Sternal neoangiogenesis following internal mammary artery devascularization: an experimental model.
Bibliographic record
Abstract
AIM: The use of bilateral internal thoracic arteries (BIMA) for coronary artery revascularization is associated with better long-term survival and longer freedom from reoperation. Concerns of deep sternal wound infections and mediastinitis have constantly emerged with the utilization of BIMA grafts on a routine basis, especially in diabetic patients. METHODS: We performed a quantitative evaluation of sternal bone healing and angiogenesis after left (LIMA) or bilateral internal mammary artery (BIMA) ligation two and four weeks after sternotomy in normal and diabetic Sprague-Dawley rats. RESULTS: The BIMA group showed a significant increase in neoangiogenesis two weeks after surgery compared to LIMA and control groups (control: 38.3 ± 5.1 vessels/mm², LIMA: 31.4 ± 3.6 vessels/mm², BIMA: 81.6 ± 7.7 vessels/mm²; P=0.047 and P=0.04, respectively). Four weeks after the procedure, bilateral devascularization was associated with lower microvessel formation when compared to LIMA or control groups (control: 50.4 ± 5.2 vessels/mm², LIMA: 64.6 ± 4.9 vessels/mm²; BIMA: 31.5 ± 4.4 vessels/mm²; P=0.006 and P=0.02, respectively). Diabetic animals showed similar results with lower four weeks microvessel formation. However, there were no significant differences when animals with induced diabetes were compared to the normal euglycemic groups for each procedure performed. CONCLUSION: BIMA ligation promotes an early increase in neoangiogenesis. Progressive sternal consolidation is associated with a significant lower level of capillaries and arterioles in the BIMA group four weeks after ligation. Diabetes did not influence the extent of neoangiogenesis between groups with similar procedures. More important clinical determinants could explain the increase incidence of sternal infection in this specific population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".