Veno-Venous ECMO: An Alternative Strategy for Acute Respiratory Failure After High-Voltage Electrocution. The Utility of Point-of-Care Tests
Bibliographic record
Abstract
We report an extraordinary case of a 43-year-old man who sustained high-voltage electrocution injury associated with severe pulmonary damage due to current flow through the tissue. For the first time, a veno-venous extracorporeal membrane oxygenation (ECMO) was successfully used to provide respiratory support during severe hypoxemia without any limitation for surgical wound excision and homologous skin transplantation. To prevent over-bleeding due to surgery, daily medications and heparin infusion aggregometry and thromboelastometry were used as new point-of-care tests. After more than 400 hours, the patient returned to conventional ventilation with a significant improvement of gas exchanges, total pulmonary restore and without thromboembolic complications. Based on our experience, maximum clot firmness (MCF) in FIBTEM is usually high. Our finding shows that fibrinogen deficiency is not a leading mechanism for bleeding in burn patients also during ECMO; they need plasma transfusion preferably. About whole blood impedance aggregometry, thrombin receptor activating peptide 6-test (AUC) is strongly correlated to surgical bleeding and platelet consumption. We suggest that a rapid correction of coagulopathy, using ROTEM and MULTIPLATE, helps to minimize allogeneic blood products and to avoid thromboembolic complications during ECMO treatment and surgical burn wound excision. J Med Cases. 2015;6(12):586-591 doi: http://dx.doi.org/10.14740/jmc2380e
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".