OBJECTIVE:This study aimed to investigate the relationships between etching and infiltration durations and their corresponding depths using optical coherence tomography (OCT), develop preliminary time-depth predictive models, and evaluate the ex vivo performance of OCT-optimized individualized resin infiltration (OCT-IRI) for enamel specimens with varying depths of demineralization. METHODS:Enamel specimens were subjected to acid etching and resin infiltration for varying durations, and OCT-derived mean gray value (MGV) changes were used to construct time-depth curves. Natural enamel specimens exhibiting non-cavitated subsurface alterations (lesions < 300 μm) and artificially demineralized teeth (lesions ≥ 300 μm) were divided into four subgroups: Untreated Control (UC), Fluoride Varnish (Duraphat), Conventional Resin Infiltration (CRI), and OCT-IRI. Following an acid challenge, resistance to secondary demineralization was evaluated. RESULTS:Both etching and infiltration depths increased nonlinearly with treatment duration, gradually approaching a plateau. For lesions < 300 μm, OCT-IRI showed significantly lower secondary demineralization than CRI and Fluoride Varnish (P < 0.05). For lesions ≥ 300 μm, CRI and OCT-IRI showed similar ex vivo performance (P > 0.05), with both performing better than Fluoride Varnish (P < 0.05), which showed no significant difference compared with the control (P > 0.05). CONCLUSION:Under these ex vivo conditions, OCT provided a non-invasive, depth-resolved quantitative assessment of enamel alterations and monitored kinetic changes over time. The observed time-depth relationships may provide preliminary reference data for future studies investigating etching and resin infiltration durations in enamel lesions of varying depths. CLINICAL SIGNIFICANCE:These preliminary findings suggest that OCT-IRI may have potential for non-invasive assessment and longitudinal monitoring of subsurface enamel changes following RI. The observed time-depth relationships provide preliminary insights toward the future development of individualized treatment protocols. However, given the exploratory ex vivo design and small sample size of this study, further in vivo and clinical studies are strictly warranted to confirm the potential clinical applicability of OCT-IRI.
OBJECTIVES:(1) To evaluate the repeatability of a spectrophotometer and seven mobile applications for measuring colour in different gingival regions; (2) to compare repeatability between instruments within each region; and (3) to compare, for each instrument, repeatability across gingival regions. MATERIALS AND METHODS:A SpectroShade Micro spectrophotometer and seven mobile applications (four iOS and three Android) were evaluated. Gingival colour was recorded in 250 participants with healthy gingiva at five regions: mesial papilla, distal papilla, free gingival margin, middle attached gingiva, and mucogingival line. CIELAB coordinates were obtained in triplicate. Repeatability was assessed using the MCDM₀₀ metric and interpreted according to the 50:50% gingival perceptibility (ΔE₀₀ = 1.1) and acceptability (ΔE₀₀ = 2.8) thresholds. Data were analysed using one-way randomised-blocks ANOVA and eta squared (η²). RESULTS:All instruments showed MCDM₀₀ values below the acceptability threshold. The spectrophotometer, all iOS applications, and the Android Colorimeter remained below the perceptibility threshold, whereas Android Color Meter exceeded it. Repeatability differed significantly between instruments, with the spectrophotometer and iOS OptiShade showing the highest repeatability and Android Color Meter the lowest. Repeatability was generally consistent across gingival regions; only the spectrophotometer and iOS ColorMeter (RGB) showed significant regional differences, with negligible effect sizes. These results describe repeatability under the study conditions and should not be interpreted as evidence of trueness or absolute accuracy. CONCLUSIONS:All instruments demonstrated clinically acceptable repeatability. The spectrophotometer and iOS OptiShade provided the most consistent measurements, while Android Color Meter showed the lowest repeatability. Gingival region had minimal influence on repeatability. CLINICAL SIGNIFICANCE:The spectrophotometer and iOS OptiShade are the most reliable options for gingival colour assessment. Mobile applications are clinically promising, although performance remains device- and environment-dependent. This conclusion refers specifically to repeatability; the study did not establish trueness or absolute accuracy.
PURPOSE:To compare tooth sensitivity (TS), gingival irritation (GI), and bleaching effectiveness between two commercial 35% hydrogen peroxide in-office bleaching formulation characterized by acidic and neutral-to-alkaline pH profiles in patients wearing fixed orthodontic appliances during the final stabilization phase of orthodontic treatment. METHODS:In this single-blind randomized clinical trial, 120 participants undergoing fixed orthodontic treatment were randomly allocated to receive either a 35% hydrogen peroxide bleaching gel with acidic pH (Whiteness HP Maxx) or a 35% hydrogen peroxide bleaching gel with neutral-to-alkaline pH (Whiteness HP AutoMixx Plus). Two bleaching sessions were performed at a 7-day interval. The primary outcome was the absolute risk and intensity of TS, assessed using a visual analogue scale (VAS). Secondary outcomes included GI (VAS) and bleaching efficacy, evaluated by spectrophotometric measurements (ΔE00, ΔEab, and ΔWID) and shade guide units (ΔSGU). Data were analyzed using chi-square and independent-samples t-tests (α = 0.05). RESULTS:Participants treated with the neutral-to-alkanine formulation showed a significantly lower absolute risk of TS than those treated with the acidic formulation (55% vs. 75%; RR = 0.73; 95% CI: 0.56-0.96; p = 0.02). TS intensity was also significantly lower in the neutral-to-alkaline group at multiple evaluation time points during both bleaching sessions (p < 0.05). No significant differences were observed between groups regarding the absolute risk or intensity of GI (p > 0.05). Both bleaching protocols produced clinically relevant and statistically comparable color changes according to objective (ΔE00, ΔEab, and ΔWID) and subjective (ΔSGU) assessments (p > 0.05). CONCLUSIONS:The neutral-to-alkaline commercial in-office bleaching system resulted in lower risk and intensity of tooth sensitivity than the acidic system, while no differences in bleaching effectiveness or gingival irritation were detected between the systems. CLINICAL SIGNIFICANCE:Among the two commercial bleaching systems evaluated, the neutral-to-alkaline formulation was associated with lower tooth sensitivity while providing clinically relevant whitening. Because the systems differed in characteristics beyond pH, this benefit cannot be attributed exclusively to pH.
