Guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients
Bibliographic record
Abstract
OBJECTIVE: To evaluate the literature and identify important aspects of insulin therapy that facilitate safe and effective infusion therapy for a defined glycemic end point. METHODS: Where available, the literature was evaluated using Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) methodology to assess the impact of insulin infusions on outcome for general intensive care unit patients and those in specific subsets of neurologic injury, traumatic injury, and cardiovascular surgery. Elements that contribute to safe and effective insulin infusion therapy were determined through literature review and expert opinion. The majority of the literature supporting the use of insulin infusion therapy for critically ill patients lacks adequate strength to support more than weak recommendations, termed suggestions, such that the difference between desirable and undesirable effect of a given intervention is not always clear. RECOMMENDATIONS: The article is focused on a suggested glycemic control end point such that a blood glucose ≥ 150 mg/dL triggers interventions to maintain blood glucose below that level and absolutely <180 mg/dL. There is a slight reduction in mortality with this treatment end point for general intensive care unit patients and reductions in morbidity for perioperative patients, postoperative cardiac surgery patients, post-traumatic injury patients, and neurologic injury patients. We suggest that the insulin regimen and monitoring system be designed to avoid and detect hypoglycemia (blood glucose ≤ 70 mg/dL) and to minimize glycemic variability.Important processes of care for insulin therapy include use of a reliable insulin infusion protocol, frequent blood glucose monitoring, and avoidance of finger-stick glucose testing through the use of arterial or venous glucose samples. The essential components of an insulin infusion system include use of a validated insulin titration program, availability of appropriate staffing resources, accurate monitoring technology, and standardized approaches to infusion preparation, provision of consistent carbohydrate calories and nutritional support, and dextrose replacement for hypoglycemia prevention and treatment. Quality improvement of glycemic management programs should include analysis of hypoglycemia rates, run charts of glucose values <150 and 180 mg/dL. The literature is inadequate to support recommendations regarding glycemic control in pediatric patients. CONCLUSIONS: While the benefits of tight glycemic control have not been definitive, there are patients who will receive insulin infusion therapy, and the suggestions in this article provide the structure for safe and effective use of this therapy.
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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 | 0.026 | 0.095 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".