Dental caries management requires iterative clinical reasoning, yet treatment thresholds and intervention pathways vary considerably among dentists despite established evidence-based frameworks. This study aims to examine how dentists integrate AI-supported diagnostic outputs into clinical reasoning in cariology, and how socio-technical conditions shape this process. Semi-structured interviews were conducted with 20 dentists from diverse specialties and practice settings in Türkiye. Interviews were developed and analyzed using the COM-B model and Theoretical Domains Framework to identify capability-, opportunity-, and motivation-related determinants of AI adoption. Reflexive thematic analysis revealed three interrelated patterns: (1) AI as a cognitive partner enhancing diagnostic confidence and preventive orientation; (2) structural and economic barriers limiting equitable access and shaping reliance on algorithmic outputs; and (3) ethical and professional concerns, including trust, liability, and surveillance, influencing the extent to which AI recommendations are accepted or resisted. Rather than directly shifting diagnostic thresholds, AI integration appears to reconfigure the socio-technical conditions under which clinical judgments are formed. Understanding these contextual determinants is essential for responsible and equitable AI implementation in cariology.
OBJECTIVE:To examine differences in the occurrence of consequences of untreated dental caries (pulpal involvement, ulceration, fistula, and abscess-PUFA) across intersectional social positions defined by sex, skin color, and household income among adolescents. METHODS:This study analyzed data from the Brazilian National Oral Health Survey (SB Brasil 2023), using a multi-stage stratified probability sampling design to represent adolescents aged 15-19 years. Social variables were combined into eight intersectional groups based on sex, skin color, and family income. Outcomes included PUFA prevalence ≥1 and counts of its components. Survey-adjusted Poisson regression with robust variance and a three-way interaction term was applied. RESULTS:The sample comprised 8,041 adolescents. Compared to high-income White males, prevalence was higher among low-income Black males (PR=5.93; 95%CI:2.60-13.51) and low-income Black females (PR=4.06; 95%CI:1.85-8.90). The predicted prevalence of PUFA ≥1 ranged from 4.0% (95%CI:2.0-7.0) among high-income White males to 21.0% (95%CI:11.0-32.0) among low-income Black males. Among females, prevalence estimates were 15.0% (95%CI:9.0-20.0) in high-income Black, 16.0% (95%CI:5.0-28.0) in low-income White, and 18.0% (95%CI:12.0-24.0) in low-income Black individuals. CONCLUSION:Marked differences in PUFA occurrence were observed across intersectional social positions, with the highest burden observed among low-income Black adolescents, particularly males for prevalence ratios, although females also presented high absolute prevalence. These findings reinforce the need for policies addressing structural social inequalities in oral health.
INTRODUCTION:Concerns about possible neurotoxicity related to fluoride exposure remain controversial, and evidence is heterogeneous across exposure ranges and study settings. This study evaluated the association between dental fluorosis and intelligence quotient (IQ) among children living in rural areas of Paraíba, Brazil. METHODS:A nested case-control study was conducted within a cross-sectional survey. Participants were matched 1:1 by age and sex. IQ was assessed using Raven's Colored Progressive Matrices and dichotomized as Lower IQ (Levels IV-V) versus Higher IQ (Levels I-III). Dental caries (DMFT/dmft) and fluorosis (TF index) were assessed after cleaning and drying. Fluoride concentration in drinking water was determined using a fluoride ion-specific electrode. Associations with Lower IQ were tested using conditional logistic regression in the matched sample (n=136) and a sensitivity analysis using logistic regression with cluster-robust standard errors. RESULTS:In crude matched analyses (68 pairs; n = 136), low family income was associated with Lower IQ (OR = 3.50, 95% CI: 1.15-10.63; p = 0.027), while dental caries showed a borderline association (OR = 1.85, 95% CI: 0.94-3.63; p = 0.075). In the adjusted conditional logistic regression model, associations were not statistically significant (income: adjusted OR = 2.93, 95% CI: 0.89-9.58; p = 0.076; caries: adjusted OR = 1.32, 95% CI: 0.57-3.05; p = 0.514), and dental fluorosis (TF>0) was not associated with Lower IQ (adjusted OR = 1.02, 95% CI: 0.45-2.33; p = 0.965). In the sensitivity analysis using the full analytic sample (n = 175) with cluster-robust standard errors clustered at the school level, low income (adjusted OR = 2.64, 95% CI: 1.04-6.71; p = 0.0416) and dental caries (adjusted OR = 2.13, 95% CI: 1.20-3.78; p = 0.0096) were associated with Lower IQ, whereas dental fluorosis was not (adjusted OR = 0.89, 95% CI: 0.55-1.45; p = 0.6471). CONCLUSION:Socioeconomic disadvantage and dental caries showed the most consistent associations with Lower IQ, whereas dental fluorosis, used as an indirect marker of earlier fluoride exposure during tooth development, was not independently associated with IQ status after adjustment when comparing Lower IQ versus Higher IQ.
