Psychological stress levels in women with endometriosis: systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
INTRODUCTION: Endometriosis is defined as the presence of endometrial-like tissue outside the uterus, associated with chronic and inflammatory reaction. Symptoms range from dysmenorrhea, dyspareunia, chronic pelvic pain, unexplained infertility to asymptomatic. The patients' quality of life is affected by anxiety, depression and stress. We aimed to verify the prevalence and levels of psychological stress among women with endometriosis. EVIDENCE ACQUISITION: The systematic review followed the PRISMA statement and the MOOSE guideline. Databases searched were MEDLINE, EMBASE, PsychNET and SciELO. The risk of bias was assessed with a modified Newcastle-Ottawa Scale. The meta-analysis of proportions used inverse variance method for pooling and random-effects model. For the stress levels we used the restricted maximum likelihood estimator for summary effects. Heterogeneity was assessed through I2 and Q statistics. Publication bias was assessed through funnel plots. Meta-regression adopted a mixed-effects model, considering patient age, endometriosis staging, stress assessment tool and data collection as categorical moderators. EVIDENCE SYNTHESIS: We included 15 studies encompassing 4,619 women with endometriosis. The overall prevalence of mild/high stress was 68% (95%CI:57%-79%), I2=98% and τ2=0.0228. The mean level of stress was 41.78% (95%CI =34.05%-49.51%), I2=99.9% and τ2=83.35. Meta-regression showed relationship with endometriosis staging. CONCLUSIONS: This is the first meta-analysis exploring the association between endometriosis and psychological stress. The interdisciplinary management of the disease should expand the mental health support in this patient care, beyond pain management. Finally, the attitude of the medical team acknowledging the patients' psychological stress may positively affect their treatment.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Meta-analysis | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.019 | 0.001 |
| Bibliometrics | 0.001 | 0.007 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".