Risk assessment of lacunar infarct associated with oral conditions: A case control study focused on radiographic bone loss and Eichner classification.

Purpose: This study aimed to evaluate whether lacunar infarcts can be predicted from occlusal support and periodontal stage on images.

Methods: Seventy patients with lacunar infarcts and 300 participants without lacunar infarcts who underwent cerebral checkups at our university hospital were retrospectively reviewed. Lacunar infarcts were assessed using magnetic resonance images by a neuroradiologist. The number of teeth, occlusal support, and severity of radiographic bone loss (RBL) were evaluated using computed tomography. Occlusal support was classified according to the Eichner classification. Additionally, patient characteristics were investigated using medical charts and blood test reports. Records of clinical periodontal parameters, such as clinical attachment loss and bleeding on probing, were also evaluated.

Results: The severity of RBL and Eichner classification in patients with lacunar infarcts was significantly higher than that in individuals without lacunar infarcts (P<.01). Receiver operating characteristic analysis revealed that the cut-off values for predicting lacunar infarct were ≥ III in the severity of RBL and ≥B1 in the Eichner classification. The corresponding areas under the curve were 0.75 and 0.70, respectively. In multivariate analysis, the factors affecting the severity of RBL (≥ III) (odds ratio [OR], 8.1; 95% confidence interval [CI], 4.1-16.3; P<.001), and Eichner classification (≥B1) (OR, 1.9; 95% CI, 0.86-4.1; P<.05) were significantly associated with the occurrence of lacunar infarcts.

Conclusion: The severity of RBL and the Eichner classification may be helpful in predicting lacunar infarcts. Therefore, proper periodontal treatment and prosthodontic rehabilitation of missing teeth may prevent lacunar infarcts.