This study aimed to review the current state of the root caries field, explore the current hot topic, and anticipate future research frontiers. The Web of Science Core Collections was searched to acquire publications that were relevant to root caries from 1992 to 2021. After retrieval and manual screening, the co-occurrence and co-operation analysis of keywords and countries/institutions/authors were performed through CiteSpace and VOSviewer based on two periods (1992-2006 and 2007-2021). From 1992 to 2021, 451 unique publications were selected. The USA, which has been the center of international cooperation, has produced the most publications in the research area in 1992-2021. Journal of Dental Research and Caries Research are the main counterpart journals in the field of root caries. The University of London is the institution with the highest number of publications in the analyzed 30 years. "Demineralization," "remineralization," "aged," "dentin," and "fluoride" have been commonly used as keywords throughout the past 30 years. More studies from different aspects have been published in the field of root caries in recent years (2007-2021). The findings of this study provide a full picture of the last 30 years in this research area; hopefully, they also provide essential information for researchers and policymakers to make decisions.
本研究旨在回顾牙根龋病的研究现状，探讨当前的热点问题，并展望未来的研究前沿。检索Web of Science核心馆藏，获取1992年至2021年与牙根龋相关的出版物。通过检索和人工筛选，通过CiteSpace和VOSviewer对1992-2006年和2007-2021年两个时间段的关键词与国家/机构/作者进行共现合作分析。从1992年到2021年，评选出451种独特的出版物。1992-2021年，作为国际合作中心的美国在该研究领域发表的论文最多。《牙科研究杂志》和《龋齿研究》是牙根龋齿领域的主要对口期刊。在过去的30年里，伦敦大学是发表论文数量最多的大学。“脱矿”、“再矿化”、“老化”、“牙本质”和“氟化物”在过去的30年里一直是常用的关键词。近年来(2007-2021)，在牙根龋领域有更多不同方面的研究发表。这项研究的结果提供了近30年来该研究领域的全貌;希望它们也能为研究人员和决策者做出决策提供必要的信息。
{"title":"A Bibliometric Analysis of Studies on Root Caries.","authors":"Mengzhen Ji, Di Fu, Ga Liao, Ling Zou","doi":"10.1159/000529050","DOIUrl":"https://doi.org/10.1159/000529050","url":null,"abstract":"<p><p>This study aimed to review the current state of the root caries field, explore the current hot topic, and anticipate future research frontiers. The Web of Science Core Collections was searched to acquire publications that were relevant to root caries from 1992 to 2021. After retrieval and manual screening, the co-occurrence and co-operation analysis of keywords and countries/institutions/authors were performed through CiteSpace and VOSviewer based on two periods (1992-2006 and 2007-2021). From 1992 to 2021, 451 unique publications were selected. The USA, which has been the center of international cooperation, has produced the most publications in the research area in 1992-2021. Journal of Dental Research and Caries Research are the main counterpart journals in the field of root caries. The University of London is the institution with the highest number of publications in the analyzed 30 years. \"Demineralization,\" \"remineralization,\" \"aged,\" \"dentin,\" and \"fluoride\" have been commonly used as keywords throughout the past 30 years. More studies from different aspects have been published in the field of root caries in recent years (2007-2021). The findings of this study provide a full picture of the last 30 years in this research area; hopefully, they also provide essential information for researchers and policymakers to make decisions.</p>","PeriodicalId":9620,"journal":{"name":"Caries Research","volume":"57 1","pages":"32-42"},"PeriodicalIF":4.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9279947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01Epub Date: 2023-09-06DOI: 10.1159/000533721
Fatemeh Eskandari, Elizabeth Adjoa Kumah, Liane Azevedo, John Stephenson, Sherley John, Fatemeh Vida Zohoori
