Mapping sequential patterns of periodontal breakdo using longitudinal electronic health records data.

Objective: To identify probabilistic, sequential patterns of periodontal breakdown using sequential pattern mining (SPM) on a large longitudinal cohort. Method and materials: Electronic health records from 19,428 patients with periodontitis (20112022) were analyzed. A custom SPM algorithm was develo...

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Publicado en:Quintessence International Vol. 57; no. 5; pp. 378 - 389
Autores principales: Chatzopoulos, Georgios S., Wolff, Larry F.
Formato: research tables/charts Journal Article
Publicado: Quintessence Publishing Company Inc. May2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2026
      vid: 57
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      pub: Quintessence Publishing Company Inc.
      place: Batavia, Illinois
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        10.3290/j.qi.b6961701
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        atl: Mapping sequential patterns of periodontal breakdo using longitudinal electronic health records data.
      aug:
        au:
          Chatzopoulos, Georgios S.
          Wolff, Larry F.
        affil: Associate Professor, Department of Developmental and Surgical Sciences, Division of Periodontology, School of Dentistry, University of Minnesota, Minneapolis, MN, USA
      sug:
        subj:
          Algorithms
          Data Mining Methods
          Electronic Health Records
          Periodontal Diseases Diagnosis
          Disease Progression
          Human
          United States
          Data Analysis, Statistical
          Retrospective Design
          Record Review
          Prospective Studies
          Descriptive Statistics
          Biomechanics
          Mandible Physiology
          Tooth Mobility
          Furcation Defects
          Incisor
          Cuspid
          Inflammation
          Hemorrhage
      ab: Objective: To identify probabilistic, sequential patterns of periodontal breakdown using sequential pattern mining (SPM) on a large longitudinal cohort. Method and materials: Electronic health records from 19,428 patients with periodontitis (20112022) were analyzed. A custom SPM algorithm was developed to identify frequent temporal subsequences of tooth mobility and furcation involvement, enforcing strict temporal precedence. "High-risk" states (eg, generalized clinical attachment loss [CAL] > 3.0 mm) were evaluated as precursors to localized failure. Association rules were ranked by confidence (conditional probability). Results: The analysis revealed distinct biomechanical cascading patterns. In the mandibular anterior sextant, mobility in the central incisors was a strong probabilistic precursor to subsequent failure in the lateral incisors and canines (confidence 7.3%). Asignificant "antagonistic cascade" was identified, where mandibular incisor mobility preceded maxillary incisor instability (confidence 8.1%). For molars, furcation involvement acted as a specific temporal sentinel for future mobility (confidence ~5% to 6%). Generalized high CAL was the strongest predictor of localized failure (confidence 18.9%), significantly outperforming active inflammation (bleeding on probing) as a driver of mechanical instability. Conclusion: Progressive biomechanical compromise (such as tooth mobility and advanced furcation involvement) follows predictable, probabilistic sequential patterns. The identification of specific "sentinel events," such as mandibular incisor mobility and molar furcation involvement, allows for a shift from reactive site-by-site management to predictive intervention. Clinical relevance: These findings underscore the critical role of generalized attachment loss in driving localized mechanical failure cascades.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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