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Clinical Pain Perception and Hormone Replacement Therapy in Postmenopausal Women Experiencing Orofacial Pain

2000· article· en· W2024556975 on OpenAlexaboutno aff
Emily A. Wise, Joseph L. Riley, Michael E. Robinson

Bibliographic record

VenueClinical Journal of Pain · 2000
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
FundersNational Institute of Dental and Craniofacial Research
KeywordsMedicineMenopausePhysical therapyHormone replacement therapy (female-to-male)McGill Pain QuestionnaireHysterectomyPostmenopausal womenChronic painVisual analogue scaleInternal medicineSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to examine the magnitude of the relation between a postmenopausal woman's hormonal replacement status and clinical pain report in a sample of women experiencing orofacial pain. DESIGN: To accomplish this, pain ratings were collected during a routine chronic pain evaluation at an orofacial pain clinic from a sample of 87 postmenopausal women. RESULTS: Results of ANCOVA (controlling for pain duration) demonstrated that postmenopausal women receiving hormone replacement therapy (HRT) reported higher levels of pain than postmenopausal women not taking HRT. Numeric pain rating scales revealed large effect sizes for worst pain report (0.62), moderate differences for average (0.48) and current (0.39) pain levels, and trivial differences for least pain (0.04). Effect sizes for the McGill Pain Questionnaire indicated somewhat smaller differences (0.35-0.24) between the two groups. CONCLUSIONS: This study is among the first to examine the relation between a woman's hormonal status and clinical pain perception and is the first to investigate the role of HRT in a postmenopausal woman's orofacial pain report in a clinical treatment setting. This area of inquiry is particularly salient given the high percentage of women who choose to initiate HRT either after hysterectomy or with the onset of menopause.

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)0.048
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0480.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.417
Teacher spread0.349 · 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

Citations59
Published2000
Admission routes1
Has abstractyes

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