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Record W4307864283 · doi:10.34172/thj.2022.21

Prevalence of Mucosal Lesions in People Consuming Chewable Tobacco in Hormozgan Province, Iran

2022· article· en· W4307864283 on OpenAlexaff
Raziyehsadat Rezvaninejad, Rayehehossadat Rezvaninejad, Abdolah Azdanesh, MohammadHosein Sheybani‐Arani, Ali Salimi Asl, Mohammad Ali Vahidipour, Mahsa Moannaei

Bibliographic record

VenueTobacco and Health · 2022
Typearticle
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineChewing tobaccoLesionPouchOral mucosaDentistryPathologySurgeryInternal medicineCancer

Abstract

fetched live from OpenAlex

Background: Tobacco has a high level of carcinogenic components. The maximum effect of the component is on the oral cavity and the location of tobacco. Quantitative studies were conducted according to the oral effect of tobacco usage by people of the south of Iran, specifically in Hormozgan province. In this experiment, the prevalence of oral lesions was studied in people who use tobacco in Hormozgan province in 2018. Materials and Methods: In this descriptive cross-sectional study, 395 patients were examined on oral lesions in Hormozgan province. Data were collected and described by a mean frequency table and then analyzed by an inferential statistical test such as the 2-dimensional chi-square test by SPSS, version 23 (P<0.05). Results: Experiments showed that 75.5% (299 from 395) of patients had mucosal lesions. The most lesions were tobacco pouch, wound, white plaque, and erythematic lesions. In addition, a significant correlation was found among parameters, including all mucosal lesions with time, all mucosal lesions with age (except wound), white plaque and erythematic mucosal lesions with smoking, tobacco pouch, and white plaque with alcohol use. However, no significant correlation was observed between oral mucosal lesions with a history of family oral lesions, tobacco pouch and wound with cigarette usage, and wound and erythematic lesions with alcohol use. Conclusion: Compared with other studies, oral mucosal lesions were highly prevalent in Hormozgan province. The possibility of oral mucosal lesions increases as one gets older; in addition, the duration of tobacco usage is a primary factor for the lesions.

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 score0.036
Threshold uncertainty score0.998

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 studies0.0000.000
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 head0.051
GPT teacher head0.346
Teacher spread0.295 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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