INTRODUCTION:Dental caries is considered the most prevalent noncommunicable disease worldwide, while metabolic syndrome (MetS) is another noncommunicable condition with an increasing global burden. These conditions are caused by common risk factors, such as lifestyle and diet, which are shaped by overarching socioeconomic determinants. The aim of this study was to assess socioeconomic disparities in caries/MetS comorbidity. METHODS:This cross-sectional study included data from adults participating in the population-based Trøndelag Health Study (HUNT4, 2017-2019). Inclusion criteria were dentate 35 years or older participants in Oral Health Examination having records of socioeconomic determinants. Socioeconomic determinants included self-reported educational level (3 categories) and household income (3 categories). The outcome was a comorbidity of untreated caries (number of teeth with clinically and radiographically detected cavitation in dentine, D3T) and MetS (defined by the Joint Interim Statement). A modified Poisson regression analyses with robust error variances was used to estimate the prevalence ratio (PR) and the corresponding 95% confidence interval (CI). Sensitivity analyses were performed. RESULTS:Out of 7347, 3840 (52%) participants were included (55% women, the mean age of the participants 57.4 years (standard deviation (SD) 12.3). Neither dental caries nor MetS were recorded in 1052 (27%) participants, while 887 (23%) experienced caries/MetS comorbidity. Caries/MetS comorbidity was associated with the educational level in a gradient: basic and middle educational level (vs. higher), PR 1.47 (95% CI 1.22-1.79) and PR 1.29, (95% CI 1.15-1.47), respectively. Income gradient was also observed: lower and medium income level (vs. higher) PR 1.46 (95% CI 1.19-1.80) and PR 1.23 (95% CI 1.03-1.48), respectively. The sensitivity analyses yielded results of similar strength. CONCLUSIONS:A socioeconomic gradient was observed in caries/MetS comorbidity in adult Norwegian population. This finding supports integrated public health interventions targeting both health conditions simultaneously, particularly among populations with lower educational levels aiming to decrease overall burden of these conditions and reduce socioeconomic disparities. Oral health services should be a part of the Universal Health Coverage to reduce financial barriers to access. Further research in other contexts and longitudinal studies as well as public health intervention studies are warranted.
Background: Artificial intelligence (AI) is currently used to develop clinical predictive models for dental caries. However, most prognostic models lack key methodological components. Few reach clinical practice, and fewer demonstrate clinical benefit. Summary: This narrative methodological review examines considerations for developing, validating, and implementing AI-based caries prognostic models. Based on established prediction model frameworks (TRIPOD+AI, PROBAST+AI, and PROGRESS), we contextualize eight critical phases for caries-specific application. Each phase addresses challenges specific to caries, e.g., clustering of teeth within patients, dominance of baseline caries experience as a predictor, and frequent absence of external validation. Addressing these phases reduces bias, improves reproducibility, and supports meaningful evaluation of clinical impact. AI-based prognostic models should serve as decision-support tools that inform clinician and patient choices rather than substitutes for clinical judgment. Key Messages: (i) Most AI-based caries prognostic models are never implemented and fewer of those implemented demonstrate clinical benefit. Methodological deficiencies explain this gap. (ii) Caries prognostic research faces field-specific challenges such as retrospective design, clustering of teeth within patients, and dominance of baseline caries experience. Valid caries prognostic models require attention to eight phases, from problem selection through deployment and ongoing monitoring. (iii) Better discrimination (higher AUC) does not indicate clinical usefulness. Calibration and decision curve analysis are essential yet frequently absent from published studies. (iv) Researchers should report regulatory considerations and plan prospective impact assessment from study inception. Models generating risk estimates that influence clinical decisions qualify as software as a medical device, requiring regulatory compliance and demonstrated clinical impact before deployment.
