Abstract 12188: Intensive Glycemic Control in Patients With Acute Coronary Syndrome: Evidence From a Meta-Analysis
Bibliographic record
Abstract
Introduction: Hyperglycemia is associated with unfavorable prognosis in patients with acute coronary syndrome (ACS). Studies with intensive glycemic control in ACS patients have provided inconsistent results. A meta-analysis was performed to evaluate the effectiveness and safety of intensive glycemic control in patients with ACS. Methods: Search of PubMed, Cochrane CENTRAL, EMBASE, EBSCO, Web of Science and CINAHL databases from their inception through April 2014, identifying randomized controlled trials (RCTs) comparing the effects of intensive versus standard glucose management in patients with ACS. We calculated summary random-effect odds ratios (OR) and 95% confidence intervals (CI). Results: Results from 10 RCTs comprising 2,621 patients were analyzed. All-cause mortality between intensive versus standard glucose management groups did not differ significantly (OR 1.00, 95% CI 0.75-1.34). Similarly, no significant differences were observed between the comparator groups for the odds of cardiac mortality (OR 0.87, 95% CI, 0.67 to 1.12), recurrent myocardial infarction (OR 1.07, 95% CI, 0.76 to 1.52), or stroke (OR 1.20, 95% CI, 0.60 to 2.40). The risk of hypoglycemia (OR 5.95, 95% CI, 2.73 to 12.97; p<0.001) was significantly higher with intensive compared with standard glucose management. Conclusions: Intensive glucose control compared with standard care in ACS patients did not reduce mortality or morbidity, but significantly increased the risk of hypoglycemia. These data from prior clinical trials should be interpreted in the context of their significant methodological limitations.
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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 | 0.019 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.032 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".