Moderate hyperglycemia and a blunted anabolic response to perioperative parenteral amino acids in type 2 diabetes mellitus patients undergoing colorectal cancer surgery
Bibliographic record
Abstract
Insulin resistance of type 2 diabetes mellitus (T2DM) is accentuated by surgical stress. Hyperglycemia can also be exacerbated by nutrition support; so a balance of anabolic and euglycemic strategies is essential. Patients with T2DM (n=7) or without (ND, n=11) undergoing colorectal cancer surgery received parenteral nutrition (PN) based on 20% of resting energy expenditure as amino acids (AAs, from 20h preop). Glucose, protein kinetics and fractional synthesis rate (FSR) of hepatic secretory proteins were measured with D‐[6,6‐ 2 H 2 ] glucose, L‐[1‐ 13 C]leucine and L‐[ring‐ 2 H 5 ]phenylalanine while fasting preop, and again while receiving PN two days postop. In fasted state preop, subjects were in negative leucine balance, with T2DM being more negative than ND (p<0.027). PN improved leucine balance (p=0.008), but balance was more negative in T2DM. Surgery invoked an acute phase response with increased fibrinogen (p<0.0001) and its FSR (p<0.0007). Albumin FSR was maintained to a similar extent postop. Plasma glucose was similar preop, but higher postop in T2DM (p<0.005), possibly resulting from a tendency for higher endogenous production (p<0.10) and lower clearance (p<0.13). Plasma AAs showed changes typical of surgery attenuated increases in branched chains (p=0.035) and essentials (p=0.026) in T2DM. PN with AAs supports acute phase response in T2DM but with moderate hyperglycemia and a blunted anabolic response. Higher AA doses or combined AA and low glucose are suggested achieve anabolic response in T2DM.(Canadian Institutes of Health Research)
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".