Stages Of Periodontal Disease Research Articles

Peri-implantitis, Risk of Recurrence and Implant Loss in Soldiers with Stage III/IV Periodontitis during 20-30 Years of Supportive Periodontal Therapy (SPT).

To help fill the knowledge gaps regarding the long-term effectiveness of peri-implantitis therapy, this retrospective study of soldiers with treated severe periodontitis (stage III gen. / IV) who had been undergoing adherent SPT for at least 20 years aimed to determine the frequency of peri-implantitis and patient-related risk factors for this, as well as the 10-year survival rates of dental implants under peri-implantitis therapy. The observation period was between 1993 and 2023. All patients were referred by their military dentists for specialist dental training and underwent systematic periodontal therapy. A multi-stage peri-implantitis treatment concept was used. In 86 (31%) of 276 patients (total treatment time 23.6 ± 2.8 years, 53.1 ± 20.4 SPT sessions), 296 implant restorations were performed to close gaps or lengthen rows of teeth. In 29 (33%) of the implant patients, peri-implantitis developed on 25% of the implants. As a result, 11% of all implants were lost within 10 years due to peri-implantitis. Peri-implantitis led to implant loss in 59% of affected patients and 45% of implants. The survival time of implants lost later was 8.4 ± 6.2 years. Peri-implantitis and implant loss rates increased statistically significantly in stage IV periodontitis as well as in heavy smokers. Patients with implant loss and peri-implantitis had received systemic antibiotics due to periodontitis recurrence statistically significantly more frequently than patients without peri-implantitis and without implants during the ≥ 20-year SPT (p 0.05). Based on the present results, the early extraction of teeth during SPT in patients with treated generalised periodontitis stage III and stage IV plus replacement with implants is not advantageous.

Assessment of Salivary Neutrophil Gelatinase-Associated Lipocalin Levels in Diseased and Healthy Periodontium

Background: periodontal disease is one of the most frequent human diseases. Depending on the severity of the inflammation, the destructive process may affect both the gingiva (gingivitis) and/or the periodontal ligament and alveolar bone that surround and support the teeth (periodontitis). Objective: The study aimed to determine and compare the level of salivary Neutrophil gelatinase-associated lipocalin in periodontal health and disease (gingivitis and periodontitis stage I-III). Subjects and Methods: A total of 90 individuals participated in the research separated into five groups, clinically healthy (n=10), gingivitis (n=20), stage I periodontitis (n=20), stage II periodontitis (n=20) and stage III periodontitis (n=20), periodontal parameters were recorded, and the level of salivary Neutrophil gelatinase-associated lipocalin was assessed by using the enzyme-linked immunosorbent assay. Results: Neutrophil gelatinase-associated lipocalin salivary level was significantly higher (p<0.05) in periodontal disease groups compared to healthy controls. A statistically significant difference was also found between gingivitis and advanced periodontitis (stageII-III) (p<0.05). No significant difference (p>0.05) was found between different stages of periodontitis. Conclusions: Neutrophil gelatinase-associated lipocalin is associated with periodontal diseases and my play a role in its pathogenesis

Prevalence and severity of periodontal disease in the host community and Rohingya refugees living in camps in Bangladesh.

To assess the prevalence and severity of periodontal disease of the Rohingya refugees and host community in Bangladesh. An unpublished pilot was conducted for the sample size calculation. Two-stage cluster sampling method was used to select 50 participants from refugee camps and 50 from the host community. Structured questionnaire and periodontal examination were completed. Composite measures of periodontal disease were based on the World Workshop (WW) and Centers for Disease Control and Prevention-American Academy of Periodontology. Linear regression models, for clinical attachment level and periodontal pocket depth (PPD) and ordered logistic regression models, for composite measures, were fitted to test the association of periodontal measures and refugee status. Compared to the host community, a smaller percentage of refugees reported good oral health-related behaviours. Refugees exhibited lower levels of bleeding on probing but higher PPD, hence a higher proportion had severe stages of periodontitis. As per the WW, prevalence of periodontal disease was 88% and 100% in the host and refugee groups, respectively. In the unadjusted models, refugees were three times more likely to have severe stages of periodontitis; this association was attenuated when adjusted for confounders (sociodemographic variables and oral health-related behaviours). Prevalence of periodontitis was high both in the host community and refugees. The refugees exhibited a more severe disease profile. The oral health of both groups is under-researched impacting the response of the health system. Large-scale research systematically exploring the oral health of both groups will inform the design and delivery of community-based interventions.

