Nociplastic Pain in Endometriosis: A Scoping Review
Bibliographic record
Abstract
Endometriosis is an inflammatory chronic condition associated with nociceptive, neuropathic, and nociplastic pain. Central sensitization (CS) is the primary nociplastic pain mechanism. However, there are currently no standardized methods for detecting CS or nociplastic pain. This review aims to identify available tools for characterizing CS/nociplastic pain in endometriosis-related chronic pelvic pain. Following the PRISMA-P protocol, MEDLINE, Embase, Scopus, and PsychINFO databases were searched on 23 April 2024, for the terms "endometriosis", "central sensitization", "nociplastic pain", "widespread pain", and "assessment tools". Publications were selected if they mentioned tool(s) for detecting nociplastic pain or CS in endometriosis patients. Information was extracted on study demographics, assessment types, and the tools used for detection. Of the 379 citations retrieved, 30 papers met the inclusion criteria. When working to identify CS and nociplastic pain, fourteen studies exclusively used patient-reported questionnaires, six used quantitative sensory testing (QST), two used clinical assessments, and eight used multiple approaches combining patient-reported questionnaires and clinical assessment. This review illustrates the diversity of tools currently used to identify CS and nociplastic pain in endometriosis patients. Further research is needed to evaluate their validity and to standardize methods in order to improve the accuracy of nociplastic pain identification and guide treatment.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".