Measurement of systemic oxygen consumption in patients during extracorporeal membrane oxygenation — description of a new method and the first clinical observations
Bibliographic record
Abstract
BACKGROUND: Extracorporeal membrane oxygenation (ECMO) provides temporary life-saving support for patients with severe cardiac failure, but is associated with significant morbidity and mortality. While ECMO enables oxygen delivery (DO2), little is known about oxygen consumption (VO2), largely due to technical difficulties. We aimed to introduce the adaptation of respiratory mass spectrometry to measure VO2 in patients during ECMO and to use this unique model to determine the pathological dependency of VO2 on DO2 in humans. METHODS AND PATIENTS: Respiratory mass spectrometry remains the 'state-of-the-art' method, allowing the highly sensitive and rapid measurement of VO2 in critically ill patients. The principle and design of the respiratory mass spectrometer are described, together with the setting up of this machine with the ECMO oxygenator and the native lungs of the patients. In two patients with severe dilated cardiomyopathy and little cardiac contraction, the decrease in pump flow and, hence, DO2 by 20% was associated with a decrease in VO2 by 5% and 8%, respectively, whereas the increase in pump flow was not associated with any significant change in VO2. CONCLUSIONS: The direct measurement of VO2 by respiratory mass spectrometry in ECMO patients provides a unique technique for clinical research on the metabolism and VO2-DO2 relationship in this special group of critically ill patients. Our pilot study is the first to demonstrate a pathological dependency of VO2 on DO2 in humans. Further studies are warranted with this technique to examine the changes and the factors affecting systemic oxygen transport in patients during ECMO.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".