Effectiveness of combinations of active compression-decompression cardiopulmonary resuscitation, impedance threshold devices and head-up cardiopulmonary resuscitation in adult out-of-hospital cardiac arrest: A systematic review
Bibliographic record
Abstract
This review summarises the current evidence base for combinations of neuroprotective CPR adjuncts (active compression-decompression chest compressions, impedance threshold devices, and head-up positioning) during out-of-hospital cardiac arrest. A systematic search (PROSPERO registration CRD42023432302) was performed in English on MEDLINE, EMBASE, and the Cochrane Library in August 2023, and repeated in February 2024. All randomised and observational studies (not abstracts) reporting on any combination of the aforementioned CPR adjuncts were included. Papers were screened independently by two researchers, with a third reviewer acting as tiebreaker. Out-of-hospital, non-traumatic, cardiac arrests in patients >18 years were eligible for inclusion. Risk of bias was assessed using the Risk of Bias 2 tool and the Newcastle-Ottawa scale. Eight of 1172 unique articles identified in the initial searches were included, with five randomised controlled trials and three observational studies. No randomised trial investigated a bundle of all three interventions. All randomised controlled trials were at intermediate or high risk of bias. Neurologically favourable survival was greater in patients treated with an impedance threshold device and active compression-decompression CPR when compared to standard CPR (8.9% vs 5.8%, p = 0.019) in the largest existing randomised trial. Conflicting results were found in observational studies comparing the complete neuroprotective bundle to standard CPR. This review was limited by small study numbers and overlapping samples, which precluded a meta-analysis. Limited data suggests that combinations of adjuncts to improve cerebral perfusion during CPR may improve survival with favourable neurological outcome. A randomised controlled trial is required to establish whether combining all three together results in improved outcomes.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".