The Association of Preoperative Glycemic Control, Intraoperative Insulin Sensitivity, and Outcomes after Cardiac Surgery
Bibliographic record
Abstract
CONTEXT: The impairment of insulin sensitivity, a marker of surgical stress, is important for outcomes. OBJECTIVE: The aim was to assess the association between the quality of preoperative glycemic control, intraoperative insulin sensitivity, and adverse events after cardiac surgery. DESIGN AND SETTING: We conducted a prospective cohort study at a tertiary care hospital. SUBJECTS: Nondiabetic and diabetic patients scheduled for elective cardiac surgery were included in the study. Based on their glycosylated hemoglobin A (HbA(1c)), diabetic patients were allocated to a group with good (HbA(1c) <6.5%) or poor (HbA(1c) >6.5%) glycemic control. INTERVENTION: We used the hyperinsulinemic-normoglycemic clamp technique. MAIN OUTCOME MEASURES: The primary outcome was insulin sensitivity measurement. Secondary outcomes were major complications within 30 d after surgery including mortality, myocardial failure, stroke, dialysis, and severe infection (severe sepsis, pneumonia, deep sternal wound infection). Other outcomes included minor infections, blood product transfusions, and the length of intensive care unit and hospital stay. RESULTS: A total of 143 nondiabetic and 130 diabetic patients were studied. In diabetic patients, a negative correlation (r = -0.527; P < 0.001) was observed between HbA(1c) and intraoperative insulin sensitivity. Diabetic patients with poor glycemic control had a greater incidence of major complications (P = 0.010) and minor infections (P = 0.006). They received more blood products and spent more time in the intensive care unit (P = 0.030) and the hospital (P < 0.001) than nondiabetic patients. For each 1 mg x kg(-1) x min(-1) decrease in insulin sensitivity, the incidence of major complications increased (P = 0.004). CONCLUSIONS: In diabetic patients, HbA(1c) levels predict insulin sensitivity during surgery and possibly outcome. Intraoperative insulin resistance is associated with an increased risk of complications, independent of the patient's diabetic state.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".