Anxiety and depression in patients with endometriosis: impact and management challenges
Bibliographic record
Abstract
Endometriosis is one of the most common gynecological diseases and affects ~10% of women in reproductive age. The most common clinical signs of endometriosis are menstrual irregularities, chronic pelvic pain (CPP), dysmenorrhea, dyspareunia and infertility. Symptoms of endometriosis often affect psychological and social functioning of patients. For this reason, endometriosis is considered as a disabling condition that may significantly compromise social relationships, sexuality and mental health. Considering this point, the aim of this narrative review is to elucidate the impact of anxiety and depression in the management of women with endometriosis. Psychological factors have an important role in determining the severity of symptoms, and women who suffer from endometriosis report high levels of anxiety, depression and other psychiatric disorders. In addition, endometriosis is one of the most important causes of CPP; women with endometriosis suffer from a wide range of pelvic pain such as dysmenorrhea, dyspareunia, nonmenstrual (chronic) pelvic pain, pain at ovulation, dyschezia and dysuria. Several studies have underlined the influence of CPP on quality of life and psychological well-being of women with endometriosis. Data suggest that the experience of pelvic pain is an important component of endometriosis and may significantly affect emotive functioning of affected women. It has been demonstrated that high levels of anxiety and depression can amplify the severity of pain. Further studies are needed to better understand the relationship between psychological factors and perception of pain. Treatment of endometriosis may be hormonal or surgical. Surgery is the primary treatment for more severe forms of endometriosis. There are few data in the literature about the influence of psychological factors and psychiatric comorbidities on the effectiveness of treatments. It is important to evaluate the presence of previous psychiatric diseases in order to select the most appropriate treatment for the patient.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".