Development and evaluation of a mechanical chest compression device for standardized rodent cardiopulmonary resuscitation
Bibliographic record
Abstract
Abstract Small animal models are indispensable in cardiopulmonary resuscitation (CPR) research. High-quality CPR, characterized by consistent chest compression rate, depth, and positioning is crucial for survival. However, achieving standardization in manual high-frequency chest compressions in small animal models remains technically challenging. This study evaluated the reproducibility of manual chest compressions and introduced a novel mechanical chest compression device (MCD) designed to improve consistency in rodent experiments. In an in vitro setup, manual compressions were performed by ten participants at target rates ranging from 100 to 260 bpm, guided by a metronome. Compressions performed on a fluid-filled polymer reservoir were analyzed for the compression rate, variability, and time within a ± 10% target range. A color indicator was used to assess the variability of the compression point. A small animal MCD was designed and tested under the same conditions. In vivo, 5 Sprague-Dawley rats underwent 5 min of electrically induced normothermic cardiac arrest followed by 8 min of external chest compressions using the MCD. Obtained data was compared to the in vitro results. A total of 21,650 manual and 20,098 mechanical compressions were analyzed. At 200 bpm, chest compressions using the MCD were significantly more precise (201 ± 1.2 bpm) than manual compressions (218 ± 21 bpm, p < 0.001) with a significant reduced compression point variability (1.7 ± 0.1 cm 2 vs. 10.8 ± 3.1 cm 2 , p < 0.001). Manual compressions maintained target rate in 58.8% of time compared to 100% for the MCD. In vivo testing confirmed these findings with chest compressions remaining within the target range 100% of the time and showing minimal rate variability (1.8 ± 1.7 bpm). These results highlight the limitations of manual chest compressions and demonstrate the potential of the MCD to enhance standardization and reproducibility in rodent CPR research.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 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 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".