INTRODUCTION:Caries risk assessment (CRA) is essential for individualized caries management in early childhood, but existing tools are difficult to standardize in routine practice. The ability of large language model (LLM)-based artificial intelligence (AI) systems to recognize and correctly apply validated CRA tools remains unclear. This study aimed to evaluate the ability of ChatGPT and Google Gemini, LLM-based AI systems, to apply and interpret CRA tools in early childhood under different prompting conditions. METHODS:Thirty standardized clinical vignettes of children aged 0-5 years were evaluated using Caries Management by Risk Assessment (CAMBRA) and the Cariogram by ChatGPT-5.1 (OpenAI, San Francisco, CA, USA) and Google Gemini-3.0 Pro (Google LLC, Mountain View, CA, USA) under three prompting conditions: unguided, guideline-informed, and guideline-only. An expert panel provided reference classifications. AI outputs were assessed for categorical agreement, mean absolute error (MAE), quality, accuracy, and readability. MAE differences were analyzed using the Friedman test and mixed-design repeated-measures analysis of variance (ANOVA), while quality, accuracy, and readability were analyzed using repeated-measures ANOVA. Reliability was assessed using intraclass correlation coefficients (ICCs). RESULTS:Inter- and intra-rater reliability were high (ICC = 0.89-0.93). Reference CAMBRA and Cariogram classifications showed a moderate correlation (ρ = 0.509; n = 30). MAE differed significantly across AI model-prompting condition combinations for both tools (p < 0.001). No significant difference was observed between AI models for CAMBRA, whereas ChatGPT showed lower MAE than Gemini for the Cariogram (p = 0.002). Guideline-informed and guideline-only prompting significantly reduced MAE and improved quality and accuracy compared with the unguided condition (p < 0.001). CONCLUSION:LLM-based AI systems can support CRA, particularly when guideline-based prompting is used. However, performance depends on the CRA tool and AI model, and numerical or algorithmic components, such as those in the Cariogram, remain challenging.
INTRODUTION:The aim of this prospective cohort study was to investigate whether obesity during adolescence influences caries increment among southern Brazilian young adults over a 5-year period. METHODS:In 2018, 1,197 adolescents attending public and private high schools in Santa Maria, southern Brazil, were examined, of whom 570 were reassessed after 5 years (retention rate: 47.6%). Baseline data collection included questionnaires on sociodemographic and behavioral variables, anthropometric measurements (height and weight), and clinical oral examinations (gingival bleeding index and Decayed, Missing or Filled Surfaces [DMFS] index). At follow-up, the DMFS index was recorded again. Multilevel Poisson regression models were used to assess the influence of weight status (normal, overweight, or obese) on caries increment. Incidence risk ratio (IRR) and 95% confidence interval (CI) were estimated. RESULTS:At baseline, 16.3% of participants were overweight (n = 92) and 11% were obese (n = 62). The overall caries increment in this sample of young adults was 1.79 surfaces (95% CI = 1.31-2.26). In the final model, after adjusting for age, family income, toothbrushing frequency, frequency of consumption of sugary food, and baseline caries experience, obese participants had a twofold higher risk of an additional carious surface compared to participants of normal weight (IRR=2.32, 95% CI=1.39-3.86, p=0.001). CONCLUSION:This study showed that obesity during adolescent was a risk factor for caries increment among young adults from southern Brazil.
