High-Dose Insulin Therapy Reduces Postoperative Liver Dysfunction and Complications in Liver Resection Patients through Reduced Apoptosis and Altered Inflammation
Bibliographic record
Abstract
CONTEXT: An exaggerated inflammatory response in patients undergoing major liver resection coupled with poor nutrition diminishes liver regenerative capacity and increases the risk of postoperative complications. OBJECTIVES: Our objective was to evaluate the biological context leading to better clinical outcomes in patients undergoing liver resection coupled with hyperinsulinemic-normoglycemic clamp vs. standard care (insulin sliding care). DESIGN AND SETTING: This study was a fundamental research analysis of a patient subset from a randomized-controlled study at the McGill University Health Center. PATIENTS AND INTERVENTION: Thirty consenting patients participating in a randomized clinical trial for liver resection received either hyperinsulinemic-normoglycemic clamp technique with 24-h preoperative carbohydrate load (intervention) or standard glucose control through insulin sliding scale treatment (control). MAIN OUTCOME MEASURES: Liver biopsies and plasma samples were taken at various time points before and after surgery. Primary measures included mRNA quantitation for genes related to insulin signaling, inflammation, and proliferation; proinflammatory cytokines at various time points; and liver function markers. These measurements were associated with clinical outcomes. RESULTS: The hyperinsulinemic-normoglycemic clamp technique reduced postoperative liver dysfunction, infections, and complications. Markers of energy stores indicated higher substrate availability. Cytokine expression pattern was altered (TNF-α, IL-8, monocyte chemoattractant protein-1, IL-6, IL-10, and C-reactive protein). Apoptosis was markedly reduced, whereas the complement system was unaltered. CONCLUSION: The hyperinsulinemic-normoglycemic clamp technique reduced postoperative negative outcomes by suppressing apoptosis. This phenomenon appears to be linked with higher substrate availability and altered cytokine secretion profile and may provide a long-term benefit of this therapy on liver resection patients.
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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 | 0.000 |
| 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".