Use of plethysmographic variability index and perfusion index to evaluate changes in arterial blood pressure in anesthetized tigers (Panthera tigris)
Bibliographic record
Abstract
OBJECTIVE To investigate use of the plethysmographic variability index (PVI) and perfusion index (PI) for evaluating changes in arterial blood pressure in anesthetized tigers (Panthera tigris). ANIMALS 8 adult tigers. PROCEDURES Each tiger was anesthetized once with a combination of ketamine, midazolam, medetomidine, and isoflurane. Anesthetic monitoring included assessment of PI, PVI, direct blood pressure measurements, anesthetic gas concentrations, esophageal temperature, and results of capnography and ECG. Mean arterial blood pressure (MAP) was maintained for at least 20 minutes at each of the following blood pressure conditions: hypotensive (MAP = 50 ± 5 mm Hg), normotensive (MAP = 70 ± 5 mm Hg), and hypertensive (MAP = 90 ± 5 mm Hg). Arterial blood gas analysis was performed at the beginning of anesthesia and at each blood pressure condition. RESULTS Mean ± SD PI values were 1.82 ± 2.38%, 1.17 ± 0.77%, and 1.71 ± 1.51% and mean PVI values were 16.00 ± 5.07%, 10.44 ± 3.55%, and 8.17 ± 3.49% for hypotensive, normotensive, and hypertensive conditions, respectively. The PI values did not differ significantly among blood pressure conditions. The PVI value for the hypotensive condition differed significantly from values for the normotensive and hypertensive conditions. The PVI values were significantly correlated with MAP (r = -0.657). The OR of hypotension to nonhypotension for PVI values ≥ 18% was 43.6. CONCLUSIONS AND CLINICAL RELEVANCE PVI was a clinically applicable variable determined by use of noninvasive methods in anesthetized tigers. Values of PVI ≥ 18% may indicate hypotension.
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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 | 0.001 |
| 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 | 0.000 |
| 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".