Endometriosis: Does Surgery Offer Long-Term Improvement in Quality of Life?
Bibliographic record
Abstract
Introduction Endometriosis is a common, estrogen-dependent, benign disease that affects women of reproductive age. Endometriosis frequently presents with pain and can result in infertility. The symptoms of the disease have a negative impact on physical and mental aspects of life, contribute to reduction of social contacts and lead to a significant reduction in quality of life. In this study, we investigated quality of life of patients with endometriosis. Moreover, we examined whether surgical management could be beneficial for those patients in terms of improving quality of life. Material and methods In this prospective study, we included patients undergoing gynecological operations due to endometriosis-associated problems between 2008 and 2014. All patients were assessed preoperatively and 30 months postoperatively. The survey form chosen to achieve the aims of the study was the Greek version of SF-36. Results The results showed that both physical and mental health were highly compromised in patients affected by endometriosis, and surgical management significantly improved patients’ quality of life, as all of the SF-36 scores were higher postoperatively (p<0.05). Discussion Endometriosis represents an important medical problem in women, with a high impact on their quality of life, and surgical management can reverse the impact of endometriosis on patients’ health and restore their quality of life.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".