Beyond Side-Specific Distributions: Patient-Level Bilateral Agreement of Mandibular Third-Molar Classifications

Background/Objectives: The right and left mandibular third molars of the same patient may be expected to have similar radiographic characteristics. This study aimed to determine whether side-specific distributions of mandibular third-molar classifications correspond to patient-level bilateral agreement and whether identical Pederson scores may conceal differences in their underlying radiographic components. Methods: This retrospective cross-sectional study included 800 mandibular third molars from 400 patients with bilateral mandibular third molars. Panoramic radiographs were evaluated separately for each side using the Winter classification, Pell-Gregory classification, and Pederson difficulty index. Bilateral agreement was assessed using raw agreement, Cohen's kappa, and weighted kappa coefficients, while side-specific distributions were compared using marginal homogeneity tests. Results: Raw agreement was 59.75% for Winter angulation, 56.0% for the combined Pell-Gregory classification, 69.5% for the Pederson difficulty group, and 48.75% for the total Pederson score. Kappa values were 0.42, 0.44, and 0.43 for Winter angulation, the combined Pell-Gregory classification, and the Pederson difficulty group, respectively. Complete agreement across all three systems was observed in 170 patients (42.5%). The Pell-Gregory ramus relationship showed substantial agreement (κ = 0.64), whereas depth showed moderate agreement (κ = 0.41). Left-side Pederson scores were significantly higher than right-side scores (p = 0.013), although the mean difference was only 0.15 points. Conclusions: Bilateral mandibular third molars showed only moderate patient-level agreement. Similarity in category distributions at the sample level should not be interpreted as within-patient agreement, and identical Pederson scores may conceal differences in angulation and position. Each mandibular third molar should therefore be evaluated separately, particularly in cases close to classification thresholds.