Dataset Information

How combining different caries lesions characteristics may be helpful in short-term caries progression prediction: model development on occlusal surfaces of primary teeth.

ABSTRACT:

Background

Few studies have addressed the clinical parameters' predictive power related to caries lesion associated with their progression. This study assessed the predictive validity and proposed simplified models to predict short-term caries progression using clinical parameters related to caries lesion activity status.

Methods

The occlusal surfaces of primary molars, presenting no frank cavitation, were examined according to the following clinical predictors: colour, luster, cavitation, texture, and clinical depth. After one year, children were re-evaluated using the International Caries Detection and Assessment System to assess caries lesion progression. Progression was set as the outcome to be predicted. Univariate multilevel Poisson models were fitted to test each of the independent variables (clinical features) as predictors of short-term caries progression. The multimodel inference was made based on the Akaike Information Criteria and C statistic. Afterwards, plausible interactions among some of the variables were tested in the models to evaluate the benefit of combining these variables when assessing caries lesions.

Results

205 children (750 surfaces) presented no frank cavitations at the baseline. After one year, 147 children were reassessed (70%). Finally, 128 children (733 surfaces) presented complete baseline data and had included primary teeth to be reassessed. Approximately 9% of the reassessed surfaces showed caries progression. Among the univariate models created with each one of these variables, the model containing the surface integrity as a predictor had the lowest AIC (364.5). Univariate predictive models tended to present better goodness-of-fit (AICs < 388) and discrimination (C:0.959-0.966) than those combining parameters (AIC:365-393, C:0.958-0.961). When only non-cavitated surfaces were considered, roughness compounded the model that better predicted the lesions' progression (AIC = 217.7, C:0.91).

Conclusions

Univariate model fitted considering the presence of cavitation show the best predictive goodness-of-fit and discrimination. For non-cavitated lesions, the simplest way to predict those lesions that tend to progress is by assessing enamel roughness. In general, the evaluation of other conjoint parameters seems unnecessary for all non-frankly cavitated lesions.

SUBMITTER: Floriano I

PROVIDER: S-EPMC8117278 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Dental caries is the most prevalent disease in humans globally. Efforts to control it have been invigorated by an increasing knowledge of the oral microbiome composition. This study aimed to evaluate the bacterial diversity in occlusal biofilms and its relationship with clinical surface diagnosis and dietary habits. Anamneses were recorded from thirteen 12-year-old children. Biofilm samples collected from occlusal surfaces of 46 permanent second molars were analyzed by 16S rRNA amplicon sequencing combined with the BLASTN-based search algorithm for species identification. The overall mean decayed, missing and filled surfaces modified index [DMFSm Index, including active white spot lesions (AWSL)] value was 8.77±7.47. Biofilm communities were highly polymicrobial collectively, representing 10 bacterial phyla, 25 classes, 29 orders, 58 families, 107 genera, 723 species. Streptococcus sp_Oral_Taxon_065, Corynebacterium matruchotii, Actinomyces viscosus, Actinomyces sp_Oral_Taxon_175, Actinomyces sp_Oral_Taxon_178, Actinomyces sp_Oral_Taxon_877, Prevotella nigrescens, Dialister micraerophilus, Eubacterium_XI G 1 infirmum were more abundant among surfaces with AWSL, and Streptococcus gordonii, Streptococcus sp._Oral_Taxon_058, Enterobacter sp._str._638 Streptococcus australis, Yersinia mollaretii, Enterobacter cloacae, Streptococcus sp._Oral_Taxon_71, Streptococcus sp._Oral_Taxon_F11, Centipeda sp._Oral_Taxon_D18 were more abundant among sound surfaces. Streptococcus mutans was detected on all surfaces in all patients, while Streptococcus sobrinus was detected only in three patients (mean relative abundances 7.1% and 0.6%, respectively). Neither species differentiated healthy from diseased sites. Diets of nine of the subjects were scored as high in fermentable carbohydrates (?2X/day between meals). A direct association between relative abundances of bacteria and carbohydrate consumption was observed among 18 species. High consumption of fermentable carbohydrates and sound surfaces were associated with a reduction in bacterial diversity. PCoA plots displayed differences in bacterial community profiles between sound and diseased surfaces. Our study showed that, in addition to mutans streptococci, other species may be associated with the initiation of dental caries on occlusal surfaces, and that biofilm diversity of tooth surfaces is influenced by carbohydrate consumption and a surface's health status.

Project description:The purpose of this study was to compare the performance of two different models of smartphone and a conventional camera with that of direct clinical examination in detecting caries lesions at different stages of progression in deciduous molars. The photographic equipment consisted of two smartphones (iPhone and Nexus 4) and a conventional macro camera setup. First, in the laboratory phase of the study, we compared the images of 20 exfoliated primary teeth having caries lesions at different stages. Then, in the clinical phase of the study, the images of 119 primary molars from fifteen children (3 to 6 years old) were used. All of the photographic images were taken using the previously described devices. In both groups, two examiners, blinded to the photographic equipment used, assessed the images independently on a computer screen, and classified them according to the International Caries Detection and Assessment System (ICDAS). The teeth were then examined directly by two other experienced examiners, and the consensus reached was considered the reference standard. Parameters of validity, such as percentage of correct answers, agreement with the reference standard, sensitivity, specificity and inter-examiner agreement (using the weighted kappa test) were calculated. The examiners performed similarly in both in vitro and in vivo studies. Inter-examiner reliability was approximately 0.7 for all the devices in the laboratory setting, and for the macro camera photography system in the clinical setting, but it was approximately 0.9 for the iPhone and Nexus images taken in vivo. With regard to the percentage of correct answers, the highest values were observed for sound and extensive caries lesions in both laboratory and clinical settings. The percentage of correct answers for initial and moderate lesions was particularly low in the clinical evaluation, irrespective of the camera devices used. Therefore, we concluded that photographic diagnosis using smartphone images is feasible and accurate for distinguishing sound tooth surfaces from extensive caries lesions; however, photographic images are not a good method for accurately detecting initial and moderate caries lesions.