AI-aided diagnosis of periodontitis in oral X-ray images

This study explored the construction and application of efficient deep-learning models to assist the diagnosis of periodontitis in panoramic radiographs. A periodontitis auxiliary diagnosis dataset was constructed in collaboration with the Peking University School of Stomatology. The dataset included 238 panoramic images, covering different stages of healthy teeth and periodontitis. The Labelme annotation tool was used to label tooth instances, alveolar bone contours, and the cemento-enamel junction. A Mask R-CNN model was developed for tooth segmentation, and a U-Net model was developed for segmenting alveolar bone contours and cemento-enamel junctions. Based on the results of tooth instance segmentation, principal component analysis was utilized to fit the direction of the dental long axis. The minimal bounding rectangle of the tooth prediction mask was used to determine the length of the tooth axis. The proportion of alveolar bone loss was calculated based on the distance of the cemento-enamel junction and the alveolar bone level along the dental long axis. An evaluation was conducted on 20 panoramic images comprising 496 teeth. The study achieved an accuracy rate of 90.73% in the staging of periodontitis.

Salivary microbiome variations in type 2 diabetes mellitus patients with different stages of periodontitis

BackgroundTo investigate the difference of salivary microbiome composition in type 2 diabetes mellitus with different stages of periodontitis.Methods105 patients diagnosed with T2DM were divided into four groups according to the Stage of periodontitis.The 16 S rDNA hypervariable regions V3-V4 were amplified by polymerase chain reaction (PCR) after saliva DNA was extracted. The library was constructed and Illumina sequencing was performed. The sequencing results were compared with the silva 138 database, and the salivary microbiome of the four groups of patients was studied by species composition analysis, species difference analysis, principal coordinate analysis, and correlation analysis.ResultsThere were significant differences in alpha diversity of salivary microbiome among the four groups, but no difference in Beta diversity. At the phylum level, there was one differential bacteria—Firmicutes, while at the genus level, there were 16 differential bacteria. Spearman’s correlation analysis identified significant correlations between periodontal health indices (PLI, SBI, AL and PD) and the abundances of over 13 genera, including Streptococcus, Gemella and Capnocytophaga, etc. Additionally, the duration of diabetes exhibited a positive correlation with AL and PD.ConclusionsThere are differences in salivary microbial composition in patients with type 2 diabetes mellitus with different stages of periodontitis. There is a correlation between some saliva microbiota and periodontal inflammation.

SLC30A4-AS1 Mediates the Senescence of Periodontal Ligament Stem Cells in Inflammatory Environments viathe Alternative Splicing of TP53BP1.

Periodontal ligament stem cells (PDLSCs) are key cells that suppress periodontal damage during both the progression and recovery stages of periodontitis. Although substantial evidence has demonstrated that incubation under an inflammatory condition may accelerate senescence of PDLSCs, whether cellular senescence in response to inflammatory incubation contributes to cell dysfunction remain unexplored. In this study, we first observed inflammation-caused PDLSC senescence in periodontitis based on comparisons of matched patients, and this cellular senescence was demonstrated in healthy cells that were subjected to inflammatory conditions. We subsequently designed further experiments to investigate the possible mechanism underlying inflammation-induced PDLSC senescence with a particular focus on the role of long noncoding RNAs (lncRNAs). LncRNA microarray analysis and functional gain/loss studies revealed SLC30A4-AS1 as a regulator of inflammation-mediated PDLSC senescence. By full-length transcriptome sequencing, we found that SLC30A4-AS1 interacted with SRSF3 to affect the alternative splicing (AS) of TP53BP1 and alter the expression of TP53BP1-204. Further functional studies showed that decreased expression of TP53BP1-204 reversed PDLSC senescence, and SLC30A4-AS1 overexpression-induced PDLSC senescence was abolished by TP53BP1-204 knockdown. Our data suggest for the first time that SLC30A4-AS1 plays a key role in regulating PDLSC senescence in inflammatory environments by modulating the AS of TP53BP1.

Occurrence of Aggregatibacter actinomycetemcomitans and Its JP2 Genotype in a Cohort of 220 Western Australians with Unstable Periodontitis.

