BioRisk-S (Biological Risk-Stomatognathic): A Predictive Algorithm for Early Systemic Detection of Stomatognathic Dysfunction.

BACKGROUND: Functional imbalance within the stomatognathic system can develop long before clinical symptoms become evident. Subtle biological changes, such as low-grade inflammation or metabolic disturbance, may precede gingival inflammation, temporomandibular discomfort, or masticatory muscle sensitivity. This study introduces the BioRisk-S (Biological Risk-Stomatognathic System) algorithm, a predictive model designed to identify early systemic alterations associated with the subclinical stage of stomatognathic dysfunction. METHODS: A total of 260 clinically healthy adults without apparent stomatognathic disorders were enrolled and evaluated at baseline (T0) and re-examined after six months (T1). Routine laboratory tests were performed to determine high-sensitivity C-reactive protein (hs-CRP), neutrophil-to-lymphocyte ratio (NLR), and 25-hydroxyvitamin D levels. These biomarkers were integrated into the BioRisk-S algorithm to estimate systemic biological imbalance. Follow-up examinations focused on detecting early functional changes, including gingival inflammation, signs of temporomandibular joint (TMJ) dysfunction, and masticatory muscle tenderness. RESULTS: Participants with higher baseline BioRisk-S scores showed significantly higher hs-CRP and NLR values, as well as lower vitamin D levels, indicating a mild but persistent inflammatory profile. After six months, these individuals exhibited early gingival inflammation, muscle tenderness, or mild TMJ discomfort more frequently than those with low BioRisk-S values (p < 0.01). The predictive model demonstrated good accuracy for detecting early biological imbalance preceding clinical dysfunction, with an area under the curve (AUC) of 0.84 (95% CI: 0.78-0.89). CONCLUSIONS: The BioRisk-S algorithm represents a feasible, low-cost tool for early systemic screening of functional imbalance within the stomatognathic system. By integrating routine laboratory parameters, this method may help identify individuals at risk before the onset of visible symptoms, supporting preventive and personalized approaches in oral and systemic health management.