The added value of periodontal measurements for identification of diabetes among Saudi adults

Relationship Between Diabetes Mellitus and Periodontal/Peri-Implant Disease: A Contemporaneous Review

The prevalence of diabetes mellitus (DM), a major chronic disease and a leading cause of death and disability around the world, is rising. According to the latest data, the global prevalence of DM has increased to 463 million (9.3% of adults) in 2019 and is estimated to reach 700 million by 2045. Periodontal disease, result of periodontium inflammation, is a common, chronic disease and has long been considered one of the complications of DM. Moreover, literature reflects a spectrum of conflicting viewpoints on the effect of diabetic conditions on the implant treatment strategies. The current review aims to update the recent epidemiologic evidence regarding the relationship between DM and periodontal/peri-implant disease, emphasising the effects of glycaemic control on the severity of these diseases and describing the pathobiological mechanisms underlying this association. This review's findings indicate a bidirectional relationship between DM and periodontal/peri-implant disease and that this relationship seems causal, implying that controlling these two diseases might help prevent each other's incidence. Additionally, the severity of periodontal/peri-implant disease is directly related to metabolic control. Although patients with diabetes can obtain implant success similar to those in systemically healthy individuals, an increased risk of peri-implantitis has been reported in DM patients. Therefore, the importance of glycaemic control and maintaining proper oral hygiene cannot be overstated.

Oral health status and risk of incident diabetes: a prospective cohort study of 213,389 individuals aged 45 and over

AIMS

To examine whether simple measures of oral health are associated with incident diabetes.

METHODS

This prospective cohort study linked data from the 45 and Up Study, Australia, to administrative health records. The study participants were 213,389 men and women, aged ≥ 45 years, with no diabetes at baseline. The oral health of participants was assessed by questionnaire. Incident diabetes cases were ascertained based on self-report in follow-up questionnaires, linked data on medical and pharmaceutical claims, and hospitalisation data up until 2019. The association between oral health and incident diabetes were calculated using multivariable cox proportional hazards models.

RESULTS

During 2,232,215 person-years of follow-up, 20,487 (9.6%) participants developed diabetes. Compared with those with ≥20 teeth, the adjusted hazard ratio (aHR) for incident diabetes was 1.12 (95% Confidence Interval (CI): 1.08, 1.17) for 10-19 teeth, 1.20 (1.14, 1.26) for 1-9 teeth and 1.15 (1.09, 1.21) for no teeth. Compared with those with excellent/very good teeth and gums, the aHR for incident diabetes was 1.07 (1.03, 1.12) for fair and 1.13 (1.07, 1.20) for poor teeth and gums.

CONCLUSIONS

Simple measures of oral health were associated with risk of developing diabetes, demonstrating the potential importance of oral health screening for diabetes prevention.

Can periodontal measures assist in the identification of adults with undiagnosed hyperglycaemia? A systematic review

AIM

The aim of this review was to answer the following question: Can periodontal measures be used to identify dental patients with undiagnosed hyperglycaemia?

MATERIALS AND METHODS

Systematic searches of electronic databases and the grey literature were carried out to identify studies developing and/or validating prediction models, based on any periodontal measure, to screen adults for undiagnosed hyperglycaemia (pre-diabetes and diabetes). Risk of bias was evaluated using the PRediction mOdel risk-of-Bias ASsessment Tool (PROBAST).

RESULTS

Ten studies were identified, of which eight were model development studies. The remaining two studies reported the external validation of one existing prediction model. The periodontal prediction model with some evidence of external validation showed moderate diagnostic performance in the development sample but lower performance in the external validation samples. According to PROBAST, all studies had high risk of bias mainly due to methodological limitations in data analysis, but also in the recruitment of participants, choice and measurement of periodontal predictors and diabetes.

CONCLUSIONS

There is a need for more robust external validation studies of existing prediction models adhering to current recommendations. Dental professionals who see patients at risk of diabetes and routinely collect periodontal measures have an important role to play in their identification and referral.