The main purpose of the present study was to investigate the carrier rate of Aggregatibacter actinomycetemcomitans and its JP2 genotype in a cohort of 200 Western Australians diagnosed with periodontitis. In this descriptive cross-sectional study, 220 consecutive patients with periodontitis, aged 18 years and older, were recruited to a specialist periodontal practice in Perth City. Every patient included in this study contributed three different intra-oral samples. Periodontal, radiographical, and microbiological assessments were performed. The samples were analysed using a polymerase chain reaction for the detection of Aggregatibacter actinomycetemcomitans and its JP2 genotype using the primers and conditions described previously. A Chi-square test and logistic regression analysis were performed to evaluate the results. The prevalence of Aggregatibacter actinomycetemcomitans was 28.18%. The carrier rates of A. actinomycetemcomitans in the unstimulated saliva, cheek swabs, and pooled subgingival plaque samples were 21.80%, 19.50%, and 17.70%, respectively. There was a significant correlation between the severe form of periodontitis (stage IV, grade C) and younger age (p = 0.004), positive family history of periodontitis (p < 0.001), oral hygiene method (p < 0.001), and irregular dental visit attendance (p < 0.001). The binary logistic regression analysis revealed that having severe periodontitis risk increased almost three times in those who were young (OR: 2.812) and came from a family with a history of periodontal disease (OR: 3.194). However, the risk of severe periodontitis was five times higher in those patients with tooth loss due to periodontal disease (OR: 5.071). The highly leukotoxic JP2 genotype of Aggregatibacter actinomycetemcomitans was not detected. This study of a Western Australian cohort confirmed the low presence of Aggregatibacter actinomycetemcomitans and the complete absence of its JP2 genotype. Young age, family history of periodontal disease, lack of flossing, irregular dental visits, and tooth loss due to periodontitis were identified as potential risk factors for periodontitis stage IV, grade C in this cohort.

Correlation of serum vitamin D and IL-8 to stages of periodontitis: a case-control analysis

ObjectivesThe current literature lacks the correlation between serum levels of vitamin D and interleukin-8 (IL-8) to the stages of periodontitis. The present research objectives are to evaluate the serum levels of vitamin D and IL-8 in periodontitis participants and healthy controls and to measure their correlation with the stages of periodontitis.MethodsThe current case-control study was conducted on patients with periodontitis and healthy controls. After obtaining a questionnaire from the participants, the following clinical parameters were measured; periodontal probing depth (PPD), clinical attachment loss (CAL), plaque index (PI), gingival index (GI), bleeding on probing (BOP), and tooth count. The serum levels of vitamin D and IL-8 were measured using ELISA kits. Then, we measured the correlation of the stages of periodontitis with the serum levels of vitamin D and IL-8.ResultsNinety-eight participants; 52 with periodontitis and 46 healthy controls were included. The patients with periodontitis showed a significantly lower level of vitamin D, higher PPD, CAL, BOP, and lower number of teeth than the controls. In addition, serum vitamin D significantly correlated with the stages of periodontitis. Serum IL-8 showed no significant difference between the study and control groups while it does not significantly correlate with the stages of periodontitis.ConclusionThe current study’s findings suggest a potential association between serum level of vitamin D with severity of periodontitis which necessitates screening vitamin D status in patients with periodontitis and investigating the possibility of vitamin D supplementation in decreasing the progression of periodontitis.

E-cadherin Single Nucleotide Variants Are Associated with Increasing Susceptibility to Periodontitis.

To investigate the association of E-cadherin single nucleotide polymorphisms (SNPs) with periodontitis and the potential of these SNPs for identifying susceptibility to periodontitis. Periodontal clinical parameters were recorded followed by collecting venous blood for DNA extraction. Polymerase chain reaction was used to amplify target segments of the E-cadherin gene. Determination of the genotype and allele frequencies was performed using Sanger sequencing. All statistical analyses were performed using GraphPad Prism (version 9) using a statistically significant difference of p < 0.05. A total of 207 participants were recruited into two groups of healthy controls (n = 105) and cases diagnosed with periodontitis stage 2 or 3, grade B or C (n = 102). Analyses indicated that the genotypes and alleles of rs3743674 and rs5030625 E-cadherin SNPs were significantly associated with periodontitis. Results from a binary regression model suggested that the presence of these SNPs may indicate susceptibility to periodontitis and increase the rate of progression. Linkage disequilibrium analysis indicated that E-cadherin variants rs3743674 and rs5030625, and rs10272115 and rs16260 were correlated in a nonrandom manner (r 2 = 0.638 and 0.495, respectively). E-cadherin gene variants, rs3743674 and rs5030625, were associated with the periodontitis phenotype. These biomarkers may identify individuals susceptible to periodontitis and the rate of disease progression.

