The Association between Hyperlactatemia and Adverse Long-Term Outcome in Infants With Moderate-To-Severe Hypoxic Ischemic Encephalopathy
Bibliographic record
Abstract
Abstract BACKGROUND: Hypoxic ischemic encephalopathy (HIE) remains one of the most devastating events in the newborn period. Lactate is invariably produced with hypoxia and poor tissue perfusion. Initial highest lactate in the first hour of life and serial measurements of blood lactate have been found to be important predictors of moderate to severe neonatal encepha-lopathy in cases of intrapartum asphyxia. OBJECTIVES: To examine the association between initial lactate level and the long term adverse outcome in infants with moderate to severe HIE (HIE II/III). We hypothesized that the level and duration to normalize hyperlactatemia in HIE infants can predict long term adverse neurodevel-opmental outcome. DESIGN/METHODS: A retrospective chart and database review for all infants ≥ 35 weeks gestational age treated in the Northern Alberta Neonatal Program with HIE II/III from January 2006 to December 2012 (excluding infants who were growth restricted or with major congenital anomalies). The primary outcome was composite of death or any disability (cerebral palsy, cognitive delay <2SD below the mean, hearing loss and blindness) at 18 months or 3 years of age. Univariate and multivariable regression analyses were used to compare the outcome. RESULTS: Of 167 infants, 106 had initial lactate >5.0mmol/L (63%) and 48 had initial lactate 16mmol/L is significant (P0.0015) for detection of adverse outcome; sensitivity 29.3% and specificity 90.5%. CONCLUSION: Most term/near term infants with HIE II/III had initial lactate > 5mmol/L. Initial lactate >16 mmol/L and duration to normalization of lactate levels was associated with the adverse 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 | 0.002 |
| 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 | 0.000 |
| 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".