CPR coaching during cardiac arrest improves adherence to PALS guidelines: a prospective, simulation-based trial
Bibliographic record
Abstract
AIM: Recent studies have shown that the integration of a trained cardiopulmonary resuscitation (CPR) Coach during resuscitation enhances the quality of CPR during simulated paediatric cardiac arrest. The objective of our study was to evaluate the effect of a CPR Coach on adherence to Paediatric Advanced Life Support (PALS) guidelines during simulated paediatric cardiac arrest. METHODS: This was a secondary analysis of data collected from a multicentre randomized controlled trial assessing the quality of CPR in teams with and without a CPR Coach. Forty paediatric resuscitation teams were equally randomized into 2 groups (with or without a CPR Coach). The primary outcome was adherence to PALS guidelines during a simulated paediatric cardiac arrest case as measured by the Clinical Performance Tool (CPT). Video recordings were assigned to 2 pairs of expert raters. Raters were trained to independently score performances using the tool. RESULTS: The reliability of the rating was adequate for the Clinical Performance Tool with an intraclass coefficients of 0.67 (95%CI: 0.22 to 0.84). Performance scores of the different teams varied between 51 and 84 points on the Clinical Performance Tool with a mean score of 70. Teams with a CPR Coach demonstrated better adherence to PALS guidelines (i.e. CPT score 73 points) compared to teams without a CPR Coach (68 points, difference 5 points; 95%CI: 1.0-9.3, p = 0.016). CONCLUSION: In addition to improving CPR quality, the presence of a CPR Coach improves adherence to PALS guidelines during simulated paediatric cardiac arrests when compared with teams without a CPR Coach.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".