Background This study examines the relationship between the microbial load of selected periodontitis-associated bacteria (PAB) and proinflammatory biomarkers in gingival crevicular fluid (GCF) from patients with periodontitis. Methods GCF and subgingival biofilm samples were collected from the deepest periodontal pocket of each quadrant of 515 patients diagnosed with periodontitis using sterile GCF collection strips for GCF and sterile paper points for subgingival biofilm. Selected PAB (i.e., Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, Prevotella intermedia, Fusobacterium nucleatum, Treponema denticola, and Tannerella forsythia) were analyzed and associated with the concentrations of interleukin-8 (IL-8) and active-matrix metalloproteinase-8 (aMMP-8). Results Increased aMMP-8 (beta:187.75, CI:[132.45;243.05], p < 0.001) and IL-8 levels (beta:144.27, CI:[84.04;204.50], p < 0.001) were associated with deeper mean probing pocket depths. Smoking was significantly associated with decreased aMMP-8 (beta:-121.81, CI:[-202.51;-41.11], p = 0.003) and IL-8 (beta:-95.44, CI:[-182.03;-8.86], p = 0.031) expression. Multivariate analysis adjusted for confounding factors revealed a significant association between IL-8 and P. gingivalis (beta: 26.68, CI:[2.00;51.37], p = 0.034). Conclusion Higher levels of proinflammatory biomarkers were observed in patients with advanced periodontal disease. Notably, the findings suggest that IL-8 levels, but not aMMP-8, might be associated with P. gingivalis levels. The results further confirm that smoking is an important confounder when examining biomarkers.
ABSTRACT Background Histological grading of oral epithelial dysplasia (OED) is the gold standard for predicting malignant transformation in potentially malignant disorders. However, traditional grading systems suffer from subjectivity and poor diagnostic reproducibility, complicating patient management. This narrative review evaluates the clinical utility of current and emerging OED grading systems. Methods We reviewed recent literature (2019–2026) comparing the traditional World Health Organization (WHO) classifications against binary grading, histopathological feature‐specific models (two‐point and six‐point systems), diagnostic biomarkers, and clinical risk factors. Results The WHO system frequently demonstrates poor‐to‐fair interobserver agreement. Conversely, binary and six‐point grading systems provide superior reproducibility. While these models effectively stratify malignant transformation risk, their clinical utility is limited by tissue sampling errors, such as “skip areas.” Furthermore, immunohistochemical biomarkers (Keratin 13 and 17) show promise as diagnostic adjuncts to assist in identifying high‐risk variants like differentiated dysplasia. Conclusion While the WHO system remains the gold standard, its subjectivity complicates clinical decisions. Adopting objective binary and feature‐specific models offers superior clinical utility for risk stratification. Clear numerical cutoffs alongside expanded morphological features and biomarkers may influence the accuracy of predicting malignant transformation, inform clinical decision‐making regarding surgical versus conservative surveillance, and optimize patient management when integrated with clinicopathological findings.
ABSTRACT Aim Recent advances in artificial intelligence (AI) have shown promise for the detection of periodontal disease. This study aimed to synthesize current evidence on the diagnostic performance of AI models applied to cone‐beam computed tomography (CBCT) for periodontal disease. Methods A comprehensive literature search of MEDLINE, Scopus, Web of Science, and Embase was conducted to identify studies on AI‐assisted diagnosis of periodontal disease using CBCT published up to December 2025. The Quality Assessment of Diagnostic Accuracy Studies‐2 (QUADAS‐2) tool was used to assess the risk of bias. Results Among 10,099 records screened, eight studies met the inclusion criteria. These studies indicate that AI models, predominantly based on convolutional neural network (CNN) architectures applied to CBCT images, have substantial potential for detecting periodontal bone loss and related conditions. However, diagnostic performance metrics varied markedly across studies, and direct comparisons with human clinicians produced inconsistent findings, underscoring the need for more rigorous study designs and standardized datasets. Conclusions Despite limitations arising from heterogeneous methodologies and non‐standardized data collection, CBCT‐based AI models show considerable promise for enhancing periodontal disease diagnosis. Further high‐quality, methodologically robust research is warranted to validate and optimize these approaches for clinical use. Trial Registration PROSPERO: CRD420251273846
ABSTRACT Aim This systematic review evaluated the clinical evidence on the benefits of antioxidant supplementation as an adjunct to conventional periodontal therapy in chronic periodontitis treatment. Materials and Methods A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and Cochrane Library from inception to February 2025 for relevant randomized controlled trials. A network meta‐analysis was performed, with evidence certainty assessed using CINeMA. Results Nineteen randomized controlled trials (810 patients) were identified and seven antioxidants were evaluated. For probing depth, adjunctive melatonin (standardized‐mean‐difference = 1.88, 95% CI: [1.09, 2.67]), resveratrol (standardized‐mean‐difference = 1.42, 95% CI: [0.33, 2.51]), and green tea (standardized‐mean‐difference = 1.30, 95% CI: [0.03, 2.57]) showed significant improvements over scaling and root planing alone. For clinical attachment loss, melatonin (standardized‐mean‐difference = 2.37, 95% CI: [1.31, 3.44]) and curcumin (standardized‐mean‐difference = 1.37, 95% CI: [0.02, 2.73]) demonstrated efficacy. No antioxidants significantly improved plaque or gingival indices. CINeMA results indicated that some evidence had low to very low certainty. Conclusion Adjunctive melatonin may enhance probing depth reduction and clinical attachment gain, green tea and resveratrol may contribute to reducing probing depth, and curcumin may improve clinical attachment loss. However, owing to limited evidence of low certainty, these conclusions require cautious interpretation.