Due to practical difficulties in quantifying fluoride exposure in populations, practical and accurate biomarkers can play a major role in the surveillance of fluoride. Among different fluoride biomarkers, spot urine and nail clippings have gained more attention due to their ease of acquisition. However, there is no robust consensus about the accuracy of these biomarkers for the estimation of fluoride exposure. This systematic review and meta-analysis aimed to synthesise evidence on the association between fluoride exposure and the fluoride concentration of spot urine and nail clippings. This review was conducted and reported using the PRISMA Statement. Nine databases (Medline, CINAHL, Web of Science, Scopus, ScienceDirect, Sage Journals Online, Campbell Collaboration, Cochrane Collaboration, and Embase); search engines (Google and Google Scholar); and grey literature were searched up to September 2022. All screening, data extraction, and quality assessments were conducted in duplicate. All experimental and observational research studies that reported the correlation between fluoride exposure and fluoride concentrations of spot urine and/or nail clippings were included. The Mixed-Methods Appraisal tool was used to assess the methodological quality of the included studies. A random effect meta-analysis was carried out to determine the relationship between fluoride exposure and fluoride concentration of biomarkers (i.e., spot urine and nail clippings). Forty-four studies met the inclusion criteria. A total of 694,578 participants were included in this review. Twenty-five studies were included in the meta-analysis. The primary meta-analysis showed a moderate correlation of 0.674 (95% confidence interval [CI]: 0.623-0.725, n = 25) between fluoride intake and fluoride concentration of spot urine and a strong correlation of 0.938 (95% CI: 0.520-1.355, n = 11) between fluoride intake and the fluoride concentration of nail clippings in all age groups. The findings of secondary meta-analyses showed a strong positive correlation between fluoride intake and fluoride/creatinine ratio of spot urine in children (0.929; 95% CI: 0.502-0.991; n = 2). In conclusion, spot urine and nail clippings have the potential to be employed as non-invasively obtained biomarkers in populations. However, due to the scarcity of high quality, relevant studies, more research is needed to establish the validity of these biomarkers.
由于在人群中量化氟化物暴露的实际困难，实用和准确的生物标志物可以在氟化物监测中发挥重要作用。在不同的氟化物生物标志物中，斑点尿和指甲屑因其易于获取而受到更多关注。然而，对于这些生物标记物用于估计氟化物暴露的准确性，还没有强有力的共识。本系统综述和荟萃分析旨在综合氟化物暴露与斑尿和指甲剪中氟化物浓度之间关系的证据。该审查是使用PRISMA声明进行和报告的。9个数据库(Medline、CINAHL、Web of Science、Scopus、ScienceDirect、Sage Journals Online、Campbell Collaboration、Cochrane Collaboration和Embase);搜索引擎(谷歌和谷歌Scholar);和灰色文献被搜索到2022年9月。所有筛选、数据提取和质量评估均为一式两份。所有报告氟化物暴露与尿样和/或剪指甲的氟化物浓度之间存在相关性的实验和观察性研究都包括在内。使用混合方法评价工具评估纳入研究的方法学质量。通过随机效应荟萃分析确定氟暴露与生物标志物(即斑尿和指甲剪)氟浓度之间的关系。44项研究符合纳入标准。本综述共纳入694,578名受试者。荟萃分析纳入了25项研究。初步meta分析显示，各年龄组氟摄入量与斑尿氟浓度的相关性为0.674(95%可信区间[CI]: 0.623 ~ 0.725, n = 25)，氟摄入量与剪指甲氟浓度的相关性为0.938 (95% CI: 0.52 ~ 1.355, n = 11)。二级meta分析结果显示，氟摄入量与儿童斑尿氟/肌酐比值呈正相关(0.929;95% ci: 0.502-0.991;n = 2)。总之，尿斑和指甲剪报有潜力在人群中作为非侵入性获得的生物标志物。然而，由于缺乏高质量的相关研究，需要更多的研究来确定这些生物标志物的有效性。
{"title":"Fluoride Exposure in Community Prevention Programmes for Oral Health Using Nail Clippings and Spot Urine Samples: A Systematic Review and Meta-Analysis.","authors":"Fatemeh Eskandari, Elizabeth Adjoa Kumah, Liane Azevedo, John Stephenson, Sherley John, Fatemeh Vida Zohoori","doi":"10.1159/000533721","DOIUrl":"10.1159/000533721","url":null,"abstract":"<p><p>Due to practical difficulties in quantifying fluoride exposure in populations, practical and accurate biomarkers can play a major role in the surveillance of fluoride. Among different fluoride biomarkers, spot urine and nail clippings have gained more attention due to their ease of acquisition. However, there is no robust consensus about the accuracy of these biomarkers for the estimation of fluoride exposure. This systematic review and meta-analysis aimed to synthesise evidence on the association between fluoride exposure and the fluoride concentration of spot urine and nail clippings. This review was conducted and reported using the PRISMA Statement. Nine databases (Medline, CINAHL, Web of Science, Scopus, ScienceDirect, Sage Journals Online, Campbell Collaboration, Cochrane Collaboration, and Embase); search engines (Google and Google Scholar); and grey literature were searched up to September 2022. All screening, data extraction, and quality assessments were conducted in duplicate. All experimental and observational research studies that reported the correlation between fluoride exposure and