Development and Internal Validation of an Exploratory Nomogram for Cerebral Small Vessel Disease Burden Using Periodontal Parameters.

Cerebral small vessel disease (CSVD) is a major cause of stroke and cognitive decline, but the contribution of periodontal disease to the overall CSVD burden remains unclear. We aimed to develop and internally validate an exploratory clinical nomogram incorporating periodontal parameters to estimate a high CSVD burden. A total of 234 individuals underwent magnetic resonance imaging (MRI) for assessment of total CSVD burden (score 0-4). Periodontitis severity and retained tooth count were recorded. Optimal predictors selected using the least absolute shrinkage and selection operator (LASSO) regression were entered into multivariable logistic regression to construct the nomogram, which was evaluated for discrimination, calibration, and clinical utility. Restricted cubic spline analysis demonstrated a linear dose-response relationship between tooth loss and high CSVD burden (P for non-linearity = 0.332). Multivariable analysis identified advanced age and hypertension as independent prognostic factors; however, the associations of severe periodontitis (P = 0.580) and severe tooth loss (P = 0.112) were attenuated and were not independently associated with high CSVD burden after adjustment. The nomogram demonstrated modest discrimination (area under the curve = 0.675) and favorable bootstrap-validated calibration (mean absolute error = 0.038). Decision curve analysis suggested potential clinical utility across selected risk thresholds, although interpretation remains exploratory because of the absence of external validation. Although severe periodontitis and tooth loss showed univariable associations with high CSVD burden, they were not independent predictors after multivariable adjustment. This exploratory nomogram provides a preliminary visualization framework for individualized risk stratification and warrants further external validation before clinical implementation.