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Record W2346601207 · doi:10.5539/gjhs.v9n1p82

Lack of Relationship between Oral Lichen Planus and Hepatitis B and C Virus Infection: A Report from Southeast of Iran

2016· article· en· W2346601207 on OpenAlexvenueno aff
Tahereh Nosratzehi, Mehrab Raiesi, Bahareh Shahryari

Bibliographic record

VenueGlobal Journal of Health Science · 2016
Typearticle
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsOral lichen planusMedicineHepatitis C virusHepatitis B virusEtiologyAntibodyHepatitis BAntigenHepatitisInternal medicineHepatitis CVirusImmunologyGastroenterology

Abstract

fetched live from OpenAlex

<p>Oral lichen planus (OLP) is a chronic autoimmune disease with an unknown etiology. Dentists are usually the first medical practitioner to diagnose this condition. The condition affects all the body parts including the oral mucosa. Several studies have reported a relation between the OLP and hepatitis B and C. Current work aimed to define the occurrence of hepatitis B virus (HBV) antigen and hepatitis C virus (HCV) antibody in OLP patients compared with healthy controls. In this case-control study, 50 patients with clinical and histopathological characteristics of OLP, as well as 50 healthy controls were studied. Both groups were similar in terms of age and sex. Serum samples (5 mL) were collected from the patients for the evaluation of HBV antigen and HCV antibody using ELISA technique. Data were analyzed using SPSS Software, version 21. Chi-square test was used as appropriated. In present study, 50 patients with OLP (33 females and 17 males) with mean age of 42 ± 14.5 years, and 50 healthy subjects (33 females and 17 males) with mean age of 41.88 ± 13.73 years were evaluated. HBV antigen and HCV antibody were detected in none of the subjects (P > 0.05). We didn't found any relation between OLP and viral hepatitis. This may be due to lower occurrence of hepatitis viruses in comparison to hyper endemic countries for these viruses or genotypic discrepancy of the viruses or other factors contributing for these patients.</p>

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 score0.007
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.124
GPT teacher head0.412
Teacher spread0.288 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicOral Health Pathology and TreatmentFrench-language works237,207