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Record W2026380842 · doi:10.1016/j.ijgo.2013.07.033

Biopsychosocial correlates of persistent postsurgical pain in women with endometriosis

2013· article· en· W2026380842 on OpenAlexaboutno aff
Erin T. Carey, Caitlin E. Martin, Matthew T. Siedhoff, Eric Bair, Sawsan As‐Sanie

Bibliographic record

VenueInternational Journal of Gynecology & Obstetrics · 2013
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBiopsychosocial modelEndometriosisPhysical therapyPelvic painGynecologyPsychiatrySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine pain and biopsychosocial correlates over time for women with persistent postsurgical pain after surgery for endometriosis. METHODS: Cross-sectional study of women who underwent any endometriosis surgery between 2003 and 2006. Following surgery, patients completed validated questionnaires (Short-Form McGill Pain Questionnaire, 12-item Short-Form Health Survey, Beck Depression Inventory, Coping Strategies Questionnaire catastrophizing subscale). The primary outcome was pelvic pain intensity, measured by the McGill total pain score. Bivariate comparisons between each potential predictor and pain intensity were performed using the χ(2) and t tests, 1-way analysis of variance, and simple linear regression. RESULTS: In total, 79 completed the questionnaires and were included in the present analysis. The McGill affective pain score was negatively correlated with age (β-coefficient -0.12, P=0.002) and positively correlated with catastrophization (β-coefficient 0.66, P=0.01). Women with a history of dyspareunia scored significantly higher on the McGill total pain score (P<0.001); there was no association between pain intensity and endometriosis severity. CONCLUSION: Younger age and catastrophization are correlated with persistent pain following surgery for endometriosis. The severity of endometriosis does not predict persistent pain. Further evaluation of psychosocial factors may identify patients who are least likely to benefit from surgeries for endometriosis-associated pelvic pain.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.282
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations77
Published2013
Admission routes1
Has abstractyes

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