Extracorporeal cardiopulmonary resuscitation for cardiac arrest: An updated systematic review
Bibliographic record
Abstract
OBJECTIVES: To provide an updated systematic review on the use of extracorporeal cardiopulmonary resuscitation (ECPR) compared with manual or mechanical cardiopulmonary resuscitation during cardiac arrest. METHODS: This was an update of a systematic review published in 2018. OVID Medline, Embase, and the Cochrane Central Register of Controlled Trials were searched for randomized trials and observational studies between January 1, 2018, and June 21, 2022. The population included adults and children with out-of-hospital or in-hospital cardiac arrest. Two investigators reviewed studies for relevance, extracted data, and assessed bias. The certainty of evidence was evaluated using GRADE. RESULTS: The search identified 3 trials, 27 observational studies, and 6 cost-effectiveness studies. All trials included adults with out-of-hospital cardiac arrest and were terminated before enrolling the intended number of subjects. One trial found a benefit of ECPR in survival and favorable neurological status, whereas two trials found no statistically significant differences in outcomes. There were 23 observational studies in adults with out-of-hospital cardiac arrest or in combination with in-hospital cardiac arrest, and 4 observational studies in children with in-hospital cardiac arrest. Results of individual studies were inconsistent, although many studies favored ECPR. The risk of bias was intermediate for trials and critical for observational studies. The certainty of evidence was very low to low. Study heterogeneity precluded meta-analyses. The cost-effectiveness varied depending on the setting and the analysis assumptions. CONCLUSIONS: Recent randomized trials suggest potential benefit of ECPR, but the certainty of evidence remains low. It is unclear which patients might benefit from ECPR.
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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 | 0.012 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".