Automated Machine Learning to Develop Predictive Models of Metabolic Syndrome in Patients with Periodontal Disease.

Metabolic syndrome is experiencing a concerning and escalating rise in prevalence today. The link between metabolic syndrome and periodontal disease is a highly relevant area of research. Some studies have suggested a bidirectional relationship between metabolic syndrome and periodontal disease, where one condition may exacerbate the other. Furthermore, the existence of periodontal disease among these individuals significantly impacts overall health management. This research focuses on the relationship between periodontal disease and metabolic syndrome, while also incorporating data on general health status and overall well-being. We aimed to develop advanced machine learning models that efficiently identify key predictors of metabolic syndrome, a significant emphasis being placed on thoroughly explaining the predictions generated by the models. We studied a group of 296 patients, hospitalized in SCJU Sibiu, aged between 45-79 years, of which 57% had metabolic syndrome. The patients underwent dental consultations and subsequently responded to a dedicated questionnaire, along with a standard EuroQol 5-Dimensions 5-Levels (EQ-5D-5L) questionnaire. The following data were recorded: DMFT (Decayed, Missing due to caries, and Filled Teeth), CPI (Community Periodontal Index), periodontal pockets depth, loss of epithelial insertion, bleeding after probing, frequency of tooth brushing, regular dental control, cardiovascular risk, carotid atherosclerosis, and EQ-5D-5L score. We used Automated Machine Learning (AutoML) frameworks to build predictive models in order to determine which of these risk factors exhibits the most robust association with metabolic syndrome. To gain confidence in the results provided by the machine learning models provided by the AutoML pipelines, we used SHapley Additive exPlanations (SHAP) values for the interpretability of these models, from a global and local perspective. The obtained results confirm that the severity of periodontal disease, high cardiovascular risk, and low EQ-5D-5L score have the greatest impact in the occurrence of metabolic syndrome.

The Influence of Periodontal Disease on Oral Health Quality of Life in Patients with Cardiovascular Disease: A Cross-Sectional Observational Single-Center Study.

Background and Objectives: Cardiovascular disease is a leading cause of global death with a rising prevalence and a heavy economic burden. Periodontal disease has been associated with cardiovascular diseases­including incident coronary heart disease, peripheral artery disease and ischemic stroke. The study evaluates the quality of life of patients with cardiovascular and periodontal disease from the point of view of oral health by using the short version of the Oral Health Impact Profile (OHIP-14) questionnaire. Materials and Methods: This study included a total of 221 patients (61.86 ± 15.03 years old) selected from the Emergency Hospital of Sibiu, Romania. The participants self-completed the OHIP-14 questionnaire and they benefited from an oral health examination conducted to assess the presence and the severity of periodontal disease. Results: Out of the 147 patients with cardiovascular disease, 77.5% had periodontal disease (32.6% stage I, 29.2% stage II, and 15.6% stage III and IV). The presence of periodontal disease was associated with a lower oral-health-related quality of life (p < 0.001, ANOVA) and with a higher OHIP-14 score in patients with cardiovascular disease (18.67 ± 8.17, p < 0.001 ANOVA). No significant difference was observed concerning patient sex and background; however, age, body mass index and the lack of an appropriate oral hygiene routine had a strong association with the individual quality of life. The general OHIP-14 score was higher in patients with periodontal disease and associated cardiovascular disease, the presence of both cardiovascular and periodontal disease being associated with a lower quality of life. Conclusions: By increasing the patients' awareness to oral healthcare measures, better outcomes and improved oral-health-related quality of life could be observed.

Saliva pH and Flow Rate in Patients with Periodontal Disease and Associated Cardiovascular Disease.

BACKGROUND Periodontal disease, a frequent oral health problem, is connected with cardiovascular morbidity and mortality. This study aimed to assess the unstimulated saliva flow rate and saliva pH as markers of the severity of periodontal disease in patients with cardiovascular disease. MATERIAL AND METHODS A cohort of 155 patients (78 men and 77 women, aged 30-92 years) was included, and a structured questionnaire obtained information about their health status, oral healthcare behaviors, and eating habits. An oral examination was performed to assess periodontal status and presence of dental calculus. The unstimulated whole salivary flow rate and salivary pH were measured. An oral hygienization was performed, and 3 months later, salivary flow rate and pH were reevaluated. RESULTS A severe form of periodontal disease was found in 22.4% of patients. Disease severity was strongly correlated with low pH values (6.25 in stage IV periodontal disease), lower salivary flow rate (0.28 mL/min), smoking, poor oral hygiene habits and obesity, with no significant differences by sex. We observed a significant increase of pH (up to 6.30±0.17) in patients with severe periodontal disease (P=0.001) and salivary flow rate values (0.29±0.07 mL/min; P=0.014) 3 months after oral hygienization. There was a strong association between the severity of periodontal disease and presence of cardiovascular disease (P=0.001). CONCLUSIONS Our study suggests that the decrease of salivary flow rate and pH level might be associated with the severity of periodontal disease.