Factors associated with hypothermia within the first 6 hours of life in infants born at ≥340 weeks’ gestation: a multivariable analysis
Bibliographic record
Abstract
Abstract Background Lack of appropriate temperature management has been associated with significant adverse outcomes in preterm and low birthweight neonates. There is a lack of similar investigations in the late preterm (340–366) and term (≥370) neonate population. Our aim was to identify key risk factors as well as clinical outcomes associated with hypothermia in this population. Methods A retrospective chart review was conducted at the Ottawa Hospital including all eligible infants ≥340 weeks’ gestation over a one-month period in November 2020. Infant, maternal, and delivery room variables were collected, including prematurity, maternal temperature, delivery mode, birthweight, and premature rupture of membranes, as well as clinical outcomes such as NICU/SCN admission and length of stay. Regression models were generated, adjusted for covariates, and stepwise regression was performed. Results Four hundred forty infants were included in the analysis; 26.8% (118/440) were hypothermic within 6 hours of delivery. In the multivariable analysis, prematurity, low 5 minute Apgar score (< 7) or need for resuscitation, maternal hypertension, and absence of premature rupture of membranes > 18 hours or suspected maternal infection were significantly associated with hypothermia within 6 hours of delivery (p < 0.05). Multivariable analysis of clinical outcomes demonstrated a significant association between hypothermia within 6 hours of delivery and NICU/SCN admission (OR = 2.87; 95% CI 1.36, 6.04), need for respiratory support or diagnosis of respiratory distress syndrome (OR = 3.94; 95% CI 1.55, 10.50), and length of stay (exp(β) = 1.20; 95% bootstrap CI 1.04, 1.37). Conclusions Our results suggest there are similar factors associated with hypothermia in our study population of infants born at ≥340 weeks’ gestation compared to prior studies in preterm and low-birthweight infants. Furthermore, hypothermia is associated with higher risk of adverse outcomes, which highlights the need to prevent hypothermia in all newborns.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".