Systemic and renal macro- and microcirculatory responses to arginine vasopressin in endotoxic rabbits*
Bibliographic record
Abstract
OBJECTIVE: Arginine vasopressin is being used increasingly to treat vasodilatory hypotension, although little is known of its effects on regional perfusion. Arginine vasopressin hemodynamic effects in physiology are mainly mediated through the V1a receptor on blood vessels. To investigate this further, we studied the effect of arginine vasopressin on systemic and renal blood flow in anesthetized, ventilated rabbits given either intravenous saline or endotoxin, and the impact of blocking V1a receptors. DESIGN: Prospective, randomized, controlled study. SETTING: Animal research laboratory. SUBJECTS: Male White New Zealand rabbits. INTERVENTIONS: Measurement was made of mean arterial blood pressure, aortic and renal blood flow velocities (pulsed Doppler), and renal cortical and medullary flow (laser Doppler). MEASUREMENTS AND MAIN RESULTS: In a first series of animals, incremental intravenous boluses of arginine vasopressin ranging from 1 to 1000 ng were administered 90 mins postendotoxin or saline. In control rabbits (n = 9), increasing doses of arginine vasopressin elevated mean arterial blood pressure but reduced both aortic and renal blood flow velocity and renal cortical flow (p <.05). In endotoxic animals (n = 6), arginine vasopressin produced a similar increase in mean arterial blood pressure although aortic flow was maintained while renal blood flow velocity increased, mostly in its diastolic component (p <.05). Pretreatment with the V1a receptor antagonist in a second series of animals blunted all the effects observed in both control (n = 5) and endotoxic (n = 6) animals, suggesting that arginine vasopressin acted mainly through V1a subtype in this early phase of sepsis. CONCLUSIONS: Preservation of renal blood flow with arginine vasopressin during endotoxemia, in particular to the cortex, suggests it could be a promising agent for hemodynamic support during septic shock.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".