Sliding Scale Regular Human Insulin for Identifying Critically Ill Patients Who Require Intensive Insulin Therapy and for Glycemic Control in those with Mild to Moderate Hyperglycemia
Bibliographic record
Abstract
Two sliding scale regular human insulin (RHI) algorithms (SSI) were retrospectively evaluated to identify those who develop severe hyperglycemia (blood glucose (BG) > 180 mg/dL) and for glycemic management of continuously-fed, critically ill trauma patients with mild to moderate hyperglycemia (BG 126 to 179 mg/dL). Assignment of low or high SSI was based upon anticipated severity of difficulty in glycemic control. BG was obtained every 3 to 6 hours. Target BG range was 70 to 149 mg/dL. Patients who were unable to achieve a BG < 150 mg/dL with SSI and who required a continuous intravenous RHI infusion were identified. Twenty-five of 121 patients (21%) failed SSI necessitating more intensive insulin therapy. The low and high intensity SSI groups exhibited a baseline BG of 123 + 33 mg/dL and 164 + 20 mg/dL (P = 0.001). Average BG for each group was 129 ± 14 mg/dL and 145 ± 21 mg/dL (P = 0.001). Each group spent 20 ± 4 and 16 ± 5 hours/day within the target BG range (P = 0.001), respectively. Mild hypoglycemia (BG 40 - 60 mg/dL) occurred in 11% and 7% of patients from each group (P = N.S.). Severe hypoglycemia (BG < 40 mg/dL) occurred in zero and two (5%) patients, respectively (P = N.S). SSI served as a useful technique to identify those requiring more intensive insulin therapy and was safe and efficacious for continuously-fed, critically ill trauma patients with mild to moderate hyperglycemia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".