Relationship between blood remifentanil concentration and stress hormone levels during pneumoperitoneum in patients undergoing laparoscopic cholecystectomy.
Bibliographic record
Abstract
OBJECTIVE: The effect of remifentanil on stress response to surgery is unclear. However, there are not clinical studies investigating the relationship between blood remifentanil concentrations and stress hormones. Therefore, the aim of the present study was to assess the association between blood remifentanil concentrations measured after pneumoperitoneum and cortisol (CORT) or prolactin (PRL) ratio (intraoperative/preoperative value), in patients undergoing laparoscopic cholecystectomy. PATIENTS AND METHODS: Patients did not receive any pre-anesthetic medication. Anesthesia induction was standardized. Anesthesia maintenance was performed with inhaled sevoflurane at age-adjusted 1.0 minimum alveolar concentration and intravenous remifentanil at infusion rate ranging from 0.1 to 0.4 mcg/kg/min. Blood samples were withdrawn before anesthesia induction and 5 min after achieving a pneumoperitoneum pressure of 12 mmHg. Correlation analyses were performed to evaluate the relationship between measured blood remifentanil concentrations, CORT or PRL ratio (intraoperative/preoperative value) and remifentanil dose delivered by the pump. RESULTS: A significant inverse correlation was found between CORT ratio and measured blood remifentanil concentration (p=0.03) or planned remifentanil dose (p=0.04). No correlations were found between blood remifentanil concentration and PRL ratio (p=0.83). CONCLUSIONS: Our data suggest that the CORT response to surgical stress is more efficiently counteracted by increased blood remifentanil concentration.
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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 | 0.001 |
| 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".