perturbations of the child “baseline”, by avoiding preoperative distress, maintaining normal intraoperative parameters and preventing postoperative discomfort. Recently, ten “N” principles (no fear/awareness, normovolemia, normotension, normal heart rate, normoxemia, normocapnia, normonatremia, normoglycemia, normotermia and no pain/nausea/vomiting/emergence delirium) have been proposed as the base of a safer anesthesia care. The current paper aims to summarize the current evidence behind the “10-Ns” rational and to help guide anesthesiologists in their practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".