Glucose and lipid metabolism indexes and blood inflammatory biomarkers of patients with severe periodontitis: A cross‐sectional study
Xiaoyuan Guan, Xiane Wang, Yi Li, Jing-Ling Xu, Lu He, Li Xu, Xinran Xu, Huanxin Meng
Abstract
BACKGROUND: To investigate the relation of established glucose and lipid metabolism indexes and blood inflammatory biomarkers with severe periodontitis in systemically healthy patients. METHODS: Systemically healthy Stage III/IV periodontitis patients (case group) (n = 397), Stage II periodontitis patients (n = 36), and periodontally healthy subjects (control group) (n = 285) were recruited. A periodontal examination, complete blood cell examination, and blood biochemical examination were conducted for all participants. Full-mouth apical films were taken for the case group. Both the case and control groups were divided by age into younger (≤ 35 years) and elder subjects. Multiple logistic regression analysis and Pearson correlation analysis were conducted. A logistic least absolute shrinkage and selection operator (LASSO) model was constructed for the younger subgroups. RESULTS: Various glucose and lipid metabolism indexes and blood inflammatory biomarkers significantly differed between severe periodontitis patients and healthy controls, and the younger subgroups presented a greater degree of statistical differences than the elder ones. More pairs of periodontal parameters and blood indexes with significantly fair linear correlations were found in the younger patient subgroup. A logistic LASSO regression model containing eight blood indexes to assess a severe periodontitis outcome in younger subgroups showed satisfactory predictive ability. CONCLUSION: The present study revealed various glucose and lipid metabolism indexes and blood inflammatory biomarkers significantly differ between severe periodontitis patients and healthy controls, especially in the younger subgroups. A LASSO regression model could be a viable option to assess severe periodontitis risk for younger patients.