fluoride concentrations of spot urine and/or nail clippings were included. The Mixed-Methods Appraisal tool was used to assess the methodological quality of the included studies. A random effect meta-analysis was carried out to determine the relationship between fluoride exposure and fluoride concentration of biomarkers (i.e., spot urine and nail clippings). Forty-four studies met the inclusion criteria. A total of 694,578 participants were included in this review. Twenty-five studies were included in the meta-analysis. The primary meta-analysis showed a moderate correlation of 0.674 (95% confidence interval [CI]: 0.623-0.725, n = 25) between fluoride intake and fluoride concentration of spot urine and a strong correlation of 0.938 (95% CI: 0.520-1.355, n = 11) between fluoride intake and the fluoride concentration of nail clippings in all age groups. The findings of secondary meta-analyses showed a strong positive correlation between fluoride intake and fluoride/creatinine ratio of spot urine in children (0.929; 95% CI: 0.502-0.991; n = 2). In conclusion, spot urine and nail clippings have the potential to be employed as non-invasively obtained biomarkers in populations. However, due to the scarcity of high quality, relevant studies, more research is needed to establish the validity of these biomarkers.</p>","PeriodicalId":9620,"journal":{"name":"Caries Research","volume":" ","pages":"197-210"},"PeriodicalIF":4.2,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10641804/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10523496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Front & Back Matter","authors":"A. Lussi, M. Buzalaf, D. Beighton","doi":"10.1159/000525642","DOIUrl":"https://doi.org/10.1159/000525642","url":null,"abstract":"","PeriodicalId":9620,"journal":{"name":"Caries Research","volume":" ","pages":""},"PeriodicalIF":4.2,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42062101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lilian Toledo Reyes, J. Knorst, F. R. Ortiz, T. Ardenghi
We performed a systematic review to evaluate the success of machine learning algorithms in the diagnosis and prognostic prediction of dental caries. The review protocol was a priori registered in the PROSPERO, CRD42020183447. The search involved electronic bibliographic databases: PubMed/Medline, Scopus, EMBASE, Web of Science, and grey literature until December 2020. We excluded review articles, case series, case reports, editorials, letters, comments, educational methodologies, assessments of robotic devices, and articles with less than 10 participants or specimens. Two independent reviewers selected the studies and performed the assessment of the methodological quality based on standardized scales. We summarize data on the machine learning algorithms used; software; performance outcomes such as accuracy/precision, sensitivity/recall, specificity, area under the receiver operating characteristic curve (AUC), and positive/negative predictive values related to dental caries. Meta-analyses were not performed due to methodological differences. Our review included 15 studies (10 diagnostic studies and 5 prognostic prediction studies). Cross-sectional design studies were predominant (12). The most frequently used statistical measure of performance reported in diagnostic studies was AUC value, which ranged from 0.745 to 0.987. For most diagnostic studies, data from contingency tables were not available. Reported sensitivities were higher in low risk of bias prognostic prediction studies (median [IQR] of 0.996 [0.971–1.000] vs. unclear/high risk of bias studies 0.189 [0–0.340]; p value 0.025). While there were no significant differences in the specificity between these subgroups, we concluded that the use of these technologies for the diagnosis and prognostic prediction of dental caries, although promising, is at an early stage. The general applicability of the evidence was limited given that most models were developed outside the real clinical setting with a prevalence of unclear/high risk of bias. Researchers must increase the overall quality of their research protocols by providing a comprehensive report on the methods implemented.
