Personalized Periodontitis Scoring With Mixed-Effect Risk Stratification
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Solution Overview
Problem
Current diagnostic tools for periodontitis fail to account for co-morbidities, local and systemic risk factors, and demographic information, limiting the ability to stratify patients and sites for personalized therapeutic approaches.
Innovation Solution
A method for patient- and site-specific assessment of microbial imbalances in periodontitis using genetic workflows, combining bacterial species quantification, clinical and demographic parameters, and a reference database to calculate a personalized periodontitis score through a linear mixed-effect model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current diagnostic tools are used for periodontitis, then the diagnostic process is simple, but the ability to stratify patients and sites for personalized therapy is insufficient
Solution Approach 1:
The patent combines multiple diagnostic elements into a unified periodontitis score: microbial profile data from genetic workflows, clinical parameters (pocket depth, bleeding on probing), demographic information (age, smoking status), and treatment history are merged into a single predictive model that outputs a standardized score for patient stratification
Solution Approach 2:
The patent introduces a linear mixed-effect model as an intermediary computational layer that processes raw microbial and clinical data, transforms them into a standardized periodontitis score, and enables comparison across different patients and sites while accounting for random effects and variability
2Adaptability or versatility
If personalized periodontitis scoring is implemented, then targeted therapy can be optimized, but the diagnostic and treatment planning process becomes more complex
Solution Approach 1:
The patent enables site-specific assessment by calculating periodontitis scores for individual periodontal sites rather than just overall patient status, allowing differentiation of disease activity and risk across different locations in the mouth to guide localized therapeutic interventions
Solution Approach 2:
The patent performs preliminary risk stratification by calculating the periodontitis score before treatment initiation, identifying high-risk patients and sites in advance, and enabling proactive treatment planning that prevents disease progression rather than reacting to established damage
3Loss of information
If microbial profile analysis is performed without accounting for risk factors, then the analysis is straightforward, but the clinical relevance for personalized therapy is limited
Solution Approach 1:
The patent creates a universal periodontitis scoring system that can accommodate multiple types of input data (microbial profiles from different genetic workflows, various clinical parameters, demographic factors) and produces a standardized output that can be applied across different patient populations and clinical settings
Data Source
AI summary
The present disclosure concerns the development of personalised periodontitis score to assess the individual level of microbial imbalances in periodontal pockets and/or saliva of a specific individual at a defined stage of treatment, relative to a predicted expected score for the average patient with similar systemic and local medical characteristics and demographic profile. The microbial profile obtained from genetic/genomic information is combined with clinical and demographical information in a mixed-effect model to obtain a predicted value and a standard error for a given set of clinical parameters. The comparison between this predicted average score and the individual patient personalised periodontitis score informs about the relative periodontal disease activity in this site and/or patient and thus allows for the stratification of the local site and/or the patient into risk categories and for the recommendation of targeted patient-specific treatment modalities.