Maintenance of Normoglycemia During Cardiac Surgery
Bibliographic record
Abstract
In Brief We used the hyperinsulinemic normoglycemic clamp technique, i.e., infusion of insulin at a constant rate combined with dextrose titrated to clamp blood glucose at a specific level, to preserve normoglycemia during elective cardiac surgery. Ten nondiabetic and seven diabetic patients entered the clamp protocols. Perioperative glucose control was also assessed in 19 nondiabetic and 11 diabetic patients (control group) receiving a conventional insulin infusion sliding scale. In patients of the clamp group, a priming bolus of insulin (2 U) was started before the induction of anesthesia followed by infusions of insulin at 5 mU·kg−1·min−1 and of variable amounts of dextrose. Arterial blood glucose was measured every 5 min in the clamp group and every 20 min in the control group. Control of normoglycemia was defined as ≥95% of the glucose levels within 4.0–6.0 mmol/L. Glucose concentration was recorded before surgery, 15 min before cardiopulmonary bypass (CPB), during early and late CPB, and at sternal closure. Patients of the control group became progressively hyperglycemic during surgery (late CPB; nondiabetics, 9.0 ± 3.2 mmol/L; diabetics, 10.1 ± 3.6 mmol/L), whereas normoglycemia was achieved in the study group (late CPB; nondiabetics, 5.5 ± 0.7 mmol/L; diabetics, 4.9 ± 0.6 mmol/L; P < 0.05 versus control group). In conclusion, it seems that normal blood glucose concentration during open heart surgery can be reliably maintained in nondiabetic and diabetic patients by using the hyperinsulinemic normoglycemic clamp technique. IMPLICATIONS: The hyperinsulinemic normoglycemic clamp can be used to preserve normoglycemia during open heart surgery. This technique in combination with a continuous intravenous glucose monitoring system may be applied in future studies to investigate the effect of aggressive intraoperative glucose control on outcome after cardiac surgery.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".