Arteriovenous Malformations of the Uterus: Long-Term Follow-Up
Bibliographic record
Abstract
BACKGROUND/AIM: Arteriovenous malformations (AVMs) of the uterus have various clinical presentations. With the advancement of and accessibility to imaging, the diagnosis of the lesions in association with less severe clinical presentations is becoming more common. Contrary to cases with severe hemorrhage, the management of these cases is not clear. The purpose of this study was to describe our experience with diagnosis, management and long-term follow-up of cases with different clinical presentations of uterine AVMs. METHODS: The clinical and sonographic presentations of 8 cases diagnosed between July 2000 and July 2003 in our medical center are described. Annual sonographic follow-up was performed for a period of at least 42 months. RESULTS: Only 3 of the 8 cases presented with heavy vaginal bleeding and 2 of them required selective embolization. Two patients had hysterectomy during the study period which was not related to a severe bleeding event. Long-term follow-up for all other cases was significant for sonographic resolution of the uterine AVM. CONCLUSION: Management of uterine AVMs should be influenced by the clinical and not by the sonographic findings. If clinically feasible, conservative management should be considered as the primary approach, since most of these lesions tend to spontaneously resolve.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".