Model of normothermic long-term cardiopulmonary bypass in swine weighing more than eighty kilograms.
Bibliographic record
Abstract
PURPOSE: Swine models have been used to study cardiovascular disease, cardiac physiology, and transplantation, and have been associated with problems, such as friability of certain organs, anesthesia difficulties, ventricular fibrillation, and edema. We describe a stable model of extended cardiopulmonary bypass (up to 22 h) in swine weighing > 80 kg to be used as a research model. METHODS: Swine (n = 5, 88 +/- 6 kg) had both femoral arteries cannulated and after open sternotomy, a two-stage venous catheter was placed in the right atrium/caudal vena cava. The circuit was primed with four parts blood and one part 0.9% NaCl. RESULTS: Cardiopulmonary bypass was maintained for 10 to 22 h, with the following parameters measured at beginning/middle/end: heart rate, 108 to 134 beats per minute; hematocrit, 30 to 38%; glucose concentration, 4 to 11 mmol/L; lactate concentration 6 to 7 mmol/L; pH 7.4 to 7.5; pCO2, 35 to 38 mmHg; pO2, 197-228 mmHg; HCO3-, 21 to 25 mmol/L; base excess, -3 to +2; and total urine output, 425 to 1,600 ml. CONCLUSIONS: Factors responsible for the success of this model include a higher oxygen concentration on initiation of cardiopulmonary bypass (567 +/- 54 mmHg), maintenance of appropriate hematocrit, and use of non-citrated blood-crystalloid prime. The results indicate a stable model of normothermic long-term cardiopulmonary bypass in swine that allows researchers a longer opportunity for further exploration of relevant research issues.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".