Surgical Outcomes in Patients With Endometriosis: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Among women treated surgically for endometriosis-associated pain, comprehensive data are lacking on the proportions of patients who experience little or no symptom relief, develop recurrent symptoms, or require further surgical treatment for endometriosis. The aim of this study was to assess the efficacy of surgical procedures used to treat endometriosis-associated pain. METHODS: Medline and Embase were searched on October 13, 2016. Articles referring to women undergoing surgery for the treatment of endometriosis-associated pain were screened by two independent investigators. For each included treatment arm, data were extracted for the proportion of patients reporting partial or no improvement after surgery for endometriosis-associated pain, pain recurrence, or requirement for further surgery. RESULTS: A total of 38 studies were included. Most studies did not report relevant outcomes to evaluate pain (71.1%) and recurrent surgery (68.4%). Of the women who underwent lesion excision, 11.8% reported no improvement in pain, and 22.6% underwent further surgery. Postoperative pain, recurrent pain, and adverse events were reported by 34.3%, 28.7%, and 14.8%, respectively, of patients who underwent excision or ablation of endometriosis combined with pelvic denervation and in 25.0%, 15.8%, and 8.1% of women who underwent lesion excision alone. Of the patients who were treated surgically for deep endometriosis affecting the bowel and/or bladder, 7.0% experienced recurrent symptoms, and 4.1% underwent further surgery. CONCLUSION: This review supports the findings of previous studies and highlights the need for standardized reporting and more detailed follow-up after surgery for endometriosis-associated pain.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".