Survey of gynecologists' and interventional radiologists' opinions of uterine fibroid embolization.
Bibliographic record
Abstract
PURPOSE: To evaluate the opinions of gynecologists and interventional radiologists regarding uterine fibroid embolization (UFE). METHODS: We mailed surveys to all gynecologists and interventional radiologists practising in Toronto, Ontario. Study criteria excluded those physicians who did not assess or treat patients with uterine fibroids. We evaluated whether they educated patients regarding UFE, together with their opinion of current and future effectiveness of UFE, self-rated knowledge of fibroid treatment options, and recommendations for treatment in several clinical scenarios. RESULTS: A total of 102 gynecologists (46.4% response rate) and 28 interventional radiologists (51.9% response rate) completed the survey. After applying the exclusion criteria, the final study population was 82 gynecologists and 17 interventional radiologists. Both groups reported high rates of patient education regarding UFE (gynecologists 100% and interventional radiologist 88.2%, P > 0.05). Interventional radiologists had higher self-rated knowledge of UFE (P = 0.05), and gynecologists had higher self-rated knowledge of all other treatment options (P = 0.00). Interventional radiologists had a more favourable opinion of the current effectiveness (P < 0.05) and future use (P > 0.05) of UFE. In 5 of the 7 clinical scenarios, interventional radiologists chose UFE, whereas gynecologists chose other treatment options (P < 0.05). CONCLUSIONS: Although most gynecologists and intterventional radiologists educate their patients regarding UFE as a treatment option for uterine fibroids, interventional radiologists have greater self-rated knowledge and a higher opinion of current effectiveness and future use and recommend UFE more often for uterine fibroid scenarios.
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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 | 0.002 | 0.010 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".