我们进行了一项系统综述，以评估机器学习算法在龋齿诊断和预后预测方面的成功。审查协议事先在PROSPERO CRD42020183447中登记。搜索涉及电子书目数据库：PubMed/Medline、Scopus、EMBASE、Web of Science和灰色文献，直到2020年12月。我们排除了综述文章、病例系列、病例报告、社论、信件、评论、教育方法、机器人设备评估以及参与者或样本少于10人的文章。两名独立评审员选择了这些研究，并根据标准化量表对方法学质量进行了评估。我们总结了所使用的机器学习算法的数据；软件性能结果，如准确性/精密度、敏感性/召回率、特异性、受试者工作特征曲线下面积（AUC）以及与龋齿相关的阳性/阴性预测值。由于方法学差异，未进行荟萃分析。我们的综述包括15项研究（10项诊断研究和5项预后预测研究）。横断面设计研究占主导地位（12）。诊断研究中报告的最常用的性能统计指标是AUC值，其范围为0.745至0.987。对于大多数诊断性研究，没有列联表中的数据。报道的敏感性在低偏倚风险预后预测研究中更高（中位数[IQR]为0.996[0.971–1.000]，而不清楚/高偏倚风险研究为0.189[0–0.340]；p值0.025）。虽然这些亚组之间的特异性没有显著差异，但我们得出结论，将这些技术用于龋齿的诊断和预后预测，尽管前景看好，但仍处于早期阶段。鉴于大多数模型是在真实临床环境之外开发的，且普遍存在不清楚/高偏倚风险，因此证据的普遍适用性有限。研究人员必须通过提供关于所实施方法的全面报告来提高研究方案的整体质量。
{"title":"Machine Learning in the Diagnosis and Prognostic Prediction of Dental Caries: A Systematic Review","authors":"Lilian Toledo Reyes, J. Knorst, F. R. Ortiz, T. Ardenghi","doi":"10.1159/000524167","DOIUrl":"https://doi.org/10.1159/000524167","url":null,"abstract":"We performed a systematic review to evaluate the success of machine learning algorithms in the diagnosis and prognostic prediction of dental caries. The review protocol was a priori registered in the PROSPERO, CRD42020183447. The search involved electronic bibliographic databases: PubMed/Medline, Scopus, EMBASE, Web of Science, and grey literature until December 2020. We excluded review articles, case series, case reports, editorials, letters, comments, educational methodologies, assessments of robotic devices, and articles with less than 10 participants or specimens. Two independent reviewers selected the studies and performed the assessment of the methodological quality based on standardized scales. We summarize data on the machine learning algorithms used; software; performance outcomes such as accuracy/precision, sensitivity/recall, specificity, area under the receiver operating characteristic curve (AUC), and positive/negative predictive values related to dental caries. Meta-analyses were not performed due to methodological differences. Our review included 15 studies (10 diagnostic studies and 5 prognostic prediction studies). Cross-sectional design studies were predominant (12). The most frequently used statistical measure of performance reported in diagnostic studies was AUC value, which ranged from 0.745 to 0.987. For most diagnostic studies, data from contingency tables were not available. Reported sensitivities were higher in low risk of bias prognostic prediction studies (median [IQR] of 0.996 [0.971–1.000] vs. unclear/high risk of bias studies 0.189 [0–0.340]; p value 0.025). While there were no significant differences in the specificity between these subgroups, we concluded that the use of these technologies for the diagnosis and prognostic prediction of dental caries, although promising, is at an early stage. The general applicability of the evidence was limited given that most models were developed outside the real clinical setting with a prevalence of unclear/high risk of bias. Researchers must increase the overall quality of their research protocols by providing a comprehensive report on the methods implemented.","PeriodicalId":9620,"journal":{"name":"Caries Research","volume":"56 1","pages":"161 - 170"},"PeriodicalIF":4.2,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48938042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Muñoz-Sandoval, K. Gambetta-Tessini, J. N. Botelho, R. Giacaman
Detection of proximal carious lesions involves the combination of clinical and radiographic methods, both with inherent difficulties. The present cross-sectional study is aimed at estimating the prevalence of cavitation in proximal carious lesions, based on a direct clinical assessment of previously detected radiographic lesions, in permanent molars and premolars. Proximal dental surfaces were radiographically evaluated using the ADA coding system and cavitation was determined through clinical visual examination of the surfaces after separation with elastomeric bands. One-hundred and twenty-six patients attending the dental clinics at the University of Talca were examined, comprising 508 proximal surfaces with radiographic codes ranging from E1 to D3. Two examiners were trained and calibrated for radiographic and clinical detection of proximal lesions. Most participants were females (61.9%). The age mean of participants was 28.7 (0.8) years old. A total of 22.2% of the examined surfaces were cavitated. Only few lesions coded as E1 (n = 4; 2.1%) and E2 (n = 9; 9.8%) were cavitated. Fifty D1 (35.5%) and 22 D2 (41.5%) lesions were cavitated after separation. Most lesions coded as D3 (n = 28; 84.8%) were cavitated. The multilevel binary regression model (p = 0.003) demonstrated that sex, age, jaw, tooth type, surface, and side were not associated with the likelihood of having proximal cavitation. Challenging conventional wisdom, most D1 and D2 lesions were not cavitated. Combining detection methods seems desirable to increase the accuracy in assessing approximal posterior lesions. The low proportion of cavitated lesions reinforces the idea of cautiously indicating invasive approaches for managing proximal carious lesions.
{"title":"Detection of Cavitated Proximal Carious Lesions in Permanent Teeth: A Visual and Radiographic Assessment","authors":"C. Muñoz-Sandoval, K. Gambetta-Tessini, J. N. Botelho, R. Giacaman","doi":"10.1159/000525193","DOIUrl":"https://doi.org/10.1159/000525193","url":null,"abstract":"Detection of proximal carious lesions involves the combination of clinical and radiographic methods, both with inherent difficulties. The present cross-sectional study is aimed at estimating the prevalence of cavitation in proximal carious lesions, based on a direct clinical assessment of previously detected radiographic lesions, in permanent molars and premolars. Proximal dental surfaces were radiographically evaluated using the ADA coding system and cavitation was determined through clinical visual examination of the surfaces after separation with elastomeric bands. One-hundred and twenty-six patients attending the dental clinics at the University of Talca were examined, comprising 508 proximal surfaces with radiographic codes ranging from E1 to D3. Two examiners were trained and calibrated for radiographic and clinical detection of proximal lesions. Most participants were females (61.9%). The age mean of participants was 28.7 (0.8) years old. A total of 22.2% of the examined surfaces were cavitated. Only few lesions coded as E1 (n = 4; 2.1%) and E2 (n = 9; 9.8%) were cavitated. Fifty D1 (35.5%) and 22 D2 (41.5%) lesions were cavitated after separation. Most lesions coded as D3 (n = 28; 84.8%) were cavitated. The multilevel binary regression model (p = 0.003) demonstrated that sex, age, jaw, tooth type, surface, and side were not associated with the likelihood of having proximal cavitation. Challenging conventional wisdom, most D1 and D2 lesions were not cavitated. Combining detection methods seems desirable to increase the accuracy in assessing approximal posterior lesions. The low proportion of cavitated lesions reinforces the idea of cautiously indicating invasive approaches for managing proximal carious lesions.","PeriodicalId":9620,"journal":{"name":"Caries Research","volume":"56 1","pages":"171 - 178"},"PeriodicalIF":4.2,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46290145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. L. Moro, L. R. Pontes, H. Maia, R. D. Freitas, T. Tedesco, D. Raggio, M. Braga, K. Ekstrand, J. Imparato, M. Cenci, F. Mendes
This is a delayed-type cross-sectional prospective accuracy study nested in a randomized clinical trial. The aim was to investigate the diagnostic accuracy of two visual criteria for caries lesions detection around restorations in primary teeth: the International Dental Federation (FDI) criteria, considering adaptation, staining, and the presence of caries, and the Caries Associated with Restorations and Sealants (CARS) system. For this, one examiner made the diagnosis and subsequent treatment decision using visual assessment in 163 children (3–10 years old) with both FDI and CARS criteria. The order of criteria used was defined by randomization. The reference standard was composed of two approaches: (1) the presence of carious tissue after restoration removal and (2) the presence of caries lesions after 6 and 12 months of follow-up. Sensitivity, specificity, and accuracy parameters were calculated at the dentin threshold. Poisson multilevel regression analyses were performed to evaluate the association of the diagnostic methods and other explanatory variables with the outcomes. Of the 651 restorations included, 480 were evaluated by the reference standard methods and were analyzed. The CARS system presented higher accuracy (0.721) than those obtained with FDI recurrence of caries (0.702), FDI marginal adaptation (0.700), and FDI marginal