The effect of small intramural uterine fibroids on the cumulative outcome of assisted conception
Bibliographic record
Abstract
BACKGROUND: This study aimed to evaluate the effect of small intramural fibroids on the cumulative pregnancy, ongoing pregnancy, live birth and implantation rates after three IVF/ICSI attempts. METHODS: The first three treatment cycles of women enrolled for IVF/ICSI over a 12-month period were analysed. Only patients with small (<or=5 cm) intramural fibroids not encroaching upon the endometrial cavity were included in the fibroid group. Cox's hazards regression was used to estimate the hazard ratio (HR) associated with the presence of intramural fibroids. RESULTS: During the study period, 322 women without fibroids (control group) and 112 women with fibroids (study group) underwent 606 IVF/ICSI cycles. The pregnancy, ongoing pregnancy and live birth rates in the study group were 23.6, 18.8 and 14.8% compared with 32.9, 28.5 and 24% in the control group, respectively (P<0.05). Cox regression analysis showed that the pregnancy rate at each cycle was reduced by 39% (HR=0.61, 95% CI=0.39-0.95, P=0.029) in the study group compared with the control group. The cumulative ongoing pregnancy rate was reduced by 43% (HR=0.57, 95% CI=0.35-0.91, P=0.018), and the cumulative live birth rate was reduced by 47% (HR=0.53, 95% CI=0.32-0.87, P=0.013) in the study group. After adjusting for confounding variables, the presence of fibroids was found to significantly reduce the ongoing pregnancy rate at each cycle of IVF/ICSI by 40% (HR=0.60, 95% CI=0.36-0.99, P=0.048) and the live birth rate at each cycle by 45% (HR=0.55, 95% CI=0.32-0.95, P=0.03). CONCLUSION: Small intramural fibroids are associated with a significant reduction in the cumulative pregnancy, ongoing pregnancy and live birth rates after three IVF/ICSI cycles.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".