Type 2 Diabetes Mellitus and the Catabolic Response to Surgery
Bibliographic record
Abstract
BACKGROUND: The authors tested the hypothesis that the catabolic responses to colorectal surgery are amplified in the presence of type 2 diabetes mellitus. METHODS: Seven nondiabetic and seven diabetic patients underwent a 6-h stable isotope infusion study (3 h fasted, 3-h glucose infusion at 4 mg . kg . min) on the second postoperative day. Leucine rate of appearance (Ra), leucine oxidation, nonoxidative leucine disposal, and glucose Ra were assessed by L-[1-C]leucine and [6,6-H2]glucose. Circulating concentrations of glucose, lactate, insulin, glucagon, and cortisol also were determined. RESULTS: Diabetic patients had a higher leucine oxidation than nondiabetic patients (P = 0.0003), whereas leucine Ra and nonoxidative leucine disposal were not different. Administration of glucose did not affect leucine kinetics regardless of whether patients were diabetic. In diabetic patients, glucose Ra was greater than in the nondiabetic group (P = 0.0032). Glucose infusion suppressed the endogenous glucose Ra to a lesser extent in diabetic than in nondiabetic patients (P = 0.0048). Plasma glucose concentrations were higher in diabetic than in nondiabetic patients (P = 0.0203), both in the postabsorptive and the fed state. Circulating concentrations of glucagon were higher (P = 0.0065) and concentrations of insulin were lower (P = 0.0146) in the presence of diabetes, resulting in a lower insulin/glucagon ratio (P = 0.0002). In diabetic patients, the insulin/glucagon ratio increased during glucose infusion to a lesser extent than in the nondiabetic group (P = 0.0014). CONCLUSION: Protein catabolism after colorectal surgery is increased in patients with type 2 diabetes mellitus as reflected by an increased oxidative protein loss.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".