A Local Sensitivity Analysis of the Trial of Continuous or Interrupted Chest Compressions during Cardiopulmonary Resuscitation: Is a Local Protocol Change Required?
Bibliographic record
Abstract
Objective The "Trial of Continuous (CCC) or Interrupted Chest Compressions (ICC) during Cardiopulmonary Resuscitation (CPR)" compared two CPR strategies for out-of-hospital cardiac arrest (OHCA). Although results were neutral, there was suggestion of benefit for ICC. However, nearly 50% of study patients had a protocol violation; regional variations may have played a role in protocol adherence and outcomes. We analyzed our British Colombia (BC) cohort to decide whether a protocol change from CCC to ICC was justified. Methods This was a post-hoc analysis of BC-enrolled study patients. The primary between-group comparison was favorable neurological outcome (modified Rankin scale ≤ 3) using intention-to-treat. Secondary analyses compared those treated per-protocol (adjusted) and the top compliant clusters (unadjusted). We classified protocol violations using a structured algorithm. We used logistic regression and computed the difference in probabilities using the marginal standardization method with bootstrapping to calculate confidence intervals. Results There were 3769 patients included, with a median age of 69 years (IQR: 56-80). There were protocol violations in 3.2% of those in the CCC group and 27% of those in the ICC group. In patients randomized to CCC or ICC, 11.2% and 10.8% (risk difference 0.42%; 95% CI -1.58, 2.41) had favorable neurological outcomes, respectively. In the per-protocol and top compliant clusters comparisons, risk differences were 0.25% (95% CI -1.70, 2.25) and 2.95% (95% CI -0.68, 6.58). Conclusion Our comparisons suggest that CCC may be the preferred strategy in our region and is likely not resulting in worse outcomes. Based on the original study and our local analysis, we found no compelling reasons to change our local strategy from CCC to ICC.
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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 | 0.338 | 0.412 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.026 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".