Bibliographic record
Abstract
BACKGROUND: Benzodiazepines are being used in neonatal intensive care units for sedation and control of seizures. However, anecdotal reports suggest that their use in infants may be associated with serious adverse effects (AEs). OBJECTIVE: To determine the incidence of AEs from benzodiazepine use in preterm and full-term infants. METHODS: Retrospective chart review of 63 infants who received benzodiazepines as a sedative or anticonvulsant over a 16-month period. RESULTS: Mean +/- SD gestational age of the infants was 33.1 +/- 6.2 weeks, and birth weight was 2.3 +/- 1.2 kg. Median (range) postnatal age at commencement of drug administration was 19 (5-54) days. Forty-one infants received lorazepam, 8 received midazolam, and 14 received both. Ten (16%) of the infants had 14 documented adverse events: seizures (n = 6), hypotension (n = 5), and respiratory depression (n = 3). Using a validated adverse drug reaction probability scale, a probable association with benzodiazepine use was demonstrated in 12 of the AEs. Due to the retrospective nature of the data, a score for definite association was not attainable. Anticonvulsant administration was required for 4 of 6 infants and, in all cases of respiratory depression, ventilatory support was initiated or increased. Two cases of significant hypotension were treated with inotropes. There was no statistically significant correlation between AEs and benzodiazepine dose or concomitant use of inotropes or analgesics (morphine), although most infants had underlying medical conditions or received multiple drugs that may have predisposed them to experience AEs. CONCLUSIONS: Administration of benzodiazepines was frequently associated with AEs in full-term and preterm infants. It is possible that underlying illnesses and concomitant drug use predisposed these effects. Until the benefit-to-risk ratio is determined by further studies, judicious use of benzodiazepines is recommended in this vulnerable population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".