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Record W4392143381 · doi:10.4240/wjgs.v16.i2.585

Poor oral health was associated with higher risk of gastric cancer: Evidence from 1431677 participants

2024· article· en· W4392143381 on OpenAlex
Fei Liu, Shi-Jun Tang, Ziwei Li, Xu‐Rui Liu, Quan Lv, Wei Zhang, Dong Peng

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Journal of Gastrointestinal Surgery · 2024
Typearticle
Languageen
FieldDentistry
TopicOral microbiology and periodontitis research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOdds ratioFunnel plotConfidence intervalIncidence (geometry)PeriodontitisGingivitisSubgroup analysisInternal medicineCohort studyRelative riskMeta-analysisPublication biasDentistry

Abstract

fetched live from OpenAlex

BACKGROUND In recent years, the association between oral health and the risk of gastric cancer (GC) has gradually attracted increased interest. However, in terms of GC incidence, the association between oral health and GC incidence remains controversial. Periodontitis is reported to increase the risk of GC. However, some studies have shown that periodontitis has no effect on the risk of GC. Therefore, the present study aimed to assess whether there is a relationship between oral health and the risk of GC. AIM To assess whether there was a relationship between oral health and the risk of GC. METHODS Five databases were searched to find eligible studies from inception to April 10, 2023. Newcastle-Ottawa Scale score was used to assess the quality of included studies. The quality of cohort studies and case-control studies were evaluated separately in this study. Incidence of GC were described by odds ratio (OR) and 95% confidence interval (CI). Funnel plot was used to represent the publication bias of included studies. We performed the data analysis by StataSE 16. RESULTS A total of 1431677 patients from twelve included studies were enrolled for data analysis in this study. According to our analysis, we found that the poor oral health was associated with higher risk of GC (OR = 1.15, 95%CI: 1.02-1.29; I 2 = 59.47%, P = 0.00 < 0.01). Moreover, after subgroup analysis, the outcomes showed that whether tooth loss (OR = 1.12, 95%CI: 0.94-1.29; I 2 = 6.01%, P > 0.01), gingivitis (OR = 1.19, 95%CI: 0.71-1.67; I 2 = 0.00%, P > 0.01), dentures (OR = 1.27, 95%CI: 0.63-1.19; I 2 = 68.79%, P > 0.01), or tooth brushing (OR = 1.25, 95%CI: 0.78-1.71; I 2 = 88.87%, P > 0.01) had no influence on the risk of GC. However, patients with periodontitis (OR = 1.13, 95%CI: 1.04-1.23; I 2 = 0.00%, P < 0.01) had a higher risk of GC. CONCLUSION Patients with poor oral health, especially periodontitis, had a higher risk of GC. Patients should be concerned about their oral health. Improving oral health might reduce the risk of GC.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.354
Teacher spread0.264 · 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