Cardiac Output Measurement in Ventilated Lambs with a Significant Left-to-Right Shunt Using the Modified Carbon Dioxide Fick Method
Bibliographic record
Abstract
BACKGROUND: It remains a great challenge to measure systemic blood flow in critically ill newborns. In a former study we validated the modified carbon dioxide Fick (mCO(2)F) method for measurement of cardiac output in a newborn lamb model. In this new study we studied the influence of a left-to-right shunt on the accuracy of the mCO(2)F method. OBJECTIVE: To analyze the influence of a left-to-right shunt on the agreement between cardiac output measurement with the mCO(2)F method and ultrasonic transit time pulmonary blood flow in a lamb model. METHODS: The study was approved by the Ethical Committee on Animal Research of the Radboud University Nijmegen and performed in 8 random-bred lambs. A Gore-Tex shunt was placed between the left pulmonary artery and the descending aorta. This aortopulmonary shunt was intermittently opened and closed, while cardiac output was manipulated by creating hemorrhagic hypotension. Cardiac output measurement with the mCO(2)F method (Q(mCO2F)) was compared with pulmonary blood flow obtained by a transit time ultrasonic flow probe positioned around the common pulmonary artery (Q(APC)). RESULTS: Bias, defined as Q(mCO2F) - Q(APC), was calculated for each measurement. With an open shunt there was a significant left-to-right shunt (mean Qp/Qs ratio 2.26; range 1.56-3.69). Mean bias (SD) was -12.3 (50.4) ml x kg(-1) x min(-1) and -12.3 (42.7) ml x kg(-1) x min(-1) for measurements with a closed and open shunt, respectively (no statistical significant difference). CONCLUSIONS: Cardiac output measurement with the mCO(2)F method is reliable and easily applicable in ventilated newborn lambs, also in the presence of a significant left-to-right shunt.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".