Evaluation of Periodontitis and Fusobacterium nucleatum Among Colorectal Cancer Patients: An Observational Cross-Sectional Study.

Periodontitis has been associated with an increased risk of CRC, as well as a worse prognosis due to increased inflammation mediators and carcinogenic factors. Moreover, direct and indirect virulence factors from periodontal pathogens, such as Fusobacterium nucleatum, could play a pivotal role in malignant transformation and progression. This cross-sectional study aims to evaluate the presence and the stage of periodontitis in a cohort of patients with CRC. The secondary aim is to assess the presence of F. nucleatum and its relationship with patients' general characteristics, concomitant pathologies, tumor characteristics, and drug therapy. Patients affected by CRC underwent dental examination and periodontal charting with the "North Carolina" probe to assess the presence and stage of periodontitis, according to the new classification of periodontal diseases of the World Workshop of the European Federation of Periodontology (EFP) and the American Academy of Periodontology (AAP) 2017. F. nucleatum presence was assessed by a dorsal tongue swab and related to the patient's general characteristics, concomitant pathologies, tumor characteristics, and drug therapy. Periodontal disease was found in 94.3% of I/II CRC stage patients and 100% of III/IV CRC stage patients. Severe periodontitis was found in 76% of the advanced CRC stage and 87.9% of patients with initial CRC, while initial periodontitis was found in 12.1% of initial CRC and 24% of late CRC stages, respectively, without significant differences. F. nucleatum presence showed no correlation between the patient's and tumor's characteristics, comorbidities, and drug assumed. Periodontal disease showed a high prevalence among CRC patients. Moreover, severe periodontitis has a higher prevalence in CRC patients compared to initial periodontitis. F. nucleatum presence was unrelated to CRC stage, site, other comorbidities, and drug therapies. With these data, it is not possible to admit a direct relationship between CRC and periodontal disease, but further case-control studies must be carried out to further prove this aspect. Preventive and operative targeted strategies to maintain a healthy oral status are suggested in CRC patients.

Effects of Toothpaste Containing 2% Zinc Citrate on Gingival Health and Three Related Bacteria-A Randomized Double-Blind Study.

Gingivitis is the initial stage of periodontitis, one of the most common oral diseases and the primary cause of tooth loss. This study aims to evaluate the effect of toothpaste containing 2% zinc citrate on gingival health and the abundance of three bacteria related to gingivitis and periodontitis. Eleven volunteers with the same oral health status were randomly assigned to the treatment (n = 5) and control (n = 6) groups. The control group used fluoride toothpaste, while the treatment group used fluoride toothpaste supplemented with 2% zinc citrate for 3 months. The plaque index, gingival index, and bleeding index were measured at baseline (0 day), 3 weeks, and 3 months. Dental plaque from four areas of the mouth (FDI criteria) was collected at the same timepoints. A total of 132 dental plaque samples were analyzed using quantitative PCR (qPCR) to monitor the abundance of Actinobacillus actinomycetemcomitans, Porphyromonas gingivalis, and Tannerella forsythia. Toothpaste containing 2% zinc citrate significantly lowered the gingival index and reduced gum bleeding but did not affect the plaque index. It also reduced the total abundance of the three bacteria related to gingivitis and periodontitis in dental plaque over a long-term period. Toothpaste with 2% zinc citrate persistently improves gingival health and reduces the presence of gingivitis-associated bacteria in dental plaque. Chinese Clinical Trial Registry (Clinical trial registration no.: ChiCTR1900020592) (09/01/2019).

The association of reproductive health factors with periodontitis in 45-80 years old US women from NHANES 2009-2014.

