Factors Associated with Apical Periodontitis: A Multilevel Analysis.

Area of Science:

• Endodontic research
• Dental statistics
• Public health dentistry

Background:

• Statistical oversight in endodontic research often ignores cluster effects.
• Apical periodontitis (AP) research can benefit from advanced statistical methods to account for patient and tooth-level variations.

Purpose of the Study:

• To explore the application of multilevel modeling in endodontic research.
• To investigate tooth-level and patient-level factors influencing apical periodontitis (AP).

Main Methods:

• Digital panoramic radiographs from a dental hospital database were analyzed.
• Two calibrated examiners assessed root filling quality and periapical health using the periapical index.
• Multilevel modeling was employed with tooth-level and patient-level predictors.

Main Results:

• Analysis included 6409 teeth; the predicted probability of AP was 0.42%.
• Significant patient-level variability in AP was observed (P < .05), with patients accounting for 53.16% of this variability.
• Posterior tooth location, inadequate root filling, and patient age were significantly associated with AP (P < .05).

Conclusions:

• Multilevel modeling is a valid and efficient statistical approach for analyzing AP data.
• While overall AP probability is low, significant individual variation exists.
• Posterior teeth, poor root filling quality, and advanced patient age are key factors associated with increased AP risk.