Background: In this study, we describe a method by which a patient can independently assess their own periodontitis risk, for example, at home, with a mobile application. The aim of the study is to use active matrix metalloproteinase aMMP-8 mouth rinse cut-off 20 ng/mL point-of-care testing (POCT) and a polynomial function to reveal patients’ statistical risk of periodontitis. Methods: The polynomial function presented in this study was modeled with multiple logistic regression and the function estimates the risk of periodontitis using a probability measure. To investigate variables associated with periodontitis, we used data from adult patients visiting dental clinics in Thessaloniki, Greece. Results: The research results revealed that with appropriate information it is possible to obtain sufficient accuracy about a patient’s potential risk of periodontitis. The function for estimating risk of periodontitis is PERIORISK = (1 + e^{−(3.392×X1+0.002×X2+1.858×X3−9.151)})⁻¹, where X1 = aMMP-8 test result and tobacco smoking status, X2 = age × waist circumference and X3 = patient’s individual and parental history of diabetes. Conclusions: The prediction of periodontitis risk using an aMMP-8 test and a polynomial function seems to be a useful, non-invasive, safe-to-use and cost-effective tool for all people. Overall, in the model created, mouth rinse cut-off 20 ng/mL aMMP-8 test result, age, waist circumference, tobacco smoking status and patient’s individual and parental history of diabetes were found to be good factors explaining the risk of periodontitis.

Background: Periodontitis is a global health crisis that affects almost half of the world’s population and commonly goes unnoticed because of its asymptomatic and pain-free nature. For early and easy detection and treatment, safe and non-invasive chair-side oral fluid biomarker (aMMP-8) diagnostics and new anti-microbial, anti-inflammatory and anti-proteolytic treatment modalities have been developed, which this review aims to introduce. Methods: For convenient diagnosis and tackling of periodontitis, adoption of an oral fluid aMMP-8 chair-side point-of-care rapid diagnostic test (POCT) has been proposed, comparable to home pregnancy and COVID-19 antigen tests, to be conveniently used by healthcare professionals and by patients themselves. To improve treatment of detected periodontitis, Finnish scientists have also developed a potentially industry-altering, biofilm-modulating, anti-microbial, anti-inflammatory, and anti-proteolytic (i) dual-light-activated photodynamic-therapy (2×PDT) and (ii) fermented lingonberry juice (FLJ) oral rinse designed for home personalized medicine and professional use. These new oral medicine technologies are reviewed and some unpublished results are presented. Results: aMMP-8 is the superior biomarker for grade of periodontitis (progression rate) when compared to the total latent/proform MMP-8 (total-MMP-8) and microbial lipopolysaccharide (LPS/LAL) activity. Cut-off 20 ng/mL is the optimal cut-off for aMMP-8 POCT and does not make false positives. Antibacterial 2× PDT light and anti-microbial FLJ treatments can eliminate and reduce problem-causing bacteria and Candida-yeasts from the mouth. Conclusions: These new oral medicine technologies have shown promising results and could have the potential to revolutionize diagnosis, prevention, oral care, plaque control and maintenance. These new game-changer oral medicine technologies have launched a new clinical field in dentistry: oral clinical chemistry.

Background/Objectives : Periodontitis is a chronic inflammatory disease initiated by dysbiotic biofilms and driven by host immune dysregulation, leading to connective tissue destruction and alveolar bone loss. Its early diagnosis is closely linked to the progression and outcome of the disease. Active-matrix metalloproteinase-8 (aMMP-8) is one of the key biomarkers for estimating irreversible collagenolytic degradation. aMMP-8 is among the key biomarkers for estimating irreversible collagenolytic degradation. To evaluate the role of oral fluid/salivary/mouthrinse aMMP-8 tests for early detection and treatment monitoring of periodontitis. Methods: A search was conducted in the Medline, Embase, Scopus, and Cochrane databases, restricted to articles published between January 2020 and December 2024 to capture the most recent literature. Pilot, cohort, case–control, and cross-sectional studies were included, while studies not aligning with the objectives of this review, as well as narrative reviews, editorials, and opinions were excluded. Results: A total of 276 articles were retrieved. After removing duplicates, 226 studies remained, of which 216 were retained following title, abstract, and keyword screening. From these, 26 studies were finally included in this review. aMMP-8 point-of-care tests appear to be promising tools for early diagnosis, disease severity assessment, and treatment monitoring in periodontitis, though findings remain conflicting across studies. Elevated aMMP-8 levels are associated with active periodontal pathology and tissue destruction, reflecting ongoing collagenolytic degeneration. Conclusions: aMMP-8 mouthrinse, saliva, or oral fluid tests can be used for predictive and early diagnosis as well as for treatment monitoring in patients with periodontal disease, and they function effectively as biomarkers for periodontitis.