We investigated the association of female reproductive factors with periodontitis. This cross-sectional study analyzed data from the US National Health and Nutrition Examination Survey 2009-2014 on 2321 women aged 45-80 years who had full-mouth periodontal examination and reproductive questionnaire. The 2018 World Workshop Classification of Periodontal and Peri-implant Diseases was used to classify periodontitis stages. After adjustment, > 3 pregnancies or live births were associated with increased stage III/IV periodontitis but age at first birth (AFB) > 23 years and female hormone use were associated with decreased stage III/IV periodontitis, while there were no associations of oral contraceptive use or menopause status with stage III/IV periodontitis. Stage III/IV periodontitis was more common in women with > 3 pregnancies or live births and AFB ≤ 23 years or never using female hormones but less common in women with ≥ 3 pregnancies or > 3 live births and AFB > 23 years or using female hormones. >3 pregnancies or live births were related with increased stage III/IV periodontitis and increased AFB was related with lowered stage III/IV periodontitis in overweight and smoking subgroups but using female hormone was related with reduced stage III/IV periodontitis in nonsmoking, non-overweight and black subgroups. >3 pregnancies/live births were related with severe periodontitis but AFB > 23 years and female hormone use were related with ameliorating periodontitis. Women with > 3 pregnancies/live births should receive intensive periodontal interventions. Female hormone therapy or AFB > 23 years may be beneficial for periodontal health of > 3 pregnancies/live births women.

Deep learning method to automatically diagnose periodontal bone loss and periodontitis stage in dental panoramic radiograph.

Artificial intelligence (AI) could be used as an automatically diagnosis method for dental disease due to its accuracy and efficiency. This research proposed a novel convolutional neural network (CNN)-based deep learning (DL) ensemble model for tooth position detection, tooth outline segmentation, tooth tissue segmentation, periodontal bone loss and periodontitis stage prediction using dental panoramic radiographs. The dental panoramic radiographs of 320 patients during the period January 2020 to December 2023 were collected in our dataset. All images were de-identified without private information. In total, 8462 teeth were included. The algorithms that DL ensemble model adopted include YOLOv8, Mask R-CNN, and TransUNet. The prediction results of DL method were compared with diagnosis of periodontists. The periodontal bone loss degree deviation between the DL method and ground truth drawn by the three periodontists was 5.28%. The overall PCC value of the DL method and the periodontists' diagnoses was 0.832 (P <​ 0.001). ​The ICC value was 0.806 (P <​ 0.001). The total diagnostic accuracy of the DL method was 89.45%. The proposed DL ensemble model in this study shows high accuracy and efficiency in radiographic detection and a valuable adjunct to periodontal diagnosis. The method has strong potential to enhance clinical professional performance and build more efficient dental health services. The DL method not only could help dentists for rapid and accurate auxiliary diagnosis and prevent medical negligence, but also could be used as a useful learning resource for inexperienced dentists and dental students.

ADGRU: Adaptive DenseNet with gated recurrent unit for automatic diagnosis of periodontal bone loss and stage periodontitis with tooth segmentation mechanism.

Periodontics and gingivitis are two of the most widely prevalent illnesses that affect people nowadays. The sixth most common disease in the world is periodontitis, and detecting periodontal bone loss is essential in the earlier condition and is crucial for the development of the proper diagnosis. Early bone loss detection can be assisted by using computer-assisted radiography examination. Understanding disease progression helps to select the most effective treatment action. An effective deep model is suggested to detect periodontal bone loss at an earlier stage for preventing the progression of Periodontics bone loss. This work is intimated by collecting images from online resources. Further, the images gathered from the dataset are preceded by the tooth segmentation which is done using DenseUNet + + . Further, the segmented images are given to the Adaptive DenseNet with Gated Recurrent Unit (AD-GRU) for detecting periodontal bone loss and this diagnosis is used for the periodontitis stage, where the ADGRU performance is augmented by optimizing the attributes using the Refined Red Kite Optimization Algorithm (RRKOA). The offered approach attained an accuracy of 94.45% which is higher than the88.63%, 90.58%, 89.54%, and 92.96% attained by the LSTM, DenseNet, GRU, DenseNet-GRU. The findings of the simulation proved the designed framework outperformed the traditional model with high accuracy. The developed effectual deep model-based periodontal bone loss and stage periodontitis diagnosis structure is used in healthcare applications.

The 2018 Classification of Periodontal Diseases: An Observational Study on Inter-examiner Agreement among Undergraduate Students.

