Plaque distribution in common femoral artery bifurcations, based on multi-slice computed tomography assessment
Bibliographic record
Abstract
Purpose The aim of this study was to observe the exact plaque distribution at the common femoral artery bifurcation by multi-slice computed tomography angiography and to examine the relationship between plaque distribution and carina location. Methods Symptomatic outpatients who underwent multi-slice computed tomography angiography between May 2013 and February 2015 were enrolled in this study. The presence and distribution of atherosclerotic plaques were assessed in cross section views of vessel lumen. Each vessel lumen cross section was divided into four equal quadrants for the common femoral, superficial femoral and profunda femoral arteries. The quadrant of the superficial femoral artery in which the carina was located was also recorded. Results In total, 184 common femoral artery bifurcations in 92 patients were analyzed. Normal arteries were more common in profunda femoral arteries than in common femoral arteries and superficial femoral arteries (both P< 0.001). Plaques were found more medial and posterior quadrants in common femoral arteries. In superficial femoral arteries, plaques were found most frequently in anterior quadrants (78.3%, n=144) and least frequently in posterior quadrants (49.5%, n=91). The carina was located in the posterior quadrant in 160 bifurcations (87.0%) of superficial femoral arteries. Quadrants opposite the carina contained plaque most proportionally (77.2%) and quadrants of carina were affected least proportionally (52.7%) in superficial femoral arteries (P <0.001). Quadrants adjacent to the carina clockwise or anticlockwise also contained a higher proportion than carina quadrants. Significance was found for anticlockwise quadrants (p=0.002), but not for clockwise quadrants (P=0.21). Conclusions The presence and distribution of atherosclerotic plaques were diverse in different artery beds of the common femoral artery bifurcations. Plaque tended to be located in areas opposite the carina in superficial femoral arteries.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".