Clinical impact of analgesic-sedative agents and peri-operative clinical status on white matter brain injury in preterm infants following surgical NEC
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The potential influence of exposure to analgesic-sedative agents (ASA) before, during, and after surgical NEC and peri-operative clinical status on white matter injury (WMI) in preterm infants has not been fully defined, and a comprehensive evaluation may inform future research and clinical interventions. METHODS: A retrospective study comparing ASA exposure before/during /after surgical NEC and peri-operative clinical status in neonates with and without WMI. RESULTS: Infants with any WMI (grade 2-4, n = 36/67, 53.7%) had a higher number of surgical procedures receiving ASA (5 [IQR: 3, 8] vs. 3 [2, 4]; p = 0.002) and had a longer duration of hypotension during their first (48.0 hours [26.0, 48.0] vs. 15.5 [6, 48]; p = 0.009) and second surgery (20 hours [0, 48h] vs. 0 [0, 22]; p = 0.017), received more hydrocortisone (35% vs.13.3%,p = 0.04) than those without any WMI. There were no differences in fentanyl/morphine/midazolam exposure before/during/after the NEC onset in the two groups.Infants with severe WMI (19/67, 28.3%, grade 3/4) had a higher incidence of AKI (P = 0.004), surgical morbidity (p = 0.047), more surgical procedures (6.5 [3, 10] vs. 4 [2, 5]; p = 0.012), and received higher mean fentanyl doses(p = 0.03) from birth until NEC onset than those without severe WMI. The univariate associations between these factors and severe WMI remained insignificant after multivariable logistic regression. CONCLUSION: Infants with WMI had more surgical procedures receiving ASA and had a longer duration of hypotension during surgeries. A large multicenter prospective study is needed to understand the full impact of ASA.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it