Abstract 18435: ETCO2 Alone is Inadequate to Verify CPR Quality
Bibliographic record
Abstract
Background: Previous studies have described modest correlation between end-tidal CO 2 (ETCO 2 ) and CPR quality during resuscitation of cardiac arrest patients, but it is unclear whether ETCO 2 alone can indicate CPR quality. The present study investigated whether ETCO 2 adequately identifies the quality of CPR provided during out-of-hospital cardiac resuscitation. Methods: ETCO 2 was monitored with side-stream CO 2 (Philips/Respironics) and CPR quality measured with an accelerometer-based system (E Series, ZOLL Medical) during the treatment of consecutive adult OHCA patients with presumed cardiac etiology by 2 EMS agencies in the Arizona SHARE QI Program between 10/08-06/13. Minute-by-minute ETCO 2 and CPR quality were extracted. ETCO 2 values were log transformation to achieve approximate normality. Linear mixed effect models were fitted to use (transformed) ETCO 2 level to predict four CPR variables: chest compression (CC) depth, CC rate, CC release velocity (CCRV), and ventilation rate (VR). A random intercept for each case was included and a spatial power covariance structure assumed for measurements over time. Results: 230 subjects (median age 69 yrs, 69% male) with 1581 minutes of data were studied. Transformed ETCO 2 was significant for CC depth (p< 0.0001), CCRV (p=0.003) and VR (p<0.0001), but only explained 3.7%, 2.7%, and 10.0% of the total variance for these variables, respectively. Transformed ETCO 2 was not a significant predictor for CC rate (p=0.89). The Figure illustrates the overlap in CC depth over quartiles of ETCO 2 , demonstrating that any specific ETCO 2 level could be found over a wide range of CC depths. Conclusion: In this secondary analysis, ETCO 2 was not an independent indicator of CC rate but was a weak predictor for CC depth, CCRV and VR. These findings suggest that ETCO 2 may be not be an adequate substitute for CPR quality monitoring. Future studies should investigate how ETCO 2 and CPR quality monitoring can be used in conjunction to optimize CPR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".