Background/Objectives: This narrative review paper highlights the multifaceted influence of dysbiotic biofilm, genetic background, host response, and environmental factors on periodontitis. It explores the roles of type I and II diabetes mellitus, gestational diabetes, and metabolic syndrome in the progression of periodontitis, drawing insights from various empirical studies and theoretical perspectives. Methods: Relevant articles were sourced using keywords in databases like PubMed/Medline, Science Direct, Scopus, and Google Scholar. Additionally, this review examines the relationship between aMMP-8 levels and increased glycemic states, as well as varying degrees of periodontitis severity. Results: The biomarker active-matrix metalloproteinase-8 (aMMP-8), produced by polymorphonuclear leukocytes (PMN), is highlighted as a reliable indicator of ongoing connective tissue degradation. Dysfunctions in PMN activity, accumulation of advanced glycation end products (AGE), and oxidative stress aggravate the periodontal inflammatory response and complications of diabetes. Traditional diagnostics of periodontitis do not provide sufficient information about the current or future disease initiation or activity of periodontitis. Conclusions: The implications of this review point to the need for monitoring periodontal health by utilizing innovative strategies like aMMP-8 point-of-care testing, using oral rinse for screening and treatment monitoring, and harnessing the potential of supportive treatments like low-dose doxycycline and light-activated mouth rinses for restoring periodontal health. Its expression in oral fluids is a promising diagnostic tool to differentiate periodontitis from gingivitis and healthy periodontium, especially when associated with systemic diseases, fostering greater collaboration among healthcare professionals.

Background: We propose a framework for determining the stage of periodontitis in a personalized medicine context, building on our previously developed model for periodontitis detection. In this study, we improved the earlier model by incorporating additional components to form a comprehensive system for identifying both the presence and stage of periodontitis. Central to the home-use application is an active-matrix metalloproteinase-8 (aMMP-8) mouth rinse test (cut-off: 20 ng/mL), integrated with software delivered via a mobile application. Methods: First, using all the data, we modeled a single polynomial function to distinguish healthy and stage I periodontitis patients from stage II and III patients. Second, we used an already published periodontitis detection function to separate stage I patients from healthy patients. Third, one more function was created that divided stage II and III patients from each other. All functions were modeled by multiple logistic regression analysis from the patient data, which consisted of 149 adult patients visiting dental offices in Thessaloniki, Greece. Results: The complete model demonstrated a sensitivity of 95.8% (95% CI: 92.1–99.4%) and a specificity of 71.0% (95% CI: 55.0–86.9%) for detecting periodontitis. Among those identified with periodontitis, the correct stage was determined in 61.1% of cases, with stage-specific accuracies of 64.3% for stage I, 60.5% for stage II, and 60.9% for stage III. All testing was performed on patient data with which the complete model was formed. Conclusions: The results of this study showed that with sufficient data and using multiple logistic regression analysis, a model can be created to simultaneously identify the presence and stage of periodontitis. Overall, in the complete model generated, a mouth rinse aMMP-8 test result with a cut-off value of 20 ng/mL, Visible Plaque Index (VPI) and information of patient’s teeth number present were found to be important factors to determine the stage of periodontitis in a personalized medicine manner for everyone to use.