Effect of Emergency Department Mattress Compressibility on Chest Compression Depth Using a Standardized Cardiopulmonary Resuscitation Board, a Slider Transfer Board, and a Flat Spine Board
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Bibliographic record
Abstract
INTRODUCTION: Cardiopulmonary resuscitation (CPR) performed on a mattress decreases effective chest compression depth. Using a CPR board partially attenuates mattress compressibility. We aimed to determine the effect of a CPR board, a slider transfer board, a CPR board with a slider transfer board, and a flat spine board on chest compression depth with a mannequin placed on an emergency department mattress. METHODS: The study used a cross-over study design. The CPR-certified healthcare providers performed 2 minutes of compressions on a mannequin in five conditions, an emergency department mattress with: (a) no hard surface, (b) a CPR board, (c) a slider transfer board, (d) a CPR board and slider transfer board, and (e) a flat spine board. Compression depths were measured from two sources for each condition: (a) an internal device measuring sternum-to-spine compression and (b) an external device measuring sternum-to-spine compression plus mattress compression. The difference of the two measures (ie, depleted compression depth) was summarized and compared between conditions. RESULTS: A total of 10,203 individual compressions from 10 participants were analyzed. The mean depleted compression depths (percentage depletion) secondary to mattress effect were the following: 23.6 mm (29.7%) on a mattress only, 13.7 mm (19.5%) on a CPR board, 16.9 mm (23.1%) on a slider transfer board, 11.9 mm (17.3%) on a slider transfer board plus backboard, and 10.3 mm (15.4%) on a flat spine board. The differences in percentage depletion across conditions were statistically significant. CONCLUSION: Cardiopulmonary resuscitation providers should use a CPR board and slider transfer board or a flat spine board alone because these conditions are associated with the smallest amount of mattress compressibility.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 it