Topical Vasodilator Response is Significantly Higher in Skeletonized Internal Mammary Artery
Bibliographic record
Abstract
AIM OF THE STUDY: Coronary artery bypass graft surgery is the gold standard for the treatment of multi-vessel and left main coronary artery disease. However, there is considerable debate that whether left internal mammary artery (IMA) should be taken as pedicled or skeletonized. This study was conducted to assess the difference in blood flow after application of topical vasodilator in skeletonized and pedicled IMA. METHODS: In this study, each patient underwent either skeletonized (n=25) or pedicled IMA harvesting (n=25). The type of graft on each individual patient was decided randomly. Intra-operative variables such as conduit length and blood flow were measured by the surgeon himself. The length of the grafted IMA was carefully determined in-vivo, with the proximal and distal ends attached, from the first rib to IMA divergence. The IMA flow was measured on two separate occasions; before and after application of topical vasodilator. Known cases of subclavian artery stenosis and previous sternal radiation were excluded from the study. RESULTS: The blood flow before application of topical vasodilator was similar in both the groups (P=0.227). However, the flow was significantly less in pedicled than skeletonized IMA after application of vasodilator (P < 0.0001). Similarly, the length of skeletonized graft was significantly higher than the length of pedicled graft (P < 0.0001). CONCLUSION: Our study signifies that skeletonization of IMA results in increased graft length and blood flow especially after the application of topical vasodilator. However, we recommend that long term clinical trials should be conducted to fully determine long term patency rates of skeletonized IMA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".