OBJECTIVE: The objective of this study was to develop an evidence-based S3-level clinical practice guideline for the management of deep and extremely deep caries in vital permanent teeth. METHODS: An evidence-based medical guideline based on systematically searched and appraised evidence as well as a structured consensus (S3-level) was jointly developed by the European Federation of Conservative Dentistry (EFCD), the European Society of Endodontology (ESE), the Organization for Caries Research (ORCA), and the German Society of Conservative Dentistry (DGZ), following the methodological framework of the Association of Scientific Medical Societies in Germany (AWMF) and the GRADE approach. Four working groups formulated key clinical questions regarding: (1) caries removal strategies, (2) cavity liners, (3) management of exposed pulps, and (4) materials for direct pulp capping and pulpotomy. Systematic reviews were conducted for each question, and evidence was synthesized and graded for quality. A structured consensus process was used to formulate recommendations. In order to encourage its wide dissemination, this article is freely accessible on Clinical Oral Investigations, International Endodontic Journal, and Caries Research journals' websites. RESULTS: Evidence supports selective (SE) or stepwise caries removal (SW) over non-selective removal (NSE) to reduce the risk of pulp exposure in deep caries. Routine use of cavity liners after caries removal showed no consistent clinical benefit and is not routinely recommended. For vital pulp therapy following pulp exposure, both direct pulp capping and pulpotomy are effective options in teeth without irreversible pulpitis, while pulpotomy is an acceptable alternative to pulpectomy in cases with signs of irreversible pulpitis. Hydraulic calcium silicate cements demonstrated superior clinical outcomes compared to calcium hydroxide and should be preferred for pulp capping and pulpotomy. The certainty of evidence ranged from very low to moderate across questions and outcomes. CONCLUSION: For deep caries, maintaining pulp vitality by using less invasive management strategies is supported by current evidence. Implementation of this guideline requires clinician training, patient-centred decision-making, and consideration of economic and practical factors. Further research is needed, particularly for extremely deep caries and towards long-term outcomes.
INTRODUCTION:Early childhood caries (ECC) affects one in four Dutch 5-year olds and disproportionately impacts children from lower socioeconomic backgrounds. The Toddler Oral Health Intervention (TOHI) integrates oral health promotion into well-baby clinics, aiming to prevent ECC from the eruption of the first tooth. This study evaluates the cost-effectiveness of TOHI compared to care as usual (CAU) from a societal perspective, using caries reduction and quality-adjusted life years (QALYs) as outcomes. METHODS:A trial-based economic evaluation was conducted alongside a pragmatic randomized controlled trial with approximately 3-3.5 years of follow-up (n = 353). Costs (intervention delivery, dental healthcare, parental travel, and productivity losses) were combined with clinical and utility outcomes to calculate incremental cost-effectiveness ratios (ICERs). Missing and skewed data were handled using multiple imputation and bootstrapping, respectively. Analyses were adjusted for maternal socioeconomic position. RESULTS:TOHI reduced cavitated caries lesions (ICDAS ≥3) by 0.93 lesions per child at an incremental cost of EUR 93, resulting in an ICER of EUR 100 per lesion prevented compared to CAU. The probability of cost-effectiveness exceeded 80% at a willingness-to-pay (WTP) threshold of EUR 250 per lesion. TOHI also yielded a QALY gain of 0.01 per child, with an ICER of EUR 6,262 per QALY gained. The probability of cost-effectiveness for QALYs exceeded 80% at a WTP threshold of EUR 20,000 per QALY and increased to approximately 85% at EUR 40,000 per QALY. Sensitivity analyses supported the findings' robustness. CONCLUSION:TOHI is a more costly, yet also more effective strategy for reducing ECC and improving quality of life within the Dutch well-baby clinic system. With a low upfront investment and ICER and a moderate to high probability of cost-effectiveness at a EUR 20,000 per QALY threshold, TOHI seems to represent good value for money. Future research should assess long-term cost-effectiveness, broader healthcare impacts, and scalability across healthcare settings.
