Association between Brain and Kidney Near-Infrared Spectroscopy and Early Postresuscitation Mortality in Asphyxiated Newborn Piglets
Bibliographic record
Abstract
BACKGROUND: Early outcome predictors after delivery room cardiopulmonary resuscitation (CPR) of asphyxiated newborns are needed. OBJECTIVES: To investigate if cerebral (rScO2) and renal (rSrO2) tissue oxygen saturation 30 min after return of spontaneous circulation (ROSC) are different between surviving versus nonsurviving piglets with asphyxia-induced cardiac arrest and CPR. Further, to investigate the relationship of rScO2 and rSrO2 to cardiac output (CO), blood pressure (BP), and biochemical variables 30 min and 4 h after ROSC. METHODS: Anesthetized, mechanically ventilated piglets (1-3 days, 1.7-2.4 kg) were used. rScO2, rSrO2, SpO2, right common carotid artery flow, and arterial BP were measured continuously. CO was measured with echocardiography. The piglets were asphyxiated until cardiac arrest and resuscitated. Piglets that survived 4 h after ROSC (n = 12) were compared with piglets that died before planned euthanasia at 4 h (n = 13). Left ventricular, and kidney and brain tissue lactate were analyzed. Correlations between variables were assessed. RESULTS: Thirty minutes after ROSC, median rSrO2 (43% [n = 10] vs. 25% [n = 2], p = 0.003) but not rScO2 (46% [41-55] [n = 10] vs. 40% [22-45] [n = 5], p = 0.08) was higher in survivors than in nonsurvivors. Arterial lactate was negatively correlated and pH positively correlated with rScO2 and rSrO2. Left ventricular, but not kidney or brain lactate was negatively correlated with rScO2 and rSrO2. There was no correlation between CO or BP and rScO2 or rSrO2. CONCLUSIONS: Despite satisfactory CO and BP vital organ oxygenation can be poor. Tissue oxygen saturation, pH, and lactate, as measures of anaerobic metabolism, may reflect vital organ oxygenation and 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".