Coronary Revascularization in Diabetic Patients
Bibliographic record
Abstract
BACKGROUND: The optimal revascularization technique in diabetic patients is an important unresolved question. PURPOSE: To compare long-term outcomes between the revascularization techniques of percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG). DATA SOURCES: English-language publications in PubMed, the Cochrane Central Register of Controlled Trials, Ovid, and EMBASE between 1 January 1990 and 1 June 2014. STUDY SELECTION: Two investigators independently reviewed randomized, controlled trials comparing PCI (with drug-eluting or bare-metal stents) with CABG in adults with diabetes with multivessel or left main coronary artery disease. DATA EXTRACTION: Study design, quality, patient characteristics, length of follow-up, and outcomes were extracted. For duplicate publications, outcomes were obtained from the publication with the longest follow-up. DATA SYNTHESIS: 40 studies were combined using a Bayesian network meta-analysis that accounted for the variation in stent choice. The primary outcome, a composite of all-cause mortality, nonfatal myocardial infarction, and stroke, increased with PCI (odds ratio [OR], 1.33 [95% credible interval {CrI}, 1.01 to 1.65]). Percutaneous coronary intervention resulted in increased mortality (OR, 1.44 [CrI, 1.05 to 1.91]), no change in the number of myocardial infarctions (OR, 1.33 [CrI, 0.86 to 1.95]), and fewer strokes (OR, 0.56 [CrI, 0.36 to 0.88]). LIMITATIONS: Study design and length of follow-up were heterogeneous, and results were driven primarily by a single study. Costs and nonvascular complications of the interventions were not examined. CONCLUSION: Coronary artery bypass grafting seems to be the preferred revascularization technique in diabetics, especially if long-term survival is anticipated. However, because of residual uncertainties and increased risk for stroke with CABG, clinical judgment is required when choosing a revascularization technique in patients with diabetes. PRIMARY FUNDING SOURCE: Fonds de recherche du Québec-Santé.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".