BACKGROUND:Artificial intelligence (AI) systems for radiographic caries detection are commonly evaluated using a small set of performance metrics, yet these measures are frequently reported and interpreted without the contextual information required for clinically meaningful conclusions. SUMMARY:This narrative review focuses on performance metrics - confusion-matrix measures (sensitivity, specificity, accuracy, predictive values, F1 score and related summaries) and discrimination metrics (area under the receiver operating characteristic curve and area under the precision recall curve) - and discusses how their interpretation depends on explicit reporting of the disease definition (grading cut-offs), unit of analysis (tooth surface/patient), decision threshold(s), and prevalence/case-mix. We additionally cover complementary metric-based assessments, including calibration (calibration curves, expected calibration error, Brier score), decision-analytic metrics (decision curve analysis and cost-sensitive clinical loss), and robustness summaries (uncertainty and subgroup/worst-group performance). A structured summary is provided of formulae, interpretive limitations, and the minimum information that should accompany each metric to support transparent reporting, comparability, and transportability. KEY MESSAGES:AI-assisted radiographic caries detection cannot be judged by headline metrics alone; traditional performance measures should be reported with clear disease definitions, operating points, prevalence, and the clinical impact of false results. We provide a practical guide to improving the transparency, comparability and clinically meaningful interpretation of future studies.
Introduction: The objective of this study was to investigate the treatment success rate of teeth treated with stepwise caries removal procedure (SWP) using SKaPa registry data. Methods: Study design was a retrospective analysis of longitudinal SKaPa database data. SWP treated teeth with a minimum of one follow-up visit was included (January 1, 2013-April 1, 2022). Teeth that had not been treated endodontically or extracted during the follow-up period was considered successful. The Kaplan-Meier survival analysis (p < 0.01) in combination with descriptive statistics was used for statistics. Results: A total of 111,771 teeth were included (50.7% women; 49.3% men). The most frequent tooth group was molars (71.5%). The results demonstrate a treatment success rate of over 60% after 110 months for teeth with deep caries lesions treated with SWP. Age was a statistically significant variable (p = 0.00) with increased survival rate for younger age-groups. Conclusion: Although SWP is performed on teeth with poor prognoses, the overall treatment success rate is over 60% after 9 years. Age, tooth group, localization, and caries risk are factors that could affect the outcome after SWP, with an improved prognosis for premolars, subjects under 40 years of age, and subjects with low or medium caries risk.
INTRODUCTION:Evidence suggests that a low copy number (CN) (2-3) of the α-amylase 1 gene (AMY1) may reduce the risk of dental caries, although findings remain inconsistent. Variations observed between studies could potentially be explained by the modulation of third factors, such as obesity, which may amplify the cariogenic potential of high AMY1 CN. This cross-sectional study explored the relationship between AMY1 gene CN variation (CNV) and dental caries experience, assessed with the Decayed and Filled Surfaces (DFS) index in young adults, and whether this association varied by obesity status. METHODS:A total of 597 participants (52.4% female, aged 26-29 years) from the Norwegian Fit Futures 3 study (2021-2022) were included. Salivary AMY1 CN was measured using droplet digital polymerase chain reaction. Obesity was defined as BMI ≥30 kg/m2. We analysed AMY1 CN as both continuous and categorical variables (2-3 [17%], 4-6 [53%], and 7-14 [30%] CN) using logistic regression. RESULTS:Although AMY1 CN alone was not associated with DFS, its interaction with obesity was significant (p = 0.036). Among obese individuals, a one-unit increase in AMY1 CN raised the probability of DFS ≥9 by 4.7 percentage points, with no association observed in non-obese individuals. In obese participants (n = 103), sex-adjusted odds ratios (ORs) for DFS ≥9 were as follows: OR 1.25 (95% CI: 1.02-1.53) per unit increase in AMY1 CN; OR 3.47 (95% CI: 1.23-9.79) for 4-6 versus 2-3 CN, and OR 4.48 (95% CI: 1.35-14.89) for 7-14 versus 2-3 CN. CONCLUSION:This study found that AMY1 gene CN alone was not directly associated with dental caries in young adults. However, obesity was identified as an effect modifier in the relationship between salivary AMY1 CNV and dental caries experience. Specifically, dental caries experience was higher in obese individuals with above-average AMY1 CN. These findings highlight the complex interplay between genetic, metabolic, and behavioural factors in dental caries development. Further research is needed to confirm these results and to explore the underlying mechanisms of this interaction.
