Neurodevelopmental outcome following exposure to sedative and analgesic drugs for complex cardiac surgery in infancy<sup>*</sup>
Bibliographic record
Abstract
OBJECTIVES/AIM: To determine whether sedation/analgesia drugs used before, during, and after infant cardiac surgery are associated with neurodevelopmental outcome. BACKGROUND: Animal models suggest detrimental effects of anesthetic drugs on the developing brain. Whether these results can be extrapolated to human neonates is unclear. METHODS/MATERIALS: This is a prospective follow-up project conducted in Western Canada. In all infants ≤6 weeks of age having surgery for congenital heart disease between April 2003 and December 2006, demographic and perioperative variables were collected prospectively. Sedation/analgesia variables were collected retrospectively. For each drug class (inhalationals, opioids, benzodiazepines, ketamine, and chloral hydrate), we calculated the cumulative dose received during hospitalization, average dose received per day, and cumulative number of days the patient received the drug. The outcomes at 18-24 months were as follows: General Adaptive Composite and motor scaled scores of the Adaptive Behavior Assessment System, significant mental, motor, and vocabulary delay. Multivariable logistic and linear regression was used to analyze the data. RESULTS: One hundred and thirty-five neonates underwent open heart surgery; 19 died, 16 had chromosomal abnormality, and five were lost to follow up, leaving 95 survivors for analysis. Multiple linear regression analysis found no evidence of an association between sedation/analgesia variables and ABAS-GAC score or motor scale score. Multiple logistic regression analysis found no evidence of an association between sedation/analgesia variables and significant mental, motor, or vocabulary delay. CONCLUSION: We found no evidence of an association between dose and duration of sedation/analgesia drugs during the operative and perioperative period and adverse neurodevelopmental outcomes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".