Comparing sternal versus left-sided chest compressions for thoracoabdominal injuries and compression biomechanics: A clinical-grade cadaver study
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Bibliographic record
Abstract
Background: The lower half of the sternum is currently recommended as the area of compression (AOC) in CPR. Compressions over this area often result in outflow obstruction and inadequate compression of the left ventricle. Alternative left-sided chest compressions that target the left ventricle may improve cardiac arrest outcomes. However, little is known about the risks of thoracoabdominal injuries or the biomechanics of left-sided compressions. Methods: The objective of this study was to examine the thoracoabdominal injury patterns and compression biomechanics during standard (control) and left-sided (experimental; off sternum, patient left, 6th rib) chest compressions. N = 6 clinical-grade cadavers (control n = 2; experimental n = 4) underwent six 2-minute rounds of chest compressions with intermittent fluoroscopy. Chest compression depth, recoil, and rate were standardized using compression feedback devices. Post-CPR dissection was used to examine for thoracoabdominal injuries. Results: Standard compressions resulted in rib fractures (n = 1 [50%]). Left-sided compressions resulted in rib fractures (n = 4 [100%]), flail chest segments (n = 3 [75%]), and internal thoracic artery injury (n = 1 [25%]). No abdominal organ injuries were identified in either group (N = 6 [0%]). During compression, each condition yielded a different pattern of chest wall deformity (standard - regular trapezoid [midline, comparable left-right sides, flat top, and bottom]; left-sided - irregular trapezium [left-sided, unequal sides, leftward sloped top]). Conclusion: Experimental left-sided compressions consistently produced rib fractures and flail chest segments. Findings should be interpreted with caution due to the limited sample size. Further studies investigating the biomechanics and outcomes of left sided chest compressions are warranted.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it