ASSESSMENT OF HEART RATE USING AUSCULTATION AND ELECTROCARDIOGRAPHY DURING NEONATAL RESUSCITATION IN A PORCINE MODEL OF ASPHYXIA
Bibliographic record
Abstract
Abstract BACKGROUND Recent neonatal resuscitation guidelines have suggested the potential benefit of introducing Electrocardiography (ECG) to monitor neonatal heart rate (HR) as standard of care for newborns receiving respiratory support in the delivery room due to advantages over auscultation. OBJECTIVES To assess effectiveness of HR detection using either ECG or auscultation. DESIGN/METHODS We reviewed recordings from our piglet neonatal resuscitations to compare an ECG with auscultation for assessing the detection of HR at cardiac arrest. Term newborn piglets (n=41) were anesthetized, intubated, instrumented, and exposed to 40-min normocapnic hypoxia followed by asphyxia, which was achieved by clamping the endotracheal tube until asystole. Asystole was confirmed by using Electrocardiography and auscultation. RESULTS The median (±IQR) duration of asphyxia was 318 (200–560)sec. In 41 piglets both auscultation and ECG HR were assessed. In 11 (27%) cases both auscultation and ECG correctly identified a bradycardic HR (mean (SD) 32(14)/min) at the beginning of chest compression. In 11 (27%) cases both auscultation and ECG correctly identified absent of any HR. However, in 19 (46%) cases auscultation did not detect a HR while ECG did detect a HR. Overall, the Positive Predictive Value was 37%, Negative Predictive Value was 100%, Sensitivity was 100%, and Specificity was 37% for the ECG to display accurate HR during asphyxia in newborn piglets. CONCLUSION Our data illustrates the need for caution in the routine use of ECG monitoring for all neonatal who might need advanced resuscitation in the deliver room.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".