2: Impact of Admission Temperature on Mortality and Major Morbidities in Very Preterm Infants
Bibliographic record
Abstract
There have been limited investigations of the influence of admission body temperature on neonatal outcomes. Optimal ranges of admission temperature associated with mortality and morbidity are still unclear. To examine the impact of admission temperature on adverse neonatal outcomes and to identify optimal ranges of temperature in very preterm infants. Inborn neonates with gestational age <33 weeks admitted to Neonatal Intensive Care Units (NICUs) in Canadian Neonatal Network between 2010 and 2012 were included. Neonates with major congenital anomalies were excluded. The admission temperature measured within 5 h after admission to NICU was classified into nine groups starting from <34.5°C to ≥38°C with 0.5°C increment. The composite outcome was defined as mortality or any major morbidity including bronchopulmonary dysplasia(BPD), necrotizing enterocolitis(NEC), nosocomial infection(NI), severe intraventricular haemorrhage or periventricular leukomalacia and severe retinopathy of prematurity (ROP). The relationship between admission temperature and composite outcome and individual components of composite outcome identified in univariate analyses were further examined and used to determine the optimal temperature range using multivariable analyses. Of all 9833 neonates, 12%, 24%, 38%, 19%, 5%, and 2% of neonates had admission temperature <36°C, 36°C to 36.4°C, 36.5°C to 36.9°C, 37°C to 37.4°C, 37.5°C to 37.9°C, ≥38°C respectively. After adjustment for related maternal and infants characteristics, admission temperature was inversely related to mortality (19.5% increase per 0.5°C decrease) and a significant ‘U’ shaped relationship between admission temperature and composite outcome, NEC, ROP, BPD, and NI was observed, respectively .The rates of composite outcome, NEC, ROP, BPD, NI were lowest when the admission temperature was between 36.5°C and 37.4°C. Admission temperature in very preterm infants is associated with mortality and major morbidities. The optimal admission temperature in preterm infants ranged between 36.5°C and 37.4°C. This is the first outcome-based and population-based study in our knowledge with findings of optimal range of temperatures in very preterm infants consistent with WHO's recommendations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".