staining criteria (0.681). The FDI marginal staining showed the study’s lowest sensitivity (0.280) and accuracy (0.681) values. The specificity values of FDI recurrence of caries and FDI marginal adaptation were lower than the CARS system. Restorations assessed after the follow-up period resulted in lower sensitivity but higher specificity than those replaced after initial evaluation. In conclusion, the CARS system is more accurate in detecting caries around restorations in primary teeth than the FDI system, in general. However, the FDI recurrence of caries and FDI marginal adaptation present similar performance to the CARS system when the dentin threshold is considered. On the other hand, marginal staining is not an accurate parameter to evaluate caries around restorations.
{"title":"Clinical Accuracy of Two Different Criteria for the Detection of Caries Lesions around Restorations in Primary Teeth","authors":"B. L. Moro, L. R. Pontes, H. Maia, R. D. Freitas, T. Tedesco, D. Raggio, M. Braga, K. Ekstrand, J. Imparato, M. Cenci, F. Mendes","doi":"10.1159/000523951","DOIUrl":"https://doi.org/10.1159/000523951","url":null,"abstract":"This is a delayed-type cross-sectional prospective accuracy study nested in a randomized clinical trial. The aim was to investigate the diagnostic accuracy of two visual criteria for caries lesions detection around restorations in primary teeth: the International Dental Federation (FDI) criteria, considering adaptation, staining, and the presence of caries, and the Caries Associated with Restorations and Sealants (CARS) system. For this, one examiner made the diagnosis and subsequent treatment decision using visual assessment in 163 children (3–10 years old) with both FDI and CARS criteria. The order of criteria used was defined by randomization. The reference standard was composed of two approaches: (1) the presence of carious tissue after restoration removal and (2) the presence of caries lesions after 6 and 12 months of follow-up. Sensitivity, specificity, and accuracy parameters were calculated at the dentin threshold. Poisson multilevel regression analyses were performed to evaluate the association of the diagnostic methods and other explanatory variables with the outcomes. Of the 651 restorations included, 480 were evaluated by the reference standard methods and were analyzed. The CARS system presented higher accuracy (0.721) than those obtained with FDI recurrence of caries (0.702), FDI marginal adaptation (0.700), and FDI marginal staining criteria (0.681). The FDI marginal staining showed the study’s lowest sensitivity (0.280) and accuracy (0.681) values. The specificity values of FDI recurrence of caries and FDI marginal adaptation were lower than the CARS system. Restorations assessed after the follow-up period resulted in lower sensitivity but higher specificity than those replaced after initial evaluation. In conclusion, the CARS system is more accurate in detecting caries around restorations in primary teeth than the FDI system, in general. However, the FDI recurrence of caries and FDI marginal adaptation present similar performance to the CARS system when the dentin threshold is considered. On the other hand, marginal staining is not an accurate parameter to evaluate caries around restorations.","PeriodicalId":9620,"journal":{"name":"Caries Research","volume":"56 1","pages":"98 - 108"},"PeriodicalIF":4.2,"publicationDate":"2022-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45339708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Cho, J. Hsiao, Antoni B. Chan, H. Ngo, N. King, R. Anthonappa
Visual attention is a significant gateway to a child’s mind, and looking is one of the first behaviors young children develop. Untreated caries and the resulting poor dental aesthetics can have adverse emotional and social impacts on children’s oral health-related quality of life due to its detrimental effects on self-esteem and self-concept. Therefore, we explored preschool children’s eye movement patterns and visual attention to images with and without dental caries via eye movement analysis using hidden Markov models (EMHMM). We calibrated a convenience sample of 157 preschool children to the eye-tracker (Tobii Nano Pro) to ensure standardization. Consequently, each participant viewed the same standardized pictures with and without dental caries while an eye-tracking device tracked their eye movements. Subsequently, based on the sequence