Risk of attention deficit hyperactivity disorder diagnosis following multiple exposures to general anesthesia in the paediatric population: A systematic review and meta-analysis
Bibliographic record
Abstract
Objectives: The risk of attention deficit hyperactivity disorder (ADHD) following multiple exposures to anesthesia has been debated. Our objective was to systematically review the literature to examine the association between multiple exposures to general anesthesia before age 5 and subsequent diagnosis of ADHD. Methods: A systematic search of EMBASE, PubMed, and SCOPUS was performed using key search terms in February 2022. We included studies that: were published after 1980, included only otherwise healthy children who experienced two or more exposures to general anesthetic before age 5, diagnosed ADHD by a medical professional before age 19 years after exposure to general anesthetic, were cross-sectional, case-control, or cohort study, and were published in English. The results (expressed as hazard ratios [HR] and associated 95% confidence intervals [CI]) were pooled using meta-analytic techniques. Studies which did not present their results as HR and 95% CI were analyzed separately. GRADE was used to determine the certainty of the findings. PRISMA guidelines were followed at each stage of the review. Results: Eight studies (196,749 children) were included. Five reported HR and 95% CI and were subsequently pooled for meta-analysis. Multiple exposures to anesthesia were associated with diagnosis of ADHD before the 19th year of life (HR: 1.71; 95% CI: 1.59, 1.84). Two of the three studies not used in the meta-analysis also found an increased risk of ADHD diagnosis following multiple anesthetic exposures. Conclusions: There was an association between multiple early exposures to general anesthesia and later diagnosis of ADHD.
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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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.037 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".