Evidence map›Paper›PMID 39917657›Full record

ArticleFrontiers in dental medicine2024

Identifying early permanent teeth caries factors in children using random forest algorithm.

Fatemeh Masaebi, Zahra Ghorbani, Mehdi Azizmohammad Looha, Marzie Deghatipour, Morteza Mohammadzadeh, Mitra Ghazizadeh Ahsaie, Fariba Asadi, Farid Zayeri

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Article in Frontiers in dental medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Fatemeh MasaebiDepartment of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Zahra GhorbaniDepartment of Community Oral Health, Dental School, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mehdi Azizmohammad LoohaBasic and Molecular Epidemiology of Gastrointestinal Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Marzie DeghatipourDepartment of Community Oral Health, Dental School, Zahedan University of Medical Sciences, Zahedan, Iran.
Morteza MohammadzadehDepartment of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Mitra Ghazizadeh AhsaieDepartment of Oral and Maxillofacial Radiology, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Fariba AsadiDepartment of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farid ZayeriProteomics Research Center and Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Early permanent dental caries can pose a serious threat to oral health in the coming years. This study aimed to investigate the key factors influencing early dental caries in permanent teeth among first-grade Iranian children. Methods: A cross-sectional study involving 778 randomly selected first-grade children from public schools in Tehran, Iran, was conducted between November 2017 and January 2018. The oral health of the children, evaluated by two trained dentists, was recorded based on the DMFT index. Information on maternal education, gender, dmft index, brushing frequency, dental visits, flossing, and sweet consumption was also collected. The Random Forest method was employed to identify factors associated with early permanent dental caries, and its performance was compared with logistic regression using the Area Under the Curve (AUC) index. Results: Logistic regression, represented by odds ratios (OR), revealed a significant association between early permanent dental caries and dmft index [OR = 1.13, 95% CI (1.07, 1.20), p-value <0.001], maternal education [OR = 2.04, 95% CI (1.15, 3.62), p-value <0.05], and sweet consumption [OR = 0.59, 95% CI (0.36, 0.98), p-value <0.05]. Random Forest analysis indicated that male gender, higher maternal education, and lower sweet consumption were associated with increased likelihood of being caries-free. Notably, Random Forest demonstrated superior performance (AUC = 0.81) compared to logistic regression (AUC = 0.72). Conclusion: Early permanent dental caries can be effectively managed by caring primary teeth and reducing consumption of sweets. Maternal education emerged as a pivotal factor in mitigating the risk of early permanent dental caries. Therefore, prioritizing these factors and preventing permanent teeth caries in childhood can be remarkably influential in reducing future caries. The usage of the Random Forest algorithm is highly recommended for identifying relevant risk factors associated with early permanent teeth.

Indexed as

dental cariesDMFT indexlogistic regressionpermanent teethrandom forest

Identifiers

PMID39917657
PMCPMC11797793

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.