ArticleBMC oral health2021
Salivary cystatin S levels in children with early childhood caries in comparison with caries-free children; statistical analysis and machine learning.
Article in BMC oral health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Assessment of proteomic salivary biomarkers for diagnosis of early childhood caries: a systematic review.Frontiers in oral health · 2025Pooled it
- Genetic evidence for causal link between systemic inflammation and dental caries risk: A bidirectional Mendelian randomization study.Medicine · 2026Article
- Artificial Intelligence Applications in Pediatric Dentistry: A Comprehensive Review.Biomimetics (Basel, Switzerland) · 2026Review
- Accuracy, quality, and readability analyses of responses from large language models to questions on pediatric dental sedation.BMC oral health · 2026Article
- Assessing the willingness of Nigerian dentists to adopt salivary diagnostic kits: a pilot cross-sectional study.BMC oral health · 2026Article
- CST4 promotes EMT and tumor progression in ovarian cancer via Wnt/β-catenin signaling.Discover oncology · 2026Article
- Metabolic profiling of severe early childhood caries and black stain: pathway and biomarker discovery in 3-6-year-olds.Frontiers in molecular biosciences · 2026Article
- Comparison of salivary statherin and beta-defensin-2 levels, oral health behaviors, and demographic factors in children with and without early childhood caries.BMC oral health · 2025Article
- Review
- The Implications of Artificial Intelligence in Pedodontics: A Scoping Review of Evidence-Based Literature.Healthcare (Basel, Switzerland) · 2024Article
- Empowering Modern Dentistry: The Impact of Artificial Intelligence on Patient Care and Clinical Decision Making.Diagnostics (Basel, Switzerland) · 2024Review
- Research and application of artificial intelligence in dentistry from lower-middle income countries - a scoping review.BMC oral health · 2024Article
- Artificial Intelligence Its Uses and Application in Pediatric Dentistry: A Review.Biomedicines · 2023Review
- Comparison of oral cavity protein abundance among caries-free and caries-affected individuals-a systematic review and meta-analysis.Frontiers in oral health · 2023Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEarly childhood caries is the most common infectious disease in childhood, with a high prevalence in developing countries. The assessment of the variables that influence early childhood caries as well as its pathophysiology leads to improved control of this disease. Cystatin S, as one of the salivary proteins, has an essential role in pellicle formation, tooth re-mineralization, and protection. The present study aims to assess salivary cystatin S levels and demographic data in early childhood caries in comparison with caries-free ones using statistical analysis and machine learning methods.
methodsA cross-sectional, case-control study was undertaken on 20 cases of early childhood caries and 20 caries-free children as a control. Unstimulated whole saliva samples were collected by suction. Cystatin S concentrations in samples were determined using human cystatin S ELISA kit. The checklist was collected from participants about demographic characteristics, oral health status, and dietary habits by interviewing parents. Regression and receiver operating characteristic (ROC) curve analysis were done to evaluate the potential role of cystatin S salivary level and demographic using statistical analysis and machine learning.
resultsThe mean value of salivary cystatin S concentration in the early childhood caries group was 191.55 ± 81.90 (ng/ml) and in the caries-free group was 370.06 ± 128.87 (ng/ml). T-test analysis showed a statistically significant difference between early childhood caries and caries-free groups in salivary cystatin S levels (p = 0.032). Investigation of the area under the curve (AUC) and accuracy of the ROC curve revealed that the logistic regression model based on salivary cystatin S levels and birth weight had the most and acceptable potential for discriminating of early childhood caries from caries-free controls. Furthermore, using salivary cystatin S levels enhanced the capability of machine learning methods to differentiate early childhood caries from caries-free controls.
conclusionSalivary cystatin S levels in caries-free children were higher than the children with early childhood caries. Results of the present study suggest that considering clinical examination, demographic and socioeconomic factors, along with the salivary cystatin S levels, could be usefull for early diagnosis ofearly childhood caries in high-risk children; furthermore, cystatin S is a protective factor against dental caries.
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