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Record W3158091781 · doi:10.18521/ktd.834163

Alexithymia And Behçet’s Disease

2021· article· en· W3158091781 on OpenAlexaboutno aff
Munise Daye, İnci Mevlitoğlu, Mine Şahingöz, Tahir Kemal Şahin

Bibliographic record

VenueKonuralp Tıp Dergisi · 2021
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsBehcet's diseaseAlexithymiaMedicineDiseaseDermatologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Objective: Behçet’s Disease (BD) is an immunoinflammatory systemic disease. In young adults, it is seen as genital ulceration, uveitis and oral aphthae. In some patients, BD may affect the central nervous system and some psychiatric symptoms may accompany this disease. There are few studies in the literature evaluating the relationship between BD and alexithymia. In this study, the relationship between BD and alexithymia is evaluated. Methods: Fifty patients diagnosed according to the International Study Group for Behçet’s Disease diagnostic criteria and fifty age and gender-matched healthy individuals were included in the study. Turkish versions of Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), and Toronto Alexithymia Scale (TAS-20) were applied to the patients and controls. Results: According to the TAS-20 scale, alexithymia was classified as: non-alexithymia, moderate and severe alexithymia. In the classification of TAS, there was a significant difference between the cases and the control group (p = 0.019).In patients with BD, alexithymia was 6 times higher than control group (OR = 6.139)(95% CI = 1,657-23.913). Conclusions: Behçet’s disease is strongly associated with alexithymia. Recognizing of these psychiatric symptoms is important for the management of BD patients. Psychotherapeutic interventions should be planned by dermatologists.

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)0.000
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 score0.029
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.271
Teacher spread0.256 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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