Glucose and lipid metabolism indexes and blood inflammatory biomarkers of patients with severe periodontitis: A cross-sectional study.
biomarkers
glucose metabolism disorders
lipid metabolism disorders
periodontitis
Journal
Journal of periodontology
ISSN: 1943-3670
Titre abrégé: J Periodontol
Pays: United States
ID NLM: 8000345
Informations de publication
Date de publication:
04 2023
04 2023
Historique:
revised:
16
08
2022
received:
13
05
2022
accepted:
13
09
2022
medline:
26
4
2023
pubmed:
6
11
2022
entrez:
5
11
2022
Statut:
ppublish
Résumé
To investigate the relation of established glucose and lipid metabolism indexes and blood inflammatory biomarkers with severe periodontitis in systemically healthy patients. 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. 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 36334021
doi: 10.1002/JPER.22-0282
doi:
Substances chimiques
Glucose
IY9XDZ35W2
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
554-563Informations de copyright
© 2022 American Academy of Periodontology.
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