Pelvic Pain, Mental Health and Quality of Life in Adolescents with Endometriosis after Surgery and Dienogest Treatment
Bibliographic record
Abstract
BACKGROUND: Diagnostic and treatment delays have caused significant impacts on the physical and emotional well-being of adolescents with endometriosis, though such research is limited. This study aimed to assess the effects of one-year dienogest therapy on the clinical picture, pain patterns, psycho-emotional status, and quality-of-life indicators in adolescents with endometriosis after surgical treatment. METHODS: The study enrolled 32 girls aged 13-17 with peritoneal endometriosis to analyze one-year dynamics of the Visual Analog Scale (VAS), McGill Pain Questionnaire, Beck Depression Scale (BDI), Hospital Anxiety and Depression Scale (HADS), Spielberger State-Trait Anxiety Inventory (STAI) and SF-36 quality-of-life survey scores along with clinical and laboratory indicators before surgery and after one-year dienogest therapy. RESULTS: The therapy provided a significant alleviation of endometriosis-associated clinical symptoms, including dysmenorrhea, pelvic pain, gastrointestinal/dysuria symptoms, decreased everyday activity (<0.001), a decrease in anxiety/depression scores (BDI, HADS, STAI), and quality-of-life improvement (<0.001). These effects were accompanied by beneficial dynamics in hormone and inflammatory markers (prolactin, cortisol, testosterone, estradiol, CA-125, neutrophil/lymphocyte ratio; <0.005) within reference ranges. A low body mass index and high C-reactive protein levels were associated with higher VAS scores; a high estradiol level was a factor for anxiety/depression aggravation (<0.05). CONCLUSIONS: Dienogest, after surgical treatment, significantly improved quality of life and reduced pain symptoms while showing good tolerability and compliance, and reasoning with timely hormonal therapy in adolescents with endometriosis.
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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 | 0.000 | 0.001 |
| 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".