Epidural blockade suppresses lipolysis during major abdominal surgery☆
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The purpose of the study was to investigate the effect of thoracic epidural administration of local anesthetic, i.e., epidural block on perioperative lipolysis. METHODS: Fourteen patients undergoing elective colorectal surgery were randomly assigned to receive either general anesthesia combined with epidural block (EDA, n = 7) or general anesthesia alone (control, n = 7). The rates of glycerol appearance (R(a) glycerol), i.e., lipolysis, were assessed by the stable isotope tracer [1,1,2,3,3-(2)H(5)]glycerol before, during, and 2 hours after the operation. Plasma concentrations of metabolic substrates (glycerol, free fatty acids [FFA], lactate) and hormones (insulin, glucagon, cortisol) were also determined. RESULTS: In the EDA group, R(a) glycerol decreased to lower intra- and postoperative values than in the control group (P <.05). Perioperative plasma concentrations of glycerol, FFA, lactate, and insulin remained unaltered with both anesthetic techniques. Intraoperative plasma glucagon and cortisol concentrations were lower in the EDA group than in the control group (P <.05). CONCLUSIONS: Epidural block suppresses lipolysis during and 2 hours after major abdominal surgery without affecting plasma glycerol or FFA concentrations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".