How <scp>ABBA</scp> may help improve neonatal resuscitation training: Auditory prompts to enable coordination of manual inflations and chest compressions
Bibliographic record
Abstract
AIM: Resuscitation guidelines recommend 90 chest compressions (CCs) and 30 inflations (INFs) per minute for neonatal cardiopulmonary resuscitation (nCPR). We hypothesised that auditory prompts would help coordinate these actions. Our aim was to investigate the effect of musical prompts during nCPR training on adherence to recommended CC and INF rates and on the quality of delivered INFs. METHODS: A simulation study was conducted employing 30 experienced neonatal staff, a respiratory function monitor and a neonatal manikin. The effects of five different auditory prompts on adherence to recommended rates of CC and INF were tested against baseline (no music). The five auditory prompts (popular musical tunes) were investigated in random order. Quality of INFs was assessed by comparing the peak inflation pressures (PIP), positive end-expiratory pressures (PEEP), percentage mask leak and tidal volumes (VT). RESULTS: Mean baseline rates at which CCs and INFs were delivered were 80 (SD 6) per minute and 28 (SD 2) per minute, respectively. Listening to auditory prompts had varying effects on CC and INF delivery rates. For CCs, a significant difference to baseline was found only when participants listened to ABBA's 'SOS', with 86 (SD 7) per minute (P = 0.04). For INFs, we found a statistically significant improvement to baseline rate only for 'SOS', with 29 (SD 2) per minute (P = 0.04), and there was no significant difference in INF quality among the auditory prompts. CONCLUSIONS: Musical prompts can help with adherence to recommended CC and INF rates but do not improve the quality of INFs during nCPR training. The lasting effect of auditory prompts as musical mnemonics on nCPR performance in vivo needs to be established.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".