Correlation between end-tidal carbon dioxide and the degree of compression of heart cavities measured by transthoracic echocardiography during cardiopulmonary resuscitation for out-of-hospital cardiac arrest
Bibliographic record
Abstract
Abstract Background The concept of personalized cardiopulmonary resuscitation (CPR) requires a parameter that reflects its hemodynamic efficiency. While intra-arrest ultrasound is increasingly implemented into the advanced life support, we realized a pre-hospital clinical study to evaluate whether the degree of compression of the right ventricle (RV) and left ventricle (LV) induced by chest compressions during CPR for out-of-hospital cardiac arrest (OHCA) and measured by transthoracic echocardiography correlates with the levels of end-tidal carbon dioxide (EtCO 2 ) measured at the time of echocardiographic investigation. Methods Thirty consecutive patients resuscitated for OHCA were included in the study. Transthoracic echocardiography was performed from a subcostal view during ongoing chest compressions in all of them. This was repeated three times during CPR in each patient, and EtCO 2 levels were registered. From each investigation, a video loop was recorded. Afterwards, maximal and minimal diameters of LV and RV were obtained from the recorded loops and the compression index of LV (LVCI) and RV (RVCI) was calculated as (maximal − minimal/maximal diameter) × 100. Maximal compression index (CImax) defined as the value of LVCI or RVCI, whichever was greater was also assessed. Correlations between EtCO 2 and LVCI, RVCI, and CImax were expressed as Spearman’s correlation coefficient ( r ). Results Evaluable echocardiographic records were found in 18 patients, and a total of 52 measurements of all parameters were obtained. Chest compressions induced significant compressions of all observed cardiac cavities (LVCI = 20.6 ± 13.8%, RVCI = 34.5 ± 21.6%, CImax = 37.4 ± 20.2%). We identified positive correlation of EtCO 2 with LVCI ( r = 0.672, p < 0.001) and RVCI ( r = 0.778, p < 0.001). The strongest correlation was between EtCO2 and CImax ( r = 0.859, p < 0.001). We identified that a CImax cut-off level of 17.35% predicted to reach an EtCO 2 level > 20 mmHg with 100% sensitivity and specificity. Conclusions Evaluable echocardiographic records were reached in most of the patients. EtCO 2 positively correlated with all parameters under consideration, while the strongest correlation was found between CImax and EtCO 2 . Therefore, CImax is a candidate parameter for the guidance of hemodynamic-directed CPR. Trial registration ClinicalTrial.gov, NCT03852225 . Registered 21 February 2019 - Retrospectively registered.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".