INTRODUCTION:Socioeconomic inequalities in adolescent dental caries remain a major public health concern, even in countries with declining overall prevalence. Chile provides a unique setting to examine these inequalities nationally and assess the potential mitigating role of systemic fluoride delivery programmes. This study aimed to address these gaps by providing a national analysis of dental caries trends among 12-year-olds in Chile from 2009 to 2023 and investigate socioeconomic inequalities in dental caries experience between municipalities. METHODS:This ecological cohort study analysed 1,261,690 dental examinations of 12-year-olds across 325 Chilean municipalities from 2009 to 2023, representing 99.8% of eligible national records. Caries prevalence was modelled against area socioeconomic deprivation (IDSE deciles), adjusting for rurality and systemic fluoride delivery programmes, and weighting for number of total examinations by municipality/year. Inequality metrics included absolute rate difference (ARD), Slope Index of Inequality (SII), and Relative Index of Inequality (RII). RESULTS:During the study period, a strong and persistent socioeconomic gradient was observed: adolescents in the most deprived municipalities had a 17-percentage-point higher caries prevalence than those in the least deprived (β = -0.17, 95% confidence interval [95% CI]: -0.20, -0.14). This gradient followed a dose-response pattern and was confirmed by summary measures (ARD = 0.151; RRR = 1.234). Temporal analysis revealed peak inequality pre-2018 (SII = 0.17, 95% CI: -0.20, -0.14), followed by a steady decline post-2018, reaching statistically nonsignificant levels by 2023 (SII = 0.04, 95% CI: -0.15, 0.06). Fluoridation programmes modestly attenuated the deprivation gradient by 24% (β = -0.13), though they explained limited variance (ΔR2 = 0.04). CONCLUSION:Socioeconomic inequalities in dental caries among Chilean adolescents remain substantial, despite national declines in prevalence. While systemic fluoridation contributes to modest reductions in inequality, structural determinants are the primary drivers of persistent inequalities.
BACKGROUND:Artificial intelligence (AI) support is expected to increase accuracy and improve treatment plans in dentistry. Nevertheless, AI's ability to promote better oral healthcare is underexplored. This scoping review explores the influence of AI in supporting dental professionals with caries detection and decision-making regarding interventions. SUMMARY:Primary articles indexed on PubMed, Web of Science, Embase, Scopus, and Cochrane Library were searched until August 2025. Studies reporting the differences between participants' caries diagnosis process and decision-making with and without AI were included. Studies only reporting algorithm accuracy, in vitro studies, or studies without an outcome related to caries detection with AI support were excluded. No time and language limits were imposed. Outcomes regarding the influence of AI on the diagnostics process and decision-making were retrieved and narratively summarised. KEY MESSAGES:Thirteen publications were included. Number of participants ranged from 3 to 74, comprising dentists with varying experience and expertise and dental students. Results showed that AI enhances sensitivity, though its impact on specificity varies (10 studies). AI can promote unnecessary interventions for early-stage caries lesions (1 study). AI increased assessment time in two out of three cases (3 studies). AI's cost-effectiveness is uncertain, as greater sensitivity did not lead to better economic outcomes (1 study). In conclusion, AI has the potential to improve diagnostics and influence treatment choices, but current evidence is limited and inconsistent regarding its impact on specificity, decision quality, and cost-effectiveness. Longitudinal studies in clinical settings with long-term follow-ups are needed to understand AI's impact on decision-making.
INTRODUCTION:Few health topics are as controversial as fluoride, and social media has become a powerful arena where health information and misinformation circulate and compete for attention. This study systematically examined fluoride-related posts across two major platforms (Instagram® and X™) in English and Spanish. METHODS:Using a standardized approach, we identified the first 200 publicly available posts related to fluoride and health on each platform and language (n = 800 total). Posts were analyzed in duplicate, assessing perception (positive, negative, neutral), accuracy (accurate or non-accurate), format, account type, among others. RESULTS:Results revealed differences across language and platform. Spanish-language content was generally more accurate and conveyed a more positive tone, while English-language posts, particularly on X™, showed a higher prevalence of alarmist narratives. Engagement patterns varied by tone, post format, and account type. Negative posts attracted more likes overall. Post written in Spanish generated lower engagement. Carousel and photo-video formats and professional accounts received substantially greater interaction. CONCLUSION:These findings provide empirical evidence that language, source, and format strongly influence the reach and resonance of fluoride posts. They also suggest that multilingual strategies using engaging formats and credible professional voices can enhance the impact of evidence-based fluoride communication and counter misinformation.
