Secondary Increase of Lactate Levels in Asphyxiated Newborns during Hypothermia Treatment: Reflect of Suboptimal Hemodynamics (A Case Series and Review of the Literature)
Bibliographic record
Abstract
Objective To evaluate whether a secondary increase of serum lactate levels in asphyxiated newborns during hypothermia treatment may reflect suboptimal dynamics. Methods-Retrospective case series and review of the literature. We present the clinical course of four asphyxiated newborns treated with hypothermia who presented with hypotension requiring inotropic support, and who displayed a secondary increase of serum lactate levels during hypothermia treatment. Serial serum lactate levels are correlated with blood pressure and inotropic support within the first 96 hours of life. Results Lactate levels initially decreased in the four patients. However, each of them started to present lower blood pressure, and lactate levels started to increase again. Inotropic support was started to raise blood pressure. The introduction of an epinephrine drip consistently worsened the increase of lactate levels in these newborns, whereas dopamine and dobutamine enabled the clearance of lactate in addition to raising the blood pressure. Rewarming was associated with hemodynamics perturbations (a decrease of blood pressure and/or an increase of lactate levels) in the three newborns who survived. Conclusions Lactate levels during the first 4 days of life should be followed as a potential marker for suboptimal hemodynamic status in term asphyxiated newborns treated with hypothermia, for whom the maintenance of homeostasis during hypothermia treatment is of utmost importance to alleviate brain injury.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".