Increased prevalence of periodontitis with hypouricemic status: findings from the Korean National Health and Nutrition Examination Survey, 2016-2018.

PURPOSE: The aim of this study was to investigate the relationship between serum uric acid (SUA) levels and the risk of periodontitis in Korean adults using data from the Korean National Health and Nutrition Examination Survey (KNHANES). METHODS: This cross-sectional study used data from the KNHANES 2016-2018 and analysed 12,735 Korean adults aged ≥19 years who underwent oral examinations. Hypouricemia was defined as SUA <3 mg/dL in men and <2 mg/dL in women, and hyperuricemia was defined as SUA ≥7 mg/dL in men and ≥6 mg/dL in women. RESULTS: The weighted prevalence of hypouricemia and hyperuricemia was 0.6% and 12.9%, respectively. The overall weighted periodontitis rate was 30.5%. The frequency of periodontitis in subjects with hypouricemia, normouricemia, and hyperuricemia were 51.1%, 30.3%, and 30.6%, respectively. Study participants with hypouricemia were significantly older, had significantly fasting blood glucose levels, and had better kidney function than non-hypouricemic participants. In univariate logistic regression analyses, hypouricemia was associated with periodontitis, but hyperuricemia was not. The fully adjusted model revealed that the adjusted odds ratio of hypouricemia for periodontitis was 1.62 (95% confidence interval, 1.13-2.33), while the relationship between hyperuricemia and periodontitis in the multivariable logistic regression model was not significant. CONCLUSIONS: The results of this study suggest that hypouricemia is associated with an increased risk of periodontitis.

Diagnosis of Early Glottic Cancer Using Laryngeal Image and Voice Based on Ensemble Learning of Convolutional Neural Network Classifiers.

OBJECTIVES: The purpose of study is to improve the classification accuracy by comparing the results obtained by applying decision tree ensemble learning, which is one of the methods to increase the classification accuracy for a relatively small dataset, with the results obtained by the convolutional neural network (CNN) algorithm for the diagnosis of glottal cancer. METHODS: Pusan National University Hospital (PNUH) dataset were used to establish classifiers and Pusan National University Yangsan Hospital (PNUYH) dataset were used to verify the classifier's performance in the generated model. For the diagnosis of glottic cancer, deep learning-based CNN models were established and classified using laryngeal image and voice data. Classification accuracy was obtained by performing decision tree ensemble learning using probability through CNN classification algorithm. In this process, the classification and regression tree (CART) method was used. Then, we compared the classification accuracy of decision tree ensemble learning with CNN individual classifiers by fusing the laryngeal image with the voice decision tree classifier. RESULTS: We obtained classification accuracy of 81.03 % and 99.18 % in the established laryngeal image and voice classification models using PNUH training dataset, respectively. However, the classification accuracy of CNN classifiers decreased to 73.88 % in voice and 68.92 % in laryngeal image when using an external dataset of PNUYH. To solve this problem, decision tree ensemble learning of laryngeal image and voice was used, and the classification accuracy was improved by integrating data of laryngeal image and voice of the same person. The classification accuracy was 87.88 % and 89.06 % for the individualized laryngeal image and voice decision tree model respectively, and the fusion of the laryngeal image and voice decision tree results represented a classification accuracy of 95.31 %. CONCLUSION: The results of our study suggest that decision tree ensemble learning aimed at training multiple classifiers is useful to obtain an increased classification accuracy despite a small dataset. Although a large data amount is essential for AI analysis, when an integrated approach is taken by combining various input data high diagnostic classification accuracy can be expected.

Retrospective analysis of the effects of non-communicable diseases on periodontitis treatment outcomes.

PURPOSE: We retrospectively analysed patients' dental and periodontal status according to the presence of non-communicable diseases (NCDs) and the effects of NCDs on periodontal treatment outcomes. Factors influencing disease recurrence were investigated using decision tree analysis. METHODS: We analysed the records of patients who visited the Department of Periodontology, Pusan National University Dental Hospital from June 2014 to October 2019. As baseline subjects, 1,362 patients with periodontitis and who underwent full-mouth periodontal examinations before periodontal treatment were selected. Among them, 321 patients who underwent periodontal examinations after the completion of periodontal treatment and 143 who continued to participate in regular maintenance were followed-up. RESULTS: Forty-three percent of patients had a NCD. Patients without NCDs had more residual teeth and lower sum of the number of total decayed, missing, filled teeths (DMFT) scores. There was no difference in periodontal status according to NCD status. Patients with a NCD showed significant changes in the plaque index after periodontal treatment. The decision tree model analysis demonstrated that osteoporosis affected the recurrence of periodontitis. CONCLUSIONS: The number of residual teeth and DMFT index differed according to the presence of NCDs. Patients with osteoporosis require particular attention to prevent periodontitis recurrence.

A decision tree to identify the combinations of non-communicable diseases that constitute the highest risk for dental caries experience: A hospital records-based study.

