Dietary Management of Blood Glucose in Medical Critically Ill Overweight and Obese Patients: An Open‐Label Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Enteral nutrition (EN) increases hyperglycemia due to high carbohydrate concentrations while providing insufficient protein. The study tested whether an EN formula with very high-protein- and low-carbohydrate-facilitated glucose control delivered higher protein concentrations within a hypocaloric protocol. METHODS: This was a multicenter, randomized, open-label clinical trial with parallel design in overweight/obese mechanically ventilated critically ill patients prescribed 1.5 g protein/kg ideal body weight/day. Patients received either an experimental very high-protein (37%) and low-carbohydrate (29%) or control high-protein (25%) and conventional-carbohydrate (45%) EN formula. RESULTS: A prespecified interim analysis was performed after enrollment of 105 patients (52 experimental, 53 control). Protein and energy delivery for controls and experimental groups on days 1-5 were 1.2 ± 0.4 and 1.1 ± 0.3 g/kg ideal body weight/day (P = .83), and 18.2 ± 6.0 and 12.5 ± 3.7 kcals/kg ideal body weight/day (P < .0001), respectively. The combined rate of glucose events outside the range of >110 and ≤150 mg/dL were not different (P = .54, primary endpoint); thereby the trial was terminated. The mean blood glucose for the control and the experimental groups were 138 (-SD 108, +SD 177) and 126 (-SD 99, +SD 160) mg/dL (P = .004), respectively. Mean rate of glucose events >150 mg/dL decreased (Δ = -13%, P = .015), whereas that of 80-110 mg/dL increased (Δ = 14%, P = .0007). Insulin administration decreased 10.9% (95% CI, -22% to 0.1%; P = .048) in the experimental group relative to the controls. Glycemic events ≤80 mg/dL and rescue dextrose use were not different (P = .23 and P = .53). CONCLUSIONS: A very high-protein and low-carbohydrate EN formula in a hypocaloric protocol reduces hyperglycemic events and insulin requirements while increasing glycemic events between 80-110 mg/dL.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".