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Record W4390271334 · doi:10.7759/cureus.51139

Clinical Features and Variations of Pain Expressions in 834 Burning Mouth Syndrome Patients With or Without Psychiatric Comorbidities

2023· article· en· W4390271334 on OpenAlexaboutno aff
Chihiro Takao, Motoko Watanabe, Gayatri Nayanar, Trang Thi Huyen Tu, Yojiro Umezaki, Miho Takenoshita, Haruhiko Motomura, Takahiko Nagamine, Akira Toyofuku

Bibliographic record

VenueCureus · 2023
Typearticle
Languageen
FieldMedicine
TopicFibromyalgia and Chronic Fatigue Syndrome Research
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceTokyo Medical and Dental University
KeywordsMcGill Pain QuestionnaireMedicineDepression (economics)AnxietyBurning mouth syndromeRating scalePsychiatryChronic painComorbidityInternal medicinePhysical therapyVisual analogue scalePsychology

Abstract

fetched live from OpenAlex

Introduction Burning mouth syndrome (BMS) is characterized as chronic burning pain or unpleasant discomfort in the oral region without any corresponding clinical abnormalities. The aim of this study is to investigate the difference in clinical features and the variations of pain expressions between BMS patients with and without psychiatric comorbidities. Methodology The patients with BMS who first visited between April 2016 and March 2020 were involved and the clinical data including the presence of psychiatric comorbidities and scores of self-rating depression scale (SDS), pain catastrophizing scale (PCS), and pain quality from short-form McGill pain questionnaire (SF-MPQ) were collected retrospectively. Results In 834 patients with BMS (700 females, 63.9 ± 13.1 years old), 371 patients (44.5%) had psychiatric comorbidities. There was no significant between-group difference in demographic data. However, significantly higher scores were observed in SDS (p < 0.001) and PCS (p < 0.001) in the patients with psychiatric comorbidities. Moreover, the patients with psychiatric comorbidities showed significantly stronger pain intensity (p < 0.001) besides higher scores of each descriptor in SF-MPQ. In addition, they had chosen more descriptors in SF-MPQ (p < 0.001); furthermore, the number of selected pain descriptors showed a stronger correlation with PCS than with SDS regardless of the presence of psychiatric comorbidities. Conclusion BMS patients may complain of various pain expressions regardless of the psychiatric comorbidities; however, more severe complaints relating to high pain catastrophizing are more likely in patients with psychiatric comorbidities. These results suggested that underlying anxiety exacerbated the variety of pain expressions in BMS patients with psychiatric comorbidities.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.348
Teacher spread0.311 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2023
Admission routes1
Has abstractyes

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