INTRODUCTION:Dental caries, the most prevalent noncommunicable disease (NCD) in adolescence, may represent a hidden link to systemic inflammatory processes, a common underlying mechanism shared by all major NCDs. Accordingly, this study investigated whether dental caries was associated with systemic inflammatory burden in adolescents. METHODS:This population-based study utilized data from the RPS Brazilian Birth Cohort Consortium, specifically the 18-19-year follow-up conducted in São Luís, Brazil (n = 441). The main exposures included the visible plaque index (VPI), number of decayed teeth, DMFT index (decayed, missing, and filling), and PUFA index. The outcome was the allostatic inflammatory load, calculated as the sum of biomarkers - IL-6, IL-18, IL-1β, TNF-α, and C-reactive protein (CRP) - that fell within the high-risk range (≥75th percentile of the sample distribution). Each biomarker contributed one point, resulting in a total score ranging from 0 to 5. Crude and adjusted coefficients were estimated using regression models. RESULTS:The number of decayed teeth (β = 0.031, p = 0.015) and the VPI (β = 0.006, p = 0.001) were positively associated with higher allostatic inflammatory load scores. Among individual biomarkers, both the number of decayed teeth (β = 8.95, SE = 4.09, p = 0.02) and the VPI (β = 1.09, SE = 0.50, p = 0.03) were positively associated with IL-18 levels, whereas no significant associations were observed for the DMFT or PUFA indices (p > 0.05). CONCLUSION:Dental caries was associated with systemic inflammation in adolescence, possibly reflecting shared underlying risk factors and highlighting the relevance of integrating oral health into strategies addressing common risk factors for non-communicable diseases.
BACKGROUND:Advances in next-generation sequencing and multi-omics approaches reinforced the concept of functional diversity within biofilm communities, revealing roles beyond bacterial taxonomy and highlighting metabolic and ecological mechanisms operating at the individual level rather than within isolated caries lesions. Moving toward new clinical solutions will require broader perspectives; to this end, we propose key directions to advance the translational potential of caries microbiome research. We present a perspective that connects ecological theory, molecular evidence, and clinical implications through three central topics: (1) microbial composition, (2) microbial function, and (3) individual-level characteristics. SUMMARY:From a compositional perspective, caries microbiome research should move beyond the search for bacterial culprits and instead consider the broader microbial ecosystem, including low-abundance and nonbacterial members (such as archaea). Within this framework, microbial taxa and functions should not be viewed as inherently "good" or "bad," but rather as context-dependent components of a dynamic ecosystem shaped by sustained environmental pressures. Functionally, the recurrent enrichment of pathways related to carbohydrate metabolism, sugar transport, and acid production likely reflects microbial adaptation to persistent sugar exposure rather than intrinsic virulence traits. This perspective suggests that progress in caries research depends on moving beyond disease-centered models toward understanding how microbial stability preserves oral health. At the individual level, individuals with previous caries experience may retain disease-associated microbial or functional signatures during remission, a phenomenon referred to here as a microbiological dysbiosis scar. This ecological memory may help explain why past caries experience remains one of the strongest predictors of future lesions and highlights the importance of incorporating individual history into the design and interpretation of caries microbiome studies. Integrating detailed clinical metadata with advanced bioinformatic approaches, including artificial intelligence, will be essential for establishing meaningful biological links. KEY MESSAGES:Progress in caries microbiome research depends on refining study design across microbial composition, functional, and individual levels. Strengthening the resilience of the oral microbiome rather than eliminating specific pathogens or the microbiome should be the central goal of caries microbiology. Moving from blame to balance is not merely semantic; it represents a fundamental shift in how we study, prevent, and manage dental caries.
