The effect of rectal temperature on perianesthetic serum concentrations of transdermally administered fentanyl in cats anesthetized with isoflurane
Bibliographic record
Abstract
OBJECTIVES: To determine whether moderate hypothermia during 4 hours of anesthesia with isoflurane substantially affects serum concentrations of transdermally administered fentanyl in the perianesthetic period in cats. ANIMALS: 7 healthy mature cats. PROCEDURE: A fentanyl patch (25 microg/h) was applied to the shaved thorax 24 hours before induction of anesthesia. Anesthesia was induced at time 0. Each cat received 2 treatments in a random order. Treatments were isoflurane anesthesia with normothermia and isoflurane anesthesia with hypothermia. Cats were intubated, connected to a nonrebreathing circuit, and maintained at 1.3X minimum alveolar concentration for 4 hours. Cats in the hypothermia treatment groups were actively cooled to 35 degrees C following the induction of anesthesia. Serum fentanyl analysis was performed at -24, -12, 0, 1, 2, 3, 4, 4.5, 5, 6, 7, 8, 9, 10, 12, and 24 hours. RESULTS: Mean +/- SEM serum fentanyl concentration (SFC) for the hypothermia treatment group (0.598 +/- 0.3048 ng/mL) was significantly lower than the baseline concentration (1.834 +/- 0.6393 ng/mL) at 1 hour. This significant reduction persisted for the duration of anesthesia for the hypothermia treatment group. Serum fentanyl concentrations returned to baseline values within 1 hour of the end of anesthesia, regardless of body temperature. CONCLUSIONS AND CLINICAL RELEVANCE: Hypothermia during inhalant anesthesia induced a significant reduction in SFC obtained with transdermal administration. The impact of this reduction in SFC on the contribution of transdermally administered fentanyl to any reduction in the need for inhalant anesthesia remains to be determined.
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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 | 0.000 | 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".