Management of Hyperglycemia in Hospitalized Adult Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline
Bibliographic record
Abstract
BACKGROUND: Adult patients with diabetes or newly recognized hyperglycemia account for over 30% of noncritically ill hospitalized patients. These patients are at increased risk for adverse clinical outcomes in the absence of defined approaches to glycemic management. OBJECTIVE: To review and update the 2012 Management of Hyperglycemia in Hospitalized Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline and to address emerging areas specific to the target population of noncritically ill hospitalized patients with diabetes or newly recognized or stress-induced hyperglycemia. METHODS: A multidisciplinary panel of clinician experts, together with a patient representative and experts in systematic reviews and guideline development, identified and prioritized 10 clinical questions related to inpatient management of patients with diabetes and/or hyperglycemia. The systematic reviews queried electronic databases for studies relevant to the selected questions. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make recommendations. RESULTS: The panel agreed on 10 frequently encountered areas specific to glycemic management in the hospital for which 15 recommendations were made. The guideline includes conditional recommendations for hospital use of emerging diabetes technologies including continuous glucose monitoring and insulin pump therapy; insulin regimens for prandial insulin dosing, glucocorticoid, and enteral nutrition-associated hyperglycemia; and use of noninsulin therapies. Recommendations were also made for issues relating to preoperative glycemic measures, appropriate use of correctional insulin, and diabetes self-management education in the hospital. A conditional recommendation was made against preoperative use of caloric beverages in patients with diabetes. CONCLUSION: The recommendations are based on the consideration of important outcomes, practicality, feasibility, and patient values and preferences. These recommendations can be used to inform system improvement and clinical practice for this frequently encountered inpatient population.
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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 | 0.013 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".