Diabetes and the Association of Postoperative Hyperglycemia With Clinical and Economic Outcomes in Cardiac Surgery
Bibliographic record
Abstract
OBJECTIVE: The management of postoperative hyperglycemia is controversial and generally does not take into account pre-existing diabetes. We analyzed clinical and economic outcomes associated with postoperative hyperglycemia in cardiac surgery patients, stratifying by diabetes status. RESEARCH DESIGN AND METHODS: Multicenter cohort study in 4,316 cardiac surgery patients operated on in 2010. Glucose was measured at 6-h intervals for 48 h postoperatively. Outcomes included cost, hospital length of stay (LOS), cardiac and respiratory complications, major infections, and death. Associations between maximum glucose levels and outcomes were assessed with multivariable regression and recycled prediction analyses. RESULTS: In patients without diabetes, increasing glucose levels were associated with a gradual worsening of outcomes. In these patients, hyperglycemia (≥180 mg/dL) was associated with an additional cost of $3,192 (95% CI 1,972 to 4,456), an additional hospital LOS of 0.8 days (0.4 to 1.3), an increase in infections of 1.6% (0.5 to 2.8), and an increase in respiratory complications of 2.6% (0.0 to 5.3). However, among patients with insulin-treated diabetes, optimal outcomes were associated with glucose levels considered to be hyperglycemic (180 to 240 mg/dL). This level of hyperglycemia was associated with cost reductions of $6,225 (-12,886 to -222), hospital LOS reductions of 1.6 days (-3.7 to 0.4), infection reductions of 4.1% (-9.1 to 0.0), and reductions in respiratory complication of 12.5% (-22.4 to -3.0). In patients with non-insulin-treated diabetes, outcomes did not differ significantly when hyperglycemia was present. CONCLUSIONS: Glucose levels <180 mg/dL are associated with better outcomes in most patients, but worse outcomes in patients with diabetes with a history of prior insulin use. These findings support further investigation of a stratified approach to the management of patients with stress-induced postoperative hyperglycemia based on prior diabetes status.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".