of viewed regions of interest (ROIs), a transition matrix was developed where the participants’ previously viewed ROI informed their subsequently considered ROI. Hence, an individual’s HMM was estimated from their eye movement data using a variational Bayesian approach to determine the optimal number of ROIs automatically. Consequently, this data-driven approach generated the visual task participants' most representative eye movement patterns. Preschool children exhibited two different eye movement patterns, distributed (78%) and selective (21%), which was statistically significant. Children switched between images with more similar probabilities in the distributed pattern while children remained looking at the same ROI than switching to the other ROI in the selective pattern. Nevertheless, all children exhibited an equal starting fixation on the right or left image and noticed teeth. The study findings reveal that most preschool children did not have an attentional bias to images with and without dental caries. Furthermore, only a few children selectively fixated on images with dental caries. Therefore, selective eye-movement patterns may strongly predict preschool children’s sustained visual attention to dental caries. Nevertheless, future studies are essential to fully understand the developmental origins of differences in visual attention to common oral health presentations in children. Finally, EMHMM is appropriate for assessing inter-individual differences in children’s visual attention.
{"title":"Understanding Children's Attention to Dental Caries through Eye-Tracking","authors":"V. Cho, J. Hsiao, Antoni B. Chan, H. Ngo, N. King, R. Anthonappa","doi":"10.1159/000524458","DOIUrl":"https://doi.org/10.1159/000524458","url":null,"abstract":"Visual attention is a significant gateway to a child’s mind, and looking is one of the first behaviors young children develop. Untreated caries and the resulting poor dental aesthetics can have adverse emotional and social impacts on children’s oral health-related quality of life due to its detrimental effects on self-esteem and self-concept. Therefore, we explored preschool children’s eye movement patterns and visual attention to images with and without dental caries via eye movement analysis using hidden Markov models (EMHMM). We calibrated a convenience sample of 157 preschool children to the eye-tracker (Tobii Nano Pro) to ensure standardization. Consequently, each participant viewed the same standardized pictures with and without dental caries while an eye-tracking device tracked their eye movements. Subsequently, based on the sequence of viewed regions of interest (ROIs), a transition matrix was developed where the participants’ previously viewed ROI informed their subsequently considered ROI. Hence, an individual’s HMM was estimated from their eye movement data using a variational Bayesian approach to determine the optimal number of ROIs automatically. Consequently, this data-driven approach generated the visual task participants' most representative eye movement patterns. Preschool children exhibited two different eye movement patterns, distributed (78%) and selective (21%), which was statistically significant. Children switched between images with more similar probabilities in the distributed pattern while children remained looking at the same ROI than switching to the other ROI in the selective pattern. Nevertheless, all children exhibited an equal starting fixation on the right or left image and noticed teeth. The study findings reveal that most preschool children did not have an attentional bias to images with and without dental caries. Furthermore, only a few children selectively fixated on images with dental caries. Therefore, selective eye-movement patterns may strongly predict preschool children’s sustained visual attention to dental caries. Nevertheless, future studies are essential to fully understand the developmental origins of differences in visual attention to common oral health presentations in children. Finally, EMHMM is appropriate for assessing inter-individual differences in children’s visual attention.","PeriodicalId":9620,"journal":{"name":"Caries Research","volume":"56 1","pages":"129 - 137"},"PeriodicalIF":4.2,"publicationDate":"2022-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42081193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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