Consensus report of the second European Consensus Workshop on Education in Periodontology.

BACKGROUND: The second European Consensus Workshop on Education in Periodontology was commissioned, as a result of the changes in the discipline and the advances in educational methods/technology, to update the 2009 Consensus report of the first European Federation of Periodontology (EFP) Workshop on the same topic that was jointly authored by the Association for Dental Education in Europe. AIM: To identify and propose changes necessary in periodontal education at three levels, namely undergraduate, specialist and continuing professional development (CPD), with respect to learning outcomes, competencies and methods of learning/training and evaluation. METHODS: Four working groups (WGs) considered education in periodontology at the undergraduate, specialist and CPD levels, and education methods. Four commissioned position papers, one per WG, summarized the relevant information. Workshop participants gathered at an in-person consensus meeting to discuss the individual reviews, and this consensus report summarizes the conclusions. RESULTS: The learning outcomes for undergraduate and specialist education in periodontology have been updated, and a proposal for learning outcomes for CPD programmes was made. Learning/teaching/training and evaluation methods were proposed for each level of education, which included face-to-face, virtual and blended learning methods. CONCLUSION: Developments in oral/dental medicine and in contemporary educational technologies have been translated into updated learning outcomes and learning/teaching/ training/evaluation methods relevant to education in periodontology.

ACES: A new framework for the application of the 2018 periodontal status classification scheme to epidemiological survey data.

AIM: To propose a framework for consistently applying the 2018 periodontal status classification scheme to epidemiological surveys (Application of the 2018 periodontal status Classification to Epidemiological Survey data, ACES). PROPOSED FRAMEWORK: We specified data requirements and workflows for either completed or planned epidemiological surveys, utilizing commonly collected measures of periodontal status (clinical attachment levels [CAL], probing depths, bleeding on probing), as well as additional necessary variables for the implementation of the 2018 periodontal status classification (tooth loss due to periodontitis and complexity factors). Following detailed instructions and flowcharts, survey participants are classified as having periodontal health, gingivitis or periodontitis. Rates of edentulism must also be reported. In cases of periodontitis, instructions on how to compute the stage and extent are provided. Assessment of grade can be derived from CAL measurements (or from radiographic alveolar bone loss data) in relation to root length and the participant's age. CONCLUSIONS: ACES is a framework to be used in epidemiological studies of periodontal status that (i) have been completed, and in which stage and grade according to the 2018 classification are inferred retroactively, or (ii) are being planned. Consistent use of the proposed comprehensive approach will facilitate the comparability of periodontitis prevalence estimates across studies.

Clinical attachment loss is cross-sectionally associated with elevated glucose among adults without diabetes.

AIM: We investigated whether periodontal measures are cross-sectionally associated with prediabetes and cardiometabolic biomarkers among non-diabetic younger adults. MATERIALS AND METHODS: One thousand seventy-one participants (mean age = 32.2 years [SE = 0.3]; 73% female) from the Oral Infections, Glucose Intolerance and Insulin Resistance Study were enrolled. Full-mouth clinical attachment loss (fm-CAL), probing depth (fm-PD) and bleeding on probing were ascertained. Interproximal CAL (i-CAL) and probing depths (i-PD) served as our primary exposures. Glucose, HbA1c, insulin and insulin resistance (HOMA-IR) outcomes were assessed from fasting blood. Prediabetes was defined per American Diabetes Association guidelines. Prediabetes prevalence ratios (PR [95% CI]) and mean [SE] cardiometabolic biomarkers were regressed on periodontal variables via multivariable robust variance Poisson regression or multivariable linear regression. RESULTS: Prevalence of prediabetes was 12.5%. Fully adjusted prediabetes PR in Tertiles 3 versus 1 of mean i-CAL was 2.42 (1.77, 3.08). Fully adjusted fasting glucose estimates across i-CAL tertiles were 83.29 [0.43], 84.31 [0.37], 86.48 [0.46]; p for trend <.01. Greater percent of sites with i-PD ≥3 mm showed elevated natural-log-HOMA-IR after adjustment (0%-12% of sites = 0.33 [0.03], 13%-26% of sites = 0.39 [0.03], ≥27% of sites = 0.42 [0.03]; p for trend = .04). CONCLUSIONS: i-CAL (vs. fm-CAL) was associated with elevated fasting glucose and prediabetes, whereas i-PD (vs. fm-PD) was associated with insulin resistance. Future studies are needed to examine periodontal disease and incident prediabetes.

Periodontitis and brain magnetic resonance imaging markers of Alzheimer's disease and cognitive aging.

INTRODUCTION: We examined the association of clinical, microbiological, and host response features of periodontitis with MRI markers of atrophy/cerebrovascular disease in the Washington Heights Inwood Columbia Aging Project (WHICAP) Ancillary Study of Oral Health. METHODS: We analyzed 468 participants with clinical periodontal data, microbial plaque and serum samples, and brain MRIs. We tested the association of periodontitis features with MRI features, after adjusting for multiple risk factors for Alzheimer's disease/Alzheimer's disease-related dementia (AD/ADRD). RESULTS: In fully adjusted models, having more teeth was associated with lower odds for infarcts, lower white matter hyperintensity (WMH) volume, higher entorhinal cortex volume, and higher cortical thickness. Higher extent of periodontitis was associated with lower entorhinal cortex volume and lower cortical thickness. Differential associations emerged between colonization by specific bacteria/serum antibacterial IgG responses and MRI outcomes. DISCUSSION: In an elderly cohort, clinical, microbiological, and serological features of periodontitis were associated with MRI findings related to ADRD risk. Further investigation of causal associations is warranted.

Dietary nitrate intake and net nitrite-generating capacity of the oral microbiome interact to enhance cardiometabolic health: Results from the Oral Infections Glucose Intolerance and Insulin Resistance Study (ORIGINS).

Background: We investigated the association between dietary nitrate intake and early clinical cardiometabolic risk biomarkers, and explored whether the oral microbiome modifies the association between dietary nitrate intake and cardiometabolic biomarkers. Methods: Cross-sectional data from 668 (mean [SD] age 31 [9] years, 73% women) participants was analyzed. Dietary nitrate intakes and alternative healthy eating index (AHEI) scores were calculated from food frequency questionnaire responses and a validated US food database. Subgingival 16S rRNA microbial genes (Illumina, MiSeq) were sequenced, and PICRUSt2 estimated metagenomic content. The Microbiome Induced Nitric oxide Enrichment Score (MINES) was calculated as a microbial gene abundance ratio representing enhanced net capacity for NO generation. Cardiometabolic risk biomarkers included systolic and diastolic blood pressure, HbA1c, glucose, insulin, and insulin resistance (HOMA-IR), and were regressed on nitrate intake tertiles in adjusted multivariable linear models. Results: Mean nitrate intake was 190[171] mg/day. Higher nitrate intake was associated with lower insulin, and HOMA-IR but particularly among participants with low abundance of oral nitrite enriching bacteria. For example, among participants with a low MINES, mean insulin[95%CI] levels in high vs. low dietary nitrate consumers were 5.8[5.3,6.5] vs. 6.8[6.2,7.5] (p=0.004) while respective insulin levels were 6.0[5.4,6.6] vs. 5.9[5.3,6.5] (p=0.76) among partcipants with high MINES (interaction p=0.02). Conclusion: Higher dietary nitrate intake was only associated with lower insulin and insulin resistance among individuals with reduced capacity for oral microbe-induced nitrite enrichment. These findings have implications for future precision medicine-oriented approaches that might consider assessing the oral microbiome prior to enrollment into dietary interventions or making dietary recommendations.