EP25.23: Prevalence of contrast venous intravasation during hysterosalpingo‐contrast‐sonography: asystematic review and meta‐analysis
Bibliographic record
Abstract
To assess the prevalence of contrast-venous intravasation during hysterosalpingo-contrast-sonography (HyCoSy) for assessment of tubal patency in infertile women. Systematic review of literature using database search (Pubmed, Scopus and Web of Science) of articles published between January 2000 and March 2024 evaluating the presence of contrast-venous intravasation during HyCoSy for assessment of tubal patency in infertile women. We used the following terms: “intravasation”, “uterine”, “tubal patency”, “ultrasound”, “ultrasonography”. The pooled prevalence for intravasation phenomenon was estimated. Heterogeneity was assessed by calculating I. Quality of studies was assessed using the Newcastle-Ottawa scale. The search identified 74 studies. After exclusions, 10 articles that met inclusion criteria were included, comprising data from 4612 women. Eight studies (all from China) used SonoVue as contrast agent and two studies (both from Australia) used ExEmFoam as contrast agent. Pooled prevalence for contrast intravasation was significantly higher for SonoVue (21.0%, 95%CI: 20.0%-22.0%) than for ExEmFoam (7.0%, 95%CI: 5.0%-7.0%). However, the sample size was significantly lower in ExEmFoam studies (N = 488 versus N= 4124). No heterogeneity was observed between studies (I: 0%). Studies quality was good Contrast-venous intravasation is a common phenomenon during HyCoSy procedures using SonoVue as contrast agent. It seems to be much less frequent when using HyFoSy.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".