Neurotoxicity of sedative and analgesia drugs in young infants with congenital heart disease: 4‐year follow‐up
Bibliographic record
Abstract
OBJECTIVES/AIM: To determine whether sedation/analgesia drugs used before, during, and after infant cardiac surgery are associated with neurocognitive and functional outcomes. BACKGROUND: Some animal models suggest neurotoxic effects of anesthetic drugs on the developing brain; however, potential human effects are unknown. Whether these results can be extrapolated to humans is unknown. METHODS/MATERIALS: Prospective follow-up project of all infants ≤6 weeks old having surgery for congenital heart disease between 04/03 and 12/06. Demographic, perioperative, and sedation/analgesia variables were collected. Outcomes at kindergarten age were Wechsler Preschool and Primary Scale of Intelligence-III, Beery-Buktenica Developmental Test of Visual Motor Integration (VMI-V), and General Adaptive Composite (GAC) of the Adaptive Behavior Assessment System-II. Multivariable linear regression was used to identify predictor variables. RESULTS: From 135 infants who underwent heart surgery, 19 died, 17 were excluded, 8 were lost to follow-up, leaving 91 children for analysis. Multiple linear regression found days on chloral hydrate [3.5 (3.7) days] was associated with lower performance intelligence quotient (PIQ) (Effect size -1.03; 95% CI -1.96, -0.10; P = 0.03), and cumulative dose [54.2 (60.3) mg·kg(-1) ] of benzodiazepines was associated with lower VMI scores (Effect size -0.07; 95% CI -0.12, -0.01; P = 0.026). No other associations were found between sedation/analgesia variables and full-scale IQ, PIQ, Verbal IQ, VMI, or GAC. CONCLUSION: Assessment of this cohort at kindergarten age found a small statistically significant association between days on chloral hydrate and PIQ, and benzodiazepine cumulative dose and lower VMI. No other association between sedation/analgesia drugs and outcomes was found.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".