MétaCan
Menu
Back to cohort
Record W4387704158 · doi:10.7759/cureus.47162

Occurrence of Oral Premalignant Lesions Among Tobacco Users in a Tribal Population: A Systematic Review and Meta-Analysis

2023· review· en· W4387704158 on OpenAlexaboutno aff
Bhavana Gupta, Anish Kumar Gupta, Neha Singh, R. B. Singh, Vivek Gupta

Bibliographic record

VenueCureus · 2023
Typereview
Languageen
FieldDentistry
TopicOral Health Pathology and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychological interventionEnvironmental healthPopulationSystematic reviewMeta-analysisPublic healthOdds ratioFamily medicineMEDLINEPathologyNursing

Abstract

fetched live from OpenAlex

This review aimed to comprehensively assess the association between tobacco use and oral health outcomes, specifically the presence of premalignant lesions (PMLs), through a synthesis of multiple assessments conducted in diverse populations. A systematic search of relevant literature was performed, and studies meeting the inclusion criteria were selected using appropriate Medical Subject Headings (MeSH) words and Boolean operators. Data from these studies was pooled and analysed using Review Manager 5.4 (The Cochrane Collaboration, The Nordic Cochrane Centre, Copenhagen). The Newcastle-Ottawa scale was used to assess the methodological quality of the studies included. The pooled analysis of the five selected papers revealed a significant correlation between tobacco use and an increased prevalence of PMLs among tobacco users. Tobacco users had an odds ratio of 15.22 (95% CI: 10.01-23.15) as compared to non-user cohorts, significant at p 0.0001. This comprehensive synthesis of assessments underscores the detrimental impact of tobacco use on oral health, particularly in terms of potentially malignant lesions. The findings emphasise the urgency of targeted public health interventions to address tobacco consumption and promote oral health awareness, especially in populations with high tobacco consumption rates. Standardisation of methodologies and representation of diverse populations in future research would strengthen the evidence base and facilitate more effective strategies to improve oral health outcomes globally.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.002
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 head0.285
GPT teacher head0.459
Teacher spread0.175 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCureusSame topicOral Health Pathology and TreatmentFrench-language works237,207