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Record W4322732518 · doi:10.1038/s41405-023-00137-9

The association between erosive toothwear and asthma – is it significant? A meta-analysis

2023· article· en· W4322732518 on OpenAlexaboutno aff
Gowri Sivaramakrishnan, Kannan Sridharan, Muneera Alsobaiei

Bibliographic record

VenueBDJ Open · 2023
Typearticle
Languageen
FieldDentistry
TopicDental Erosion and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsFunnel plotMedicineMeta-analysisAsthmaPublication biasStudy heterogeneityInhalerSample size determinationStatisticConfoundingMEDLINEForest plotDentistryInternal medicineStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: The association of asthma with oral conditions such as dental caries, dental erosion, periodontal diseases and oral mucosal changes has been the subject of debate among dental practitioners. Existing evidence indicates that an inhaler is the most common and effective way of delivering the asthma medications directly into the lungs. Few studies in the past attributed this association to the changes in salivary flow caused due to these medications. Considering this unclear association, the aim of the present meta-analyses is to identify the association between erosive toothwear and asthma from individual studies conducted until date. METHODOLOGY: Electronic databases were systematically searched until 30th September 2022. Articles identified using the search strategy were imported to RAYYAN systematic review software. Data was extracted relating to study design, geographic location, year of publication, sample size, the assessment method for erosive toothwear and asthma. The Newcastle Ottawa scale was utilized to assess the quality of evidence reported from the included studies. RevMan Version 5.3 was used to perform a random-effects meta-analysis to produce pooled estimates from OR and 95% CI of included studies. The I² statistic was used to determine the extent of heterogeneity. A funnel plot was generated to visually assess the potential for publication bias. Sensitivity analyses were performed by excluding individual studies one at a time. GRADE approach was used for grading the evidence for key comparisons. RESULTS: Twelve articles were included in the final meta-analysis. A total of 1027 asthmatics and 5617 non-asthmatics were included. All studies demonstrated moderate to low risk of bias. The overall pooled estimate (OR: 2.03; 95% CI: 0.96, 4.29) and subgroup analyses in children (OR: 1.67; 95% CI: 0.63, 4.42) did not show statistically significant difference in the occurrence of dental erosion between the asthmatic and non-asthmatic group. However, asthmatic adults had significantly greater dental erosion in comparison to the control adults (OR: 2.76; 95% CI: 1.24, 6.16). Sensitivity analyses also provided inconclusive evidence. Funnel plot asymmetry indicated significant heterogeneity, changes in effect size and selective publication. CONCLUSION: The association between inhalational asthmatic medication and tooth wear is inconclusive. There are a number of confounding factors that play a greater role in causing dental erosion in these patients. Dentist must pay particular attention to these factors while treating asthmatic patients. The authors produce a comprehensive checklist in order to ensure complete assessment before providing advice on their medications alone.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.043
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.043
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0240.082
Bibliometrics0.0090.008
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.133
GPT teacher head0.373
Teacher spread0.240 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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

Citations5
Published2023
Admission routes1
Has abstractyes

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