Neonatal Abstinence Syndrome and Preterm Infants
Bibliographic record
Abstract
BACKGROUND/SIGNIFICANCE: Intrauterine opioid drug exposure is associated with an increased risk of preterm birth. Preterm infants may not exhibit the same withdrawal symptoms as term infants diagnosed with neonatal abstinence syndrome (NAS). There are no current standards for how to screen, assess, or treat NAS in preterm infants. PURPOSE: This study explored the current state of practice for preterm infants born at less than 34 weeks of gestational age exposed to intrauterine opioids. METHODS: This was a descriptive cross-sectional study of NAS practice in preterm infants born at less than 34 weeks of gestational age in neonatal intensive care units (NICUs) in the United States and Canada. The study was conducted May through September 2018. All respondents cared for preterm infants born at less than 34 weeks of gestational age exposed to intrauterine drugs. RESULTS: There were 70 respondents representing 67 hospitals in the United States and 1 in Canada. Level III NICUs represented 69% of respondents. Ninety-three percent reported neonatal triggers for further evaluation. Review of maternal history and maternal urine testing was the most consistent practice across NICUs. A modified Finnegan scoring tool was used for both preterm and term infants. Morphine was reported as the most common first-line drug used for treatment. IMPLICATIONS FOR PRACTICE: Great variability in NAS practice for preterm infants born at less than 34 weeks of gestational age across the multiple NICUs supports the need for a validated preterm infant assessment tool and development of appropriate treatment strategies. IMPLICATIONS FOR RESEARCH: Future research describing the NAS symptomatology of preterm infants born at less than 34 weeks of gestational age exposed to intrauterine opioids is warranted.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".