To investigate whether dental status, represented by the DMFT score, was affected by the presence of NCDs and determined the NCDs that had a greater impact on the DMFT score. This retrospective cross-sectional study included a total of 10,017 individuals. The presence of NCDs was investigated based on self-reported medical history recorded on each patient's dental hospital record. Individual DMFT score was evaluated on the basis of the dental records and panoramic radiographs. The data were further analyzed using multiple regression analysis and chi-squared automatic interaction detection (CHAID) analysis. A total of 5,388 individuals had more than one NCD among hypertension (HT), diabetes mellitus (DM), hyperlipidemia, cardiovascular disease (CVD), and osteoporosis. The average DMFT score was 8.62 ± 7.10 in the NCD group, significantly higher than that in those without NCD (5.53 ± 5.48) (P < 0.001). In the regression analysis, age, NCDs, and psychiatric problems were selected as risk factors of DMFT score. In the CHAID decision tree analysis, age was the risk factor that most influenced the DMFT score. HT was the most influential factor in a newly generated decision tree excluding age, and osteoporosis, DM, and CVD were important risk factors acting in the subgroups. Patients with NCD had worse dental conditions than those who did not, and some combinations of NCDs related highest risk for a dental caries-related index. In clinical practice, dentists should provide meticulous care for dental caries in elderly patients with NCDs, especially when certain diseases, such as HT, osteoporosis, DM, and CVD, are present together.

Association between body mass index and fitness in Korean adults according to the lump mean value and Gaussian fitting.

The aim of this study was to determine the body mass index (BMI) for the best fitness and effective exercise. This study analyzed data from the Korean national fitness assessment by the Korea Institute of Sport Science (2017). The fitness tests considered were sit-up, standing long jump (SLJ), 20-m multi-stage shuttle run (20-m MSSR), and 10-m shuttle run (10-m SR) tests. The BMIs for the best fitness and widths of the fitness distributions were calculated using the lump mean value and Gaussian fitting. The values of BMI (kg/m2) associated with the best sit-up, SLJ, 20-m MSSR, and 10-m SR scores were 23.4, 22.6, 22.2, and 22.6 for males and 19.0, 18.5, 18.6, and 18.6 for females. The widths (kg/m2) of the sit-up, SLJ, 20-m MSSR, and 10-m SR distributions were 3.65, 3.42, 3.73, and 2.86 for males and 4.84, 4.88, 4.45, and 4.35 for females. The results show that the BMI can be reduced the most and fitness can be increased effectively by the 20-m MSSR for males and the SLJ for females, which could be used to establish personal exercise aims.

Serum Levels of Interleukin-6 and Titers of Antibodies Against Porphyromonas gingivalis Could Be Potential Biomarkers for the Diagnosis of Oral Squamous Cell Carcinoma.

It has been suggested that Porphyromonas gingivalis (P. gingivalis), a keystone pathogen in chronic periodontitis, is associated with a variety of cancers, including oral cancer. Recently, studies have shown the effects of persistent exposure to P. gingivalis on the promotion of tumorigenic properties of oral epithelial cells, suggesting that chronic P. gingivalis infection is a potential risk factor for oral cancer. On the other hand, Fusobacterium nucleatum (F. nucleatum), one of the major periodontal pathogens, has emerged as an important factor in the colon cancer progression. Here, we investigated the diagnostic potential of serum immunoglobulin G antibody against periodontal pathogens, P. gingivalis and F. nucleatum, and serum IL-6 for oral squamous cell carcinoma (OSCC). An enzyme-linked immunosorbent assay (ELISA) was used to determine and compare the serum levels of interleukin 6 (IL-6), F. nucleatum IgG, and P. gingivalis IgG in 62 OSCC patients with 46 healthy controls. The serum levels of P. gingivalis IgG and IL-6 were higher in OSCC patients than in non-OSCC controls, and the difference was statistically significant. In addition, a high serum level of IL-6 was associated with a worse prognosis in OSCC patients. Thus, P. gingivalis IgG and IL-6 could be utilized as potential serum biomarkers for the diagnosis of OSCC, and the serum level of IL-6 contributes to improved prognostic performance.

Oral Administration of Porphyromonas gingivalis, a Major Pathogen of Chronic Periodontitis, Promotes Resistance to Paclitaxel in Mouse Xenografts of Oral Squamous Cell Carcinoma.

Chemotherapy is not a first-line therapy for oral squamous cell carcinoma (OSCC), which is the most common type of oral cancer, because most OSCC shows resistance to chemotherapeutic reagents. Inflammatory signals are suggested to be associated with chemoresistance as well as carcinogenesis in many different cancers, and thus chronic periodontitis, the most common chronic inflammatory disease of the oral cavity, could modulate responsiveness to chemotherapeutic agents used against oral cancer. This study was performed to define the role of chronic periodontitis in oral cancer progression and to determine the responsiveness of oral cancer to a chemotherapeutic reagent. First, we quantified the tumor growth rate and changes in serum cytokine profiles of mice administered Porphyromonas gingivalis, a major pathogen of chronic periodontitis. Compared with uninfected mice, the mice that were chronically administered P. gingivalis showed increased resistance to paclitaxel and a decreased tumor growth rate. In addition, P. gingivalis-treated mice exhibited higher serum levels of interleukin-6 (IL-6) than uninfected mice. Furthermore, the sensitivity of tumor xenografts to paclitaxel in mice administered P. gingivalis was dramatically increased when the mice were administered ibuprofen, an anti-inflammatory drug which supports the modulatory effect of periodontal pathogen-induced inflammation in chemoresistance.