Spatial pattern of ventilation-perfusion mismatch following acute pulmonary thromboembolism in pigs
Bibliographic record
Abstract
We studied the spatial distribution of the abnormal ventilation-perfusion (Va/Q) units in a porcine model of acute pulmonary thromboembolism (APTE), using the fluorescent microsphere (FMS) technique. Four piglets ( approximately 22 kg) were anesthetized and ventilated with room air in the prone position. Each received approximately 20 g of preformed blood clots at time t = 0 min via a large-bore central venous catheter, until the mean pulmonary arterial pressure reached 2.5 times baseline. The distributions of regional Va and blood flow (Q) at five time points (t = -30, -5, 30, 60, 120 min) were mapped by FMS of 10 distinct colors, i.e., aerosolization of 1-mum FMS for labeling Va and intravenous injection of 15-mum FMS for labeling Q. Our results showed that, at t = 30 min following APTE, mean Va/Q (Va/Q = 2.48 +/- 1.12) and Va/Q heterogeneity (log SD Va/Q = 1.76 +/- 0.23) were significantly increased. There were also significant increases in physiological dead space (11.2 +/- 12.7% at 60 min), but the shunt fraction (Va/Q = 0) remained minimal. Cluster analyses showed that the low Va/Q units were mainly seen in the least embolized regions, whereas the high Va/Q units and dead space were found in the peripheral subpleural regions distal to the clots. At 60 and 120 min, there were modest recoveries in the hemodynamics and gas exchange toward baseline. Redistribution pattern was mostly seen in regional Q, whereas Va remained relatively unchanged. We concluded that the hypoxemia seen after APTE could be explained by the mechanical diversion of Q to the less embolized regions because of the vascular obstruction by clots elsewhere. These low Va/Q units created by high flow, rather than low Va, accounted for most of the resultant hypoxemia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".