Neonatal Intensive Care Unit Admission Temperatures of Infants 1500 g or More
Bibliographic record
Abstract
BACKGROUND: Smaller preterm infants often receive extra attention with implementation of additional thermoregulation interventions in the delivery room. Yet, these bundles of interventions have largely remained understudied in larger infants. PURPOSE: The purpose of this study was to evaluate initial (or admission) temperatures of infants born weighing 1500 g or more with diagnoses requiring admission to the neonatal intensive care unit (NICU). METHODS: Retrospective medical record review of 388 infants weighing 1500 g or more admitted to the NICU between January 2016 and June 2017. RESULT: In total, 42.5% of infants weighing 1500 g or more were admitted hypothermic (<36.5°C), 54.4% with a normothermic temperature, and 2.8% were hyperthermic. Of those infants admitted hypothermic, 30.4% had an admission temperature ranging from 36°C to 36.4°C and 12.1% had an admission temperature of less than 36°C. When compared with infants weighing less than 1500 g, who were born at the same institution and received extra thermal support interventions, there was a statistically significant difference (P < .001) between admission temperatures where infants less than 1500 g were slightly warmer (36.8°C vs 36.5°C). IMPLICATIONS FOR PRACTICE: Ongoing admission temperature monitoring of all infants requiring NICU admission regardless of birth weight or admission diagnosis is important if we are going to provide the best support to decrease mortality and morbidity for this high-risk population. IMPLICATIONS FOR RESEARCH: While this study examined short-term outcomes, effects on long-term outcomes were not addressed. Findings could be used to design targeted interventions to support thermal regulation for all high-risk infants. CONCLUSION: Neonates admitted to the NICU weighing 1500 g or more are at high risk for developing hypothermia, similar to smaller preterm infants.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".