The objective of the present observational study was to assess the inter-examiner agreement for the diagnosis of periodontitis using the 2018 CPD among fourth and fifth year undergraduate students. It is hypothesised that there is no difference in the inter-examiner relaibility between fourth- and fifth-year undergraduate students regarding staging and grading periodontal disease using the 2018 Classification of Periodontal Diseases (CPD). All participants received training on the 2018 CPD scheme through a mandatory periodontics course conducted by a periodontist. Documentation for seven deidentified periodontitis patients, comprising medical history, dental history including tooth loss, intra-oral photographs and radiographs, periodontal charts reporting probing depth, plaque and bleeding on probing scores, furcation involvement and clinical attachment loss, was sent via e-mail to undergraduate students. The cases consisted of one sextant, and the participants were instructed to assume the sextant to be a true representation of the entire dentition. Power analysis was done on pilot data, and the level of significance was set at p0.05. The percentage of undergraduate students in the fourth and fifth year that correctly identified the stage of periodontitis according to the 2018 CPD ranged between 28% and 72% and 18.5% and 77.8%, respectively. The percentage of undergraduate students in the fourth and fifth year that correctly identified the grade of periodontitis ranged between 40% and 88% and 51.8% and 92.5%, respectively. The overall staging and grading ranged between 22.8% and 74.1%, and 45.66% and 87.4%, respectively. There was no statistically significant difference between fourth- and fifth-year undergraduate students with regards to assigning the correct diagnoses to case documentation in terms of either stage or grade. Fourth- and fifth-year undergraduate students demonstrated high inter-examiner agreement using the 2018 CPD.

Quorum Sensing Molecule Autoinducer-2 Promotes Macrophage Classical Polarization and Exacerbates Periodontal Inflammation Via Nf-Κb Signalling.

The role of quorum sensing signaling in the immunoinflammatory response during the development of periodontitis is not yet known. This study aimed to explore the effect of Autoinducer-2, a quorum sensing signaling molecule, on macrophage phenotypic remodeling in the immune microenvironment of periodontitis, to further elucidate its mechanism and to discover inhibitors against periodontitis. Bioluminescence experiments and periodontitis model were used to demonstrate the association between periodontitis progression with AI-2. Next, AI-2 challenged macrophage was introduced to transcriptomic sequence and the immune profile was characterized in combination with flow cytometry, qPCR, and immunofluorescence. Activation of NF-κB signalling by AI-2 was confirmed by fluorescence co-localization and immunoblotting. Finally, morphological methods such as Micro-CT and HE, TRAP staining and immunological methods such as immunohistochemistry/fluorescence staining were used to assess the mechanisms by which AI-2 regulates periodontitis progression. AI-2 level was positively correlated with the progression of periodontitis stages and was significantly higher in periodontitis stage III and IV patients. AI-2 promotes macrophage classical polarization and facilitates the secretion of inflammatory factors in vitro, which is dependent on the activation of the NF-κB signaling pathway. AI-2 promotes alveolar bone resorption, but D-ribose acts as a quorum sensing inhibitor to alleviate macrophage classical polarization and attenuates alveolar bone resorption and inflammatory responses in periodontitis mice. Our study demonstrates that AI-2 promoted classical polarization of macrophage and exacerbated periodontal inflammation which could be reversed by D-ribose.

Automating bone loss measurement on periapical radiographs for predicting the periodontitis stage and grade

Automating bone loss measurement on periapical radiographs for predicting the periodontitis stage and grade

Periodontitis and Diabetes Differentially Affect Inflammation in Obesity

Periodontitis (PD) potentiates systemic inflammatory diseases and fuels a feed-forward loop of pathogenic inflammation in obesity and type 2 diabetes (T2D). Published work in this area often conflates obesity with obesity-associated T2D; thus, it remains unclear whether PD similarly affects the inflammatory profiles of these 2 distinct systemic diseases. We collected peripheral blood mononuclear cells (PBMCs) from cross-sectionally recruited subjects to estimate the ability of PD to affect cytokine production in human obesity and/or T2D. We analyzed 2 major sources of systemic inflammation: T cells and myeloid cells. Bioplex quantitated cytokines secreted by PBMCs stimulated with T cell– or myeloid-targeting activators, and we combinatorially analyzed outcomes using partial least squares discriminant analysis. Our data show that PD significantly shifts peripheral T cell– and myeloid-generated inflammation in obesity. PD also changed myeloid- but not T cell–generated inflammation in T2D. T2D changed inflammation in samples from subjects with PD, and PD changed inflammation in samples from subjects with T2D, consistent with the bidirectional relationship of inflammation between these 2 conditions. PBMCs from T2D subjects with stage IV PD produced lower amounts of T cell and myeloid cytokines compared with PBMCs from T2D subjects with stage II to III PD. We conclude that PD and T2D affect systemic inflammation through overlapping but nonidentical mechanisms in obesity, indicating that characterizing both oral and metabolic status (beyond obesity) is critical for identifying mechanisms linking PD to systemic diseases such as obesity and T2D. The finding that stage IV PD cells generate fewer cytokines in T2D provides an explanation for the paradoxical findings that the immune system can appear activated or suppressed in PD, given that many studies do not report PD stage. Finally, our data indicate that a focus on multiple cellular sources of cytokines will be imperative to clinically address the systemic effects of PD in people with obesity.

