Published online Dec 15, 2023. doi: 10.4239/wjd.v14.i12.1793
Peer-review started: August 8, 2023
First decision: September 29, 2023
Revised: October 20, 2023
Accepted: November 27, 2023
Article in press: November 27, 2023
Published online: December 15, 2023
Processing time: 128 Days and 7.1 Hours
Periodontitis is a complication of type 2 diabetes mellitus (T2DM). With lifestyle changes and the acceleration of the aging process, the prevalence of periodontitis and diabetes is increasing annually.
Periodontitis can lead to tooth loosening and loss, decline in oral function, and reduced living standards.
This study aimed to explore and analyze the factors influencing periodontal disease in patients with T2DM, and construct prediction models for the risk of periodontal disease in patients with T2DM.
We conducted a retrospective study in patients with T2DM hospitalized in our hospital to analyze the factors influencing periodontitis in patients with T2DM. We used random forest and logistic regression prediction models to assess the risk of specific factors in periodontitis.
This study found that the factors influencing periodontal disease in patients with T2DM were age, brushing frequency, education level, and glycosylated hemoglobin, total cholesterol, and triglyceride levels. The prediction models both had good predictive value.
In this study, a random forest model was established and compared to a logistic regression model. The results showed that the random forest and logistic regression models had good predictive value and can accurately predict the risk of periodontitis in patients with T2DM.
In the future, we will expand the sample size, combine samples from multiple regions, and include additional influencing factors to build a more complete prediction model.