Clinical update regarding general anesthesia-associated neurotoxicity in infants and children
Bibliographic record
Abstract
PURPOSE OF REVIEW: The U.S. Federal Drug Administration (FDA) recently released a warning stating that 'repeated or lengthy use of general anesthetic and sedation drugs during surgeries or procedures in children younger than 3 years or in pregnant women during their third trimester may affect the development of children's brains' (www.fda.gov/ucm582356.htm). The goal of this article is to review the most recent clinical studies which provide evidence that these concerns may be overstated for the majority of healthy young children who require surgery and anesthesia. RECENT FINDINGS: Three large retrospective matched cohort studies published within the past year provide data on a total of 59 814 children exposed to general anesthesia before age 4 (including 30 021 <2 years and 9814 multiple exposure). All three studies independently conclude that neither exposure to anesthesia in children under 2 years of age nor multiple exposures are associated with adverse neurodevelopmental consequences in the patient populations studied. Biological, environmental, and social factors were found to be of far greater import. SUMMARY: These findings suggest that anesthetic neurotoxicity is not a major contributory pathway for adverse neurodevelopmental outcomes in the majority of healthy children who require surgery before 3 years of age. Future work should focus on the particular vulnerabilities of the fetus, premature infant, and children with developmental disabilities, major congenital, cardiac or neurological abnormalities not specifically addressed by these studies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".