Randomized clinical trial of the impact of insulin therapy on liver function in patients undergoing major liver resection
Bibliographic record
Abstract
BACKGROUND: Postoperative liver dysfunction is the major source of morbidity and mortality in patients undergoing partial hepatectomy. This study tested the benefits of a metabolic support protocol based on insulin infusion, for reducing liver dysfunction following hepatic resection. METHODS: Consecutive consenting patients scheduled for liver resection were randomized to receive preoperative dextrose infusion followed by insulin therapy using the hyperinsulinaemic normoglycaemic clamp protocol (n = 29) or standard therapy (control group, n = 27). Patients in the insulin therapy group followed a strict dietary regimen for 24 h before surgery. Intravenous dextrose was started at 2 mg per kg per min the night before and continued until surgery. Hyperinsulinaemic therapy for a total of 24 h was initiated at 2 munits per kg per min at induction of anaesthesia, and continued at 1 munit per kg per min after surgery. Normoglycaemia was maintained (3.5-6.0 mmol/l). Control subjects received no additional dietary supplement and a conventional insulin sliding scale during fasting. All patients were tested serially to evaluate liver function using the Schindl score. Liver tissue samples were collected at two time points during surgery to measure glycogen levels. RESULTS: Demographics were similar in the two groups. More liver dysfunction occurred in the control cohort (liver dysfunction score range 0-8 versus 0-4 with insulin therapy; P = 0.031). Median (interquartile range) liver glycogen content was 278 (153-312) and 431 (334-459) µmol/g respectively (P = 0.011). The number of complications rose with increasing severity of postoperative liver dysfunction (P = 0.032) CONCLUSION: The glucose-insulin protocol reduced postoperative liver dysfunction and improved liver glycogen content. REGISTRATION NUMBER: NCT00774098 (http://www.clinicaltrials.gov).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".