INTRODUCTION:This study aimed to assess the sensitivity, specificity, and accuracy of a digital-based method for caries assessment in a rodent model, compared to a conventional modified-Keyes method. METHODS:One hundred and eight mandible molars of Sprague-Dawley rats were collected from a cariogenic caries rodent model, including both caries-free and carious teeth. Smooth surfaces were evaluated using digital photography, whereas sulcal lesions and volumetric quantification were assessed with micro-CT and the Amira software. In the conventional assessment, smooth surfaces were examined under a stereomicroscope with tactile probing, and sulcal surfaces were evaluated on stained, sectioned teeth. Sensitivity, specificity, and accuracy of the digital approaches were calculated, with the conventional method serving as the gold standard. Spearman correlation analysis was conducted between conventional enamel caries scores, combined digital (photography and micro-CT) enamel caries scores, and micro-CT quantified remaining enamel volume. RESULTS:A total of 107 m were available for smooth surfaces evaluation, and 98 m were included for sulcal surfaces, tooth-level caries detection and enamel lesion assessments. For smooth surfaces, the digital photographic method demonstrated an accuracy of 88.0%, with a sensitivity of 88.8% and a specificity of 85.7%. In the evaluation of sulcal caries, Micro-CT analysis achieved an accuracy of 96.9%, with 100% sensitivity and 87.0% specificity. For tooth-level caries detection, the combined digital approaches of smooth surface photography and sulcal micro-CT slicing achieved 96.9% accuracy, 97.6% sensitivity, and 92.9% specificity. CONCLUSIONS:This study demonstrates the efficacy of digital photography and micro-CT in the caries assessment of rodent models. The findings support the establishment of a standardized, nondestructive imaging protocol to enhance consistency in caries research.
INTRODUCTION:The study objective was to assess and compare the use of diagnostic methods, clinical decision-making, treatment strategies, and attitudes of general dentists, pediatric dentists, and endodontists regarding deep carious lesions (DCL) in Egypt and Saudi Arabia. METHODS:A cross-sectional multinational study was conducted in Egypt and Saudi Arabia (January 2023-June 2024). A validated online questionnaire was distributed to 1,000 dentists (734 Egypt; 266 Saudi Arabia), including general practitioners, pediatric dentists, and endodontists. The survey covered demographics, diagnostics, clinical scenarios, treatment strategies, and influencing factors. Data were analyzed using SPSS v26 with descriptive statistics, chi-square tests, and logistic regression (p < 0.05). RESULTS:A total of 500 dentists responded (response rate of 46.0% for Egypt [338/734] and 60.9% for Saudi Arabia [162/266]). Most participants were general practitioners (60.4%) and female (57.8%), with an average of 9 years of clinical experience. Selective caries removal was preferred by 23.2% of general practitioners, 34.2% of pediatric dentists, and 21.8% of endodontists. Multivariable regression analysis showed that selective caries removal was more likely to be chosen by pediatric dentists (adjusted odds ratio [AOR] = 1.38, p = 0.04), dentists practicing in Egypt (AOR = 2.70, p < 0.001), and those who had attended MID courses (AOR = 1.75, p < 0.001). Endodontists demonstrated greater adherence to evidence-based guidelines (AOR = 3.35, p < 0.001), whereas practicing in Egypt (AOR = 0.43, p = 0.002), having more years of experience (AOR = 0.94, p = 0.001), and attending MID courses (AOR = 0.57, p = 0.03) were associated with lower odds of adherence. CONCLUSIONS:Pediatric dentists, practitioners in Egypt, and those with training in minimally invasive dentistry were more likely to favor selective caries removal, whereas endodontists demonstrated the highest adherence to AAE guidelines and tended to prefer more invasive treatment strategies. Despite strong evidence supporting conservative approaches for managing DCLs in vital teeth, invasive strategies were still commonly reported among respondents. Greater implementation of evidence-based, patient-centered treatment strategies is needed among dentists in Egypt and Saudi Arabia.
