66: Temperature Control During Transport in Infants with Evidence of Perinatal Hypoxia-Ischemia Referred for Possible Cooling: A QI Study
Bibliographic record
Abstract
In our tertiary center all infants with evidence of perinatal hypoxia-ischemia are outborn and transported for assessment of level of encephalopathy and need for cooling. Temperature monitoring during transport is a central and challenging component of their management. Given the lack of consensus on whether therapeutic hypothermia should be initiated outside the NICU, the choice of the target temperature is usually made by the neonatologist responsible for the transport. To evaluate the effectiveness of temperature control during transport in infants referred to our tertiary center. From June 2012 to June 2014 medical records of infants with GA ≥36 weeks, birth weight ≥1800 g and <6 h of life at time of referral for possible cooling were reviewed. Data on demographics, severity of fetal acidemia, presence of perinatal events, ages at referral call and NICU admission, assessment on the level of encephalopathy, and temperature at arrival of transport team and admission to our NICU were collected. A total of 131 eligible infants were transported. Temperature monitoring and recording was variable. There was no recorded temperature in 7% of patients at the referring centers and 1.5% at NICU admission. Several different sites were used: axillary, rectal, or esophageal. Normothermia (36–37°C) was recommended in 84% of the cases with recorded temperatures of 36.4±0.9°C at referring center and 36.1±0.9°C at NICU admission. Infants submitted to passive cooling had temperatures of 34.6±1.5°C and 34.2±1.1°C at referring centers and NICU admission, respectively. There were a large proportion of neonates with temperatures outside the desired range (Figure 1). The level of encephalopathy was mostly assessed by the transport nurse (96%), using neurological exam in all cases. At admission 73 infants (56.1%) had either a normal / Sarnat I neurological exam. Five of the 21 infants submitted to passive cooling (24%) had a normal / Sarnat I exam at admission. Two cases of overcooling were observed in the passive cooling (5%) and six cases of overheating (4.5%) in the normal temperature groups. Current temperature monitoring and control of infants with evidence of hypoxia-ischemia transported to our center is sub-optimal and requires the development and implementation of a well defined protocol.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".