OBJECTIVES:This randomized, prospective, split-mouth study aimed to evaluate the clinical performance of flowable bulk-fill restorative systems in Class II restorations after 7 years of follow-up. METHODS:Class II restorations were performed in 159 teeth according to the restorative systems: conventional microhybrid resin composite (PA - Peak Universal + Amelogen Plus, Ultradent); flowable bulk-fill and nanofilled resin composites (ABF - Adper Single Bond 2 + Filtek Bulk Fill Flow + Filtek Z350XT, Solventum); and flowable bulk-fill and microhybrid resin composites (XST - XP Bond + SDR + TPH3, Dentsply). Clinical performance was assessed using the USPHS criteria. Statistical analyses included Kaplan-Meier survival test, Log-rank test, Frailty Cox proportional-hazard model, Generalized Linear Mixed Model, and Generalized Estimating Equations (α=0.05). RESULTS:A total of 76 restorations were evaluated after 7 years. No significant differences in survival rates were found among the groups. At the 7-year evaluation, both bulk-fill systems showed higher marginal discoloration than PA. A significant difference was observed between PA and ABF for surface texture, whereas XST did not differ from either group. For longitudinal comparisons, most parameters showed no significant differences over time. The XST group showed a significant change in marginal integrity between the 3- and 4-year follow-ups, which was maintained at the 7-year follow-up, whereas the ABF group showed a significant difference in marginal discoloration between the 3- and 7-year follow-ups. Logistic regression analysis revealed that no baseline factors influenced retention outcomes. CONCLUSIONS:No statistically significant differences in survival were detected among the tested restorative systems after 7 years. Although flowable bulk-fill restorative systems showed increased marginal discoloration, this finding may be interpreted as an esthetic alteration rather than a functional failure or the need for restoration replacement. Additionally, flowable bulk-fill restorative systems showed changes in marginal outcomes over time. CLINICAL SIGNIFICANCE:Flowable bulk-fill restorative systems can be used in Class II restorations, as no statistically significant differences in survival were detected among the tested restorative systems after 7 years. Clinicians should be aware of the increased risk of marginal discoloration in these restorative systems; however, it should be interpreted as an esthetic alteration rather than a functional failure.
OBJECTIVE:This study aims to develop and evaluate machine learning (ML) models predicting headache at 40 years of age using longitudinal data from the 1982 Pelotas Birth Cohort, Brazil. METHODS:Analysis included 2,963 participants followed from birth to age 40. The outcome of interest was self-reported headache at age 40, ascertained by a standardized yes/no item. Predictors spanning sociodemographic, lifestyle, sleep, diet, mental health, and orofacial pain domains over the life course were used. Five supervised ML algorithms were evaluated: XGBoost, CatBoost, Random Forest, LightGBM, and TabPFN, benchmarked against multivariable logistic regression. Model performance was primarily assessed using the area under the ROC curve, with accuracy, precision, recall, and F1-score also reported. Data analysis was conducted in Python, with the database split into training (70%) and test (30%) sets. Model interpretability was assessed using Shapley values. RESULTS:Self-reported headache was reported by 1,275 individuals (43.0%). The tuned XGBoost classifier achieved the highest discriminative performance (AUC = 0.79, 95% CI 0.76-0.82), which did not differ significantly from multivariable logistic regression (AUC = 0.78, 95% CI 0.75-0.81). Across all algorithms, AUC ranged from 0.76 to 0.79, with specificity consistently high (0.79-0.83) and sensitivity moderate (0.54-0.64). At the 0.50 threshold, the tuned XGBoost classifier showed positive and negative predictive values of 0.70 and 0.75. Restricted to variables measured before age 40, the same classifier achieved an AUC of 0.74 (95% CI 0.71-0.78). Shapley analysis identified female sex, poor sleep quality, psychological distress, dietary trigger foods, lower household income, and reduced social support from friends as the dominant contributors to model output. CONCLUSION:ML models using life-course data can predict midlife headache with moderate-to-good discriminative ability. The prominence of modifiable psychosocial and socioeconomic predictors suggests concrete targets for future etiological and interventional research. Further model refinement, external validation, and assessment of clinical and public health utility are needed before real-world implementation. CLINICAL SIGNIFICANCE:Sleep quality, psychological distress, social support and household income, asked during routine dental history-taking, identify adults more likely to report headache; bruxism and dental attendance do not. Because sensitivity is moderate, these items should guide who warrants fuller headache and orofacial pain assessment rather than serve as a screening test.
