The Quality of Preoperative Glycemic Control Predicts Insulin Sensitivity During Major Upper Abdominal Surgery: A Case-Control Study
Bibliographic record
Abstract
Objective: To examine the association of the quality of preoperative glycemic control and insulin sensitivity during major upper abdominal surgery. Background: In cardiac surgery, glycated hemoglobin A1c (HbA1c), an indicator of glycemic control during the preceding 3 months, correlated with intraoperative insulin sensitivity. Furthermore, insulin resistance showed a significant association with adverse clinical outcomes. Methods: This study is a post hoc exploratory analysis of a randomized controlled trial in patients undergoing elective hepatectomy and receiving the hyperinsulinemic-normoglycemic clamp (HNC) as a potential intervention to reduce surgical site infections (ClinicalTrials.gov NCT01528189). Immediately before skin incision, the HNC was initiated by infusing insulin at the rate of 2 mU/kg/min. Dextrose was administered at rates titrated to maintain normoglycemia (4.0–6.0 mmol/L). The average of 3 consecutive dextrose infusion rates during steady state was used as a measure of insulin sensitivity. Primary outcome was the relationship between preoperative HbA1c and insulin sensitivity during surgery. Secondary outcomes were the associations of insulin sensitivity with the patient’s body mass index (BMI) and postoperative morbidity. Results: Thirty-four patients were studied. HbA1c (Y = −0.52X + 4.8, P < 0.001, R 2 = 0.29), BMI (Y = −0.12X + 5.0, P < 0.001, R 2 = 0.43) showed negative correlations with insulin sensitivity. The odds ratio of postoperative complications within 30 days of surgery for every increase in insulin sensitivity by 1 mg/kg/min was 0.22 (95% confidential interval, 0.06–0.59; P = 0.009). Conclusions: We demonstrate significant associations of the quality of preoperative glycemic control and body mass index with insulin sensitivity during hepatectomy. The degree of insulin resistance correlated with postoperative morbidity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".