Extracorporeal cardiopulmonary resuscitation as a standard of care in the future: a literature review
Bibliographic record
Abstract
Background: The use of extracorporeal cardiopulmonary resuscitation (ECPR) is limited generally to situations where traditional CPR failed to restore a patient's heart rhythm. Although ECPR is not regarded as the standard of care for cardiac arrest patients, it might be a more effective treatment for some forms of cardiac arrest. This literature review explores the efficacy of ECPR as a potential standard of care for cardiac arrest in the future. Methods: English language publications fulfilling eligibility criteria from 2010 to 2023 were found through a literature search using four electronic databases (PubMed, Google Scholar, Cochrane, and IEEE Explore). Articles were included in this literature review for fulfilling following criteria: empirical primary studies evaluating ECPR in human subjects with either IHCA or OHCA; articles published in English between 2010 and 2023; articles exploring ECPR in cardiac arrest across all ages of patients. Results : 12 studies out of 1,092 search results met the inclusion criteria for data extraction and synthesis. Data extracted included the efficacy of ECPR in both IHCA and OHCA patients based on the PICO framework. The quality of study done by NOS (Newcastle-Ottawa Quality Assessment Scale for Cohort Studies) resulted in three studies with moderate quality while nine were of high quality. Conclusions: ECPR was associated with neurologically intact survival with favorable neurological outcomes compared to a standard CRP for cardiac arrest patients. This study also demonstrates that, at the moment, ECPR is the most successful in centers with a well-trained multidisciplinary ECMO team of experts. On the other hand, cardiac arrest patients in semi-rural areas and underdeveloped locations are likely to benefit less from ECPR interventions due to the lack of necessary ECPR expertise and infrastructure. Those individuals eligible for ECPR benefit from better neurological outcomes and associated higher survival rates.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".