75: Initiation of Passive Cooling at Referring Center is Most Predictive of Achieving Early Therapeutic Hypothermia in Asphyxiated Newborns
Bibliographic record
Abstract
Therapeutic hypothermia (TH) for infants with perinatal asphyxia is effective at reducing death or disability. Current evidence suggests that the sooner cooling is commenced, the more likely it is to be beneficial. To identify factors associated with early achievement of TH (core temperature 33–34 degrees) in two Ontario outborn level 3 NICUs. Retrospective cohort study of asphyxiated newborns who received TH according to NICHD criteria in two academic level 3 Neonatal Intensive Care Units (NICU): SickKids (Toronto; January 2009 to December 2010) and CHEO (Ottawa; October 2009 to December 2013). All infants were transported by a neonatal transport team (NNTT). Multivariate linear regression including who initiated cooling and degree of resuscitation in the model was performed. The combined cohort is described in Table 1. Need for extensive resuscitation (CPR or epinephrine) was strongly associated with earlier initiation of TH (1.4 h, P=0.001). Waiting for advice from our tertiary care centers was associated with a 1.2 h delay (95% CI 0.5 – 2) in initiation of TH. Waiting for the NNTT to initiate cooling was associated with a delay of 2.5 h (95% CI 1.7 – 3.3) while waiting for admission to the NICU delayed onset by 5.7 h. Age at initiation of cooling was the only factor associated with age when TH was achieved, with each 1 h of delay being associated with a 0.8 h delay in reaching target core temperature. Gestational age, birth weight and site in the multivariate models did not change the findings significantly. Initiating passive cooling at the referring center, before transfer, is critical to earlier initiation and faster achievement of target core temperature in asphyxiated infants. Greater outreach education and development of clinical care pathways are needed to improve optimal delivery of TH to enhance outcome.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".