Endometriosis fertility index predicts live births following surgical resection of moderate and severe endometriosis
Bibliographic record
Abstract
STUDY QUESTION: Can live birth be accurately predicted following surgical resection of moderate-severe (Stage III-IV) endometriosis? SUMMARY ANSWER: Live births can accurately be predicted with the endometriosis fertility index (EFI), with adnexal function being the most important factor to predict non-assisted reproductive technology (non-ART) fertility or the requirement for ART (www.endometriosisefi.com). WHAT IS KNOWN ALREADY: Fertility prognosis is important to many women with severe endometriosis. Controversy persists regarding optimal post-operative management to achieve pregnancy and the counselling of patients regarding duration of conventional treatments before undergoing ART. The EFI is reported to correlate with expectant management pregnancy rate, although external validation has been performed without specifically addressing fertility in women with moderate and severe endometriosis. STUDY DESIGN, SIZE, DURATION: Retrospective cohort study of 279 women from September 2001 to June 2016. PARTICIPANTS/MATERIALS, SETTINGS, METHODS: We included women undergoing laparoscopic resection of Stage III-IV endometriosis who attempted pregnancy post-operatively. The EFI was calculated based on detailed operative reports and surgical images. Fertility outcomes were obtained by direct patient contact. Kaplan-Meier model, log rank test and Cox regression were used for analyses. MAIN RESULTS AND THE ROLE OF CHANCE: The follow-up rate was 84% with a mean duration of 4.1 years. A total of 147 women (63%) had a live birth following surgery, 94 of them (64%) without ART. The EFI was highly associated with live births (P < 0.001): for women with an EFI of 0-2 the estimated cumulative non-ART live birth rate at five years was 0% and steadily increased up to 91% with an EFI of 9-10, while the proportion of women who attempted ART and had a live birth, steadily increased from 38 to 71% among the same EFI strata (P = 0.1). A low least function score was the most significant predictor of failure (P = 0.003), followed by having had a previous resection (P = 0.019) or incomplete resection (P = 0.028), being older than 40 compared to <35 years of age (P = 0.027), and having leiomyomas (P = 0.037). LIMITATIONS REASONS FOR CAUTION: The main limitation of this study is its retrospective design. Imprecision was higher with low EFI due to smaller sample size in this subgroup. Finally, the EFI is somewhat subjective and could be prone to intra- and inter-observer variations. WIDER IMPLICATIONS OF THE FINDINGS: Women with a high EFI score have excellent fertility prognosis and may be advised to try to become pregnant with timed intercourse compared to women with a low score, for which prompt referral to ART seems more reasonable. Other prognostic factors can be used to guide the management of women with an intermediate EFI score. These data follow women over many years post-resection and represent longitudinal fertility data rarely demonstrated in such a cohort. The location and impact of lesions on the ability of the adnexa to function seems crucial for the fertility prognosis and should be further investigated. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by the GRACE Research funds. S.M.-L. is the recipient of a Training Award from the Fonds de Recherche Quebec-Sante. D.A. is the primary author of the Endometriosis Fertility Index. All authors have no conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A.
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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 | 0.005 |
| 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) | 0.002 | 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".