Unanswered questions of anesthesia neurotoxicity in the developing brain
Bibliographic record
Abstract
PURPOSE OF REVIEW: This article reviews recent advances and controversies of developmental anesthesia neurotoxicity research with a special focus on the unanswered questions in the field both from clinical and preclinical perspectives. RECENT FINDINGS: Observational cohort studies of prenatal and early childhood exposure to anesthesia have reported mixed evidence of an association with impaired neurodevelopment. Meta-analyses of currently available studies of early childhood exposure to anesthesia suggest that, while limited to no change in general intelligence can be detected, more subtle deficits in specific neurodevelopmental domains including behavior and executive function may be seen. Several studies have evaluated intraoperative blood pressure values and neurocognitive outcomes and have not found an association. Although many animal studies have been performed, taking into consideration other peri-operative exposures such as pain and inflammation may help with translation of results from animal models to humans. SUMMARY: Advances have been made in the field of developmental anesthetic neurotoxicity over the past few years, including the recognition that anesthetic exposure is associated with deficits in certain cognitive domains but not others. Although the most important question of whether anesthetic agents actually cause long-term neurodevelopmental effects in children has still not been answered, results from recent studies will guide further studies necessary to inform clinical decision-making in children.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".