Prediabetes Associates with Matrix Metalloproteinase-8 Activation and Contributes to the Rapid Destruction of Periodontal Tissues.

The aim of this cross-sectional study was to investigate the relationship between periodontitis, potential periodontitis oral fluid biomarkers, and prediabetes. This study included 150 Greek adults aged 25 to 78 years who were tested with an Hemoglobin A1C (HBA1c) diagnostic system, an active-matrix metalloproteinase-8 (aMMP-8) point-of-care (PoC) test, and several salivary biomarkers enzyme-linked immunosorbent assay tests and gelatin zymography. A full-mouth clinical examination was performed to assess their periodontal and oral health status. The Kruskal-Wallis test was used to determine the statistically significant difference in the levels of periodontal oral fluid biomarkers between the different periodontitis stages, periodontitis grades, and the stages and grades of periodontitis combined. Spearman's rank correlation was performed to assess the strength and direction of the association between aMMP-8 and HbA1c levels (<5.7 and ≥5.7%) and with the other oral fluid biomarkers among patients with severe periodontitis. A two-sided p-value below 0.05 was considered statistically significant in this study. aMMP-8, but not total MMP-8 or other biomarkers, associated significantly with the stage and grade of periodontitis combined (p < 0.001, Kruskal-Wallis test). Among stage III grade C periodontitis patients, aMMP-8 levels were significantly positively correlated with prediabetes (Spearman's rho = 0.646, p = 0.044), total MMP-8 (rho = 0.636, p = 0.048), PMN Elastase (rho = 0.729, p = 0.017), total MMP-9 (rho = 0.721, p = 0.019), and total MMP-8/TIMP-1 molar ratio (rho = 0.879, p < 0.001). Prediabetic disease development can upregulate MMP-8 expression (total MMP-8) in rapidly progressing, severe periodontitis, where MMP-8 latent species are further activated into their active forms (aMMP-8). Simultaneously, several proinflammatory biomarker levels are elevated in this tissue-destructive biomarker cascade. This development is easily detectable online/in real-time within 5 minutes by aMMP-8 PoC testing at the dentist's office.

Developing a Prediction Model for Periodontal Disease Using Ordinal Random Forest

Background: Periodontitis, a common inflammatory disease affecting oral health, is a major public health concern. Early detection of this disease is highly important in order to achieve less invasive and less costly treatment. The ordinal nature of different levels of periodontitis is usually not considered in many studies. It is often recognized and used as a nominal variable, in which case some information related to the ordinal nature is ignored. The aim of this study was to use continuation ratio logistic and ordinal random forest (RF) models to predict the three stages of periodontitis. Methods: Overall, this study evaluated 300 patients referred to the Periodontology Department of Hamadan University, western Iran, between September 2016 and June 2018. The performance of continuous ratio logistic and ordinal forest models was evaluated using the same set of training and test data to predict different types of periodontitis (gingivitis, localized, and generalized periodontitis) based on input variables. Accuracy, kappa, gamma, Somers’d, and precision were utilized for comparison. Results: The results confirmed the higher predictive ability of the ordinal RF model compared to the logistic continuation ratio model for all scoring indices (accuracy of 0.87 vs. 0.80). Alveolar bone loss, attachment loss, probing pocket depth, simplified oral hygiene index, and plaque index were identified as the most important variables. Conclusion: Due to the ordinal nature of different levels of periodontal disease, the use of accurate prediction models such as ordinal RF is suggested since they can take into account the ordinal nature of the response in predicting and evaluating the effect of important variables. Ordinal RF is a well-suited machine learning technique for developing accurate predictive models of periodontal disease risk.