Doppler Ultrasound for Heart Rate Assessment in a Porcine Model of Neonatal Asphyxia
Bibliographic record
Abstract
Objectives: Approximately 10% of newborn infants require resuscitation at birth. Accurate heart rate (HR) assessment guides resuscitation interventions, thereby reducing morbidities and mortality. While existing HR assessment methods have several limitations, the Doppler ultrasound (Doppler-US) might be a promising alternative. We aimed to evaluate accuracy and optimal use of Doppler-US for HR assessments during neonatal asphyxia in a pre-clinical model. Design: HR assessments were performed in 16 term newborn piglets that were anesthetized, intubated and instrumented. Study I evaluated optimal transducer position, Study II compared aortic (AV) and pulmonary (PV) examination modes, and Study III examined accuracy during asphyxia, for HR assessment. Setting: Experimental setting. Subjects: Asphyxia-induced piglets. Interventions: Study I: Doppler-US (USCOM® 1A) HR was assessed on upper (A), middle (B), and lower (C) third of the sternum; study II: Doppler-US HR was assessed using AV and PV examination modes; study III: HR was assessed during asphyxia. Comparisons were made between Doppler-US and the clinical gold standard for HR assessments, electrocardiography (ECG). Measurements and Main Results: Study I: Mean(SD) Doppler-US HR at position A, B, and C showed no difference when compared to ECG HR. Study II: The mean(SD) Doppler-US HR using AV and PV modes also showed no difference when compared to ECG HR. Study III: Bland-Altman analysis revealed a mean difference(95% limits of agreement) between Doppler-US and ECG HR of 1.5(-16-19)bpm. Additionally, motion artefacts produced false peaks and peak size was seen to decrease as bradycardia progressed. Conclusions: HR assessment using Doppler-US during asphyxia is accurate but has limitations and must be further evaluated prior to clinical use. Doppler-US can be positioned along the sternum and use either AV or PV mode for accurate assessments in a piglet model of neonatal asphyxia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".