Mental Health Outcomes of Endometriosis Patients during the COVID-19 Pandemic: Impact of Pre-pandemic Central Nervous System Sensitization
Bibliographic record
Abstract
To correlate pain-related phenotyping for central nervous system sensitization in endometriosis-associated pain with mental health outcomes during the COVID-19 pandemic, the prospective Endometriosis and Pelvic Pain Interdisciplinary Cohort (ClinicalTrials.gov #NCT02911090) was linked to the COVID-19 Rapid Evidence Study of a Provincial Population-Based Cohort for Gender and Sex (RESPPONSE) dataset. The primary outcomes were depression (PHQ-9) and anxiety (GAD-7) scores during the pandemic. The explanatory variables of interest were the Central Sensitization Inventory (CSI) score (0-100) and endometriosis-associated chronic pain comorbidities/psychological variables before the pandemic. The explanatory and response variables were assessed for correlation, followed by multivariable regression analyses adjusting for PHQ-9 and GAD-7 scores pre-pandemic as well as age, body mass index, and parity. A higher CSI score and a greater number of chronic pain comorbidities before the pandemic were both positively correlated with PHQ-9 and GAD-7 scores during the pandemic. These associations remained significant in adjusted analyses. Increasing the CSI score by 10 was associated with an increase in pandemic PHQ-9 by .74 points (P < .0001) and GAD-7 by .73 points (P < .0001) on average. Each additional chronic pain comorbidity/psychological variable was associated with an increase in pandemic PHQ-9 by an average of .63 points (P = .0004) and GAD-7 by .53 points (P = .0002). Endometriosis patients with a history of central sensitization before the pandemic had worse mental health outcomes during the COVID-19 pandemic. As a risk factor for mental health symptoms in the face of major stressors, clinical proxies for central sensitization can be used to identify endometriosis patients who may need additional support. PERSPECTIVE: This article adds to the growing literature of the clinical importance of central sensitization in endometriosis patients, who had more symptoms of depression and anxiety during the COVID-19 pandemic. Clinical features of central sensitization may help clinicians identify endometriosis patients needing additional support when facing major stressors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".