Successful Extracorporeal Cardiopulmonary Resuscitation for Pediatric Cardiac Arrest with a Long Low-Flow Time
Bibliographic record
Abstract
As the cardiopulmonary resuscitation (CPR) time increases, patient prognosis and neurological outcomes are expected to worsen. Although the effectiveness of introducing ECMO in CPR has been discussed, there are currently no definitive criteria for the use of extracorporeal CPR with a lack of evidence. Here, we report a case of a 12-year-old female with severe myocarditis who survived out-of-hospital cardiac arrest with ventricular tachycardia and ventricular fibrillation due to the introduction of extracorporeal CPR after long-duration conventional CPR (total conventional CPR time: 73 minutes). Inter-hospital transport under veno-arterial extracorporeal membrane oxygenation (VA-ECMO) support was performed after extracorporeal CPR by the previous hospital. On admission to the pediatric intensive care unit, the patient's pupils were severely dilated with sluggish light reflexes. The condition of the pupils immediately improved after increasing the flow of VA-ECMO from 1.7 to 2.4 L/min/m2. The patient received medical support, including systemic steroids, immunoglobin, and 48 hours of therapy for mild hypothermia, and she demonstrated recovery of cardiac function in the first 6 days after admission. The patient was discharged from the hospital with a normal functional status. Extracorporeal CPR has to be considered even for long-duration CPR, and in which case it is important to make careful assessments of the presence of factors (e.g., initial rhythm, the quality of conventional CPR, the time to conventional CPR initiation) before starting extracorporeal CPR. In neurological evaluation, ECMO flow should be sufficient to ensure cardiac output. The present case also suggests that good-quality CPR with ECMO may compensate for its CPR length.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".