Massive aspiration syndrome: a possible indication for “emergent” veno-venous extracorporeal membrane oxygenation?: a case report
Bibliographic record
Abstract
BACKGROUND: Veno-venous extracorporeal membrane oxygenation (VV-ECMO) is usually performed in cases of severe respiratory failure in which conventional and advanced mechanical ventilation strategies are ineffective in achieving true lung-protective ventilation, thus triggering ventilatory-induced lung injury. If circulatory failure coexists, veno-arterial ECMO (VA-ECMO) may be preferred over VV-ECMO because of its potential for circulatory support. In VA-ECMO, the respiratory contribution is less effective and the complication rate is higher than in the VV configuration. CASE PRESENTATION: The authors present a case in which VV-ECMO was performed in an emergency setting to treat a 68-year-old White male patient who experienced acute respiratory failure after massive aspiration. Despite intubation and intensive care unit admission, multiple organ failure occurred suddenly, thus prompting referral to a level-1 trauma center with an ECMO facility. The patient's condition slowly improved with VV-ECMO support along with standard treatment for hemodynamic impairment. VV-ECMO was discontinued on day 8. The patient was extubated on day 14 and discharged home fully recovered 34 days after the event. CONCLUSIONS: Attention was focused on the decision to initiate VV-ECMO support even in the presence of severe hemodynamic derangement, although VA-ECMO could have provided better hemodynamic support but less effective respiratory support.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".