Monitoring of caries disease by risk assessments and activity

Development of short forms for screening children's dental caries and urgent treatment needs using item response theory and machine learning methods

OBJECTIVES

Surveys can assist in screening oral diseases in populations to enhance the early detection of disease and intervention strategies for children in need. This paper aims to develop short forms of child-report and proxy-report survey screening instruments for active dental caries and urgent treatment needs in school-age children.

METHODS

This cross-sectional study recruited 497 distinct dyads of children aged 8-17 and their parents between 2015 to 2019 from 14 dental clinics and private practices in Los Angeles County. We evaluated responses to 88 child-reported and 64 proxy-reported oral health questions to select and calibrate short forms using Item Response Theory. Seven classical Machine Learning algorithms were employed to predict children's active caries and urgent treatment needs using the short forms together with family demographic variables. The candidate algorithms include CatBoost, Logistic Regression, K-Nearest Neighbors (KNN), Naïve Bayes, Neural Network, Random Forest, and Support Vector Machine. Predictive performance was assessed using repeated 5-fold nested cross-validations.

RESULTS

We developed and calibrated four ten-item short forms. Naïve Bayes outperformed other algorithms with the highest median of cross-validated area under the ROC curve. The means of best testing sensitivities and specificities using both child-reported and proxy-reported responses were 0.84 and 0.30 for active caries, and 0.81 and 0.31 for urgent treatment needs respectively. Models incorporating both response types showed a slightly higher predictive accuracy than those relying on either child-reported or proxy-reported responses.

CONCLUSIONS

The combination of Item Response Theory and Machine Learning algorithms yielded potentially useful screening instruments for both active caries and urgent treatment needs of children. The survey screening approach is relatively cost-effective and convenient when dealing with oral health assessment in large populations. Future studies are needed to further leverage the customize and refine the instruments based on the estimated item characteristics for specific subgroups of the populations to enhance predictive accuracy.

Caries prevalence using ICDAS visual criteria and risk assessment in children and adolescents with cerebral palsy: A comparative study

AIMS

To compare the dental caries prevalence using the International Caries Detection and Assessment System (ICDAS) and the caries risk by Caries Management by Risk Assessment (CAMBRA) in individuals with cerebral palsy (CP) and normoactives (NAs).

METHODS AND RESULTS

Sixty children and adolescents aged 6-12 years (30 CP/30 NA) were clinically evaluated by one calibrated examiner using two-digit ICDAS criteria and converted into components of dmf/DMF indices: d2mf2/D2MF2 (enamel and dentin lesions) and d3mf3/D3MF3 (dentin lesions). An adapted CAMBRA was used for risk classification. The mean d2mf2s/d2mf2t and D2MF2S/D2MF2T for CP were 17.0 ± 16.8/7.5 ± 4.3 and 10.7 ± 17.6/5.3 ± 5.8, respectively, and for NA were 17.2 ± 16.9 /6.9 ± 4.8 and 11.1 ± 11.7/5.5 ± 4.7, respectively. The mean d3mf3s/d3mf3t and D3MF3S/D3MF3T for CP were 10.1 ± 16.7/3.0 ± 4.1 and 4.9 ± 15.6/0.2 ± 0.4, respectively, while for NA the mean values were 9.8 ± 13.0/3.5 ± 3.8 and 2.1 ± 5.7/0.9 ± 2.0, respectively. There were no statistically differences for caries prevalence and risk in both groups (p > 0.05).

CONCLUSIONS

Dental caries was highly prevalent in CP and NA children and adolescents. Enamel and dentin lesions and high caries risk were the most common condition.