Analysis of Arterial Blood Vessels Surrounding the Myoma
Bibliographic record
Abstract
OBJECTIVE: The optimal direction of myomectomy incision in relation to the blood vessels is unclear. Accordingly, we evaluated the location and course of arterial blood vessels surrounding the myoma. METHODS: This study is a retrospective analysis of 592 arterial blood vessels in 60 patients with symptomatic uterine leiomyomata undergoing uterine artery embolization. RESULTS: We encountered 592 arterial blood vessels surrounding the myoma. The vessels could be seen encircling the surface of the myoma. The dominant myoma was located on anterior (n=30), posterior (n=17), and fundal part of the uterus (n=13). There was no difference in the diameter (6.9+/-2.7 cm, 5.8+/-0.7 cm, and 6.7+/-0.5 cm) and volume of the myoma (268.6+/-52.7 cm(3), 197.0+/-64.5 cm(3), and 199.3+/-40.5 cm(3)) among anterior, posterior, and fundal, respectively. The vessels were graded as coursing with angles of 0-30 degrees, 30-60 degrees, and 60-90 degrees. There were significantly more blood vessels in the 30-60 degree group among anterior myoma (n=88, 42.5%) than in 0-30 degree (n=59, 28.5%, P=.004, 95% confidence interval [CI] 0.36-0.81) and 60-90 degree groups (n=60, 29.0%, 95% CI 1.2-2.7). Similar findings were found among posterior myoma (0-30 degrees n=26, 21.7%; 30-60 degrees n=59, 49.2%; P<.001, 95% CI 0.16-0.50; 60-90 degrees 35 (29.2%), P<.002, 95% CI 1.37-3.9). Among fundal myomas, there was no difference in the number of vessels in the 0-30 degree (n=28, 28.6%), 60-90 degree (n=40, 40.8%), and in 60-90 degree groups (n=30, 30.6%). CONCLUSION: Arterial blood vessels travel mostly diagonally on the surface of anterior and posterior myomas. There was no predominant pattern in the course of the arteries on fundal myomas. These findings suggest that regardless of the direction of the myomectomy incision, arterial blood vessels on myoma surface could be injured. LEVEL OF EVIDENCE: II.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".