Impact of coronary collateralization on long-term clinical outcomes in type 2 diabetic patients after successful recanalization of chronic total occlusion
Bibliographic record
Abstract
BACKGROUND: To assess the prognostic role of coronary collaterals in patients with type 2 diabetes mellitus (T2DM) after successful percutaneous coronary intervention (PCI) for chronic total occlusion (CTO). METHODS: Coronary collateralization was graded according to Rentrop scoring system in 198 type 2 diabetic patients and 335 non-diabetics with stable angina undergoing PCI for at least one CTO lesion. Left ventricular ejection fraction (LVEF) was determined and major adverse cardio-cerebral events (MACCE) were recorded during follow-up. RESULTS: Poor collateralization was more common in patients with T2DM than in non-diabetics (40% vs 29%, p = 0.008). At 13.5 ± 4.1 months, the rate of composite MACCE (17.3% vs 27.6%, p = 0.034) and repeat revascularization (15.2% vs 25.5%, p = 0.026) was lower and the increase in LVEF (3.10% vs 1.80%, p = 0.024) was greater in patients with good collaterals than in those with poor collaterals for non-diabetic group. The associations were in the same direction for T2DM group (35% vs 44%; 30% vs 36%; 2.14% vs 1.65%, respectively) with a higher all-cause mortality in diabetic patients with poor collaterals (p = 0.034). Multivariable Cox proportional hazards analysis showed that coronary collateralization was an independent factor for time to MACCE (HR 2.155,95% CI 1.290-3.599, p = 0.003) and repeat revascularization (HR 2.326, 95% CI 1.357-3.986, p = 0.002) in non-diabetic patients, but did not enter the model in those with T2DM. CONCLUSIONS: T2DM is associated with reduced coronary collateralization. The effects of the status of coronary collateralization on long-term clinical outcomes and left ventricular function appear to be similar in size in type 2 diabetic patients and non-diabetics after successful recanalization of CTO.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".