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The Prevalence of Alveolar Ridge Defects According to Seibert's Classification: A Cross-Sectional Study
Mohamed Farith N1, Kalyani Ramkumar Sadhana1, Vidyashree V Nandini1
1Prosthodontics, SRM Kattankulathur Dental College and Hospital, SRM Institute of Science and Technology, Chengalpattu, IND.
Abstract:
Background and objective Alveolar ridge defects in partially edentulous patients present significant challenges in prosthodontic treatment planning. Seibert's classification system provides a structured approach to categorizing these defects based on the buccolingual and apico-coronal dimensions of the ridge. Accurate classification is crucial for determining appropriate treatment strategies for implant placement, fixed prosthesis, or tissue augmentation. Hence, this study aimed to assess and classify tissue defects in partially edentulous ridges based on Seibert's classification Methods A cross-sectional study was conducted to measure and classify alveolar ridge defects in partially edentulous patients by using Seibert's classification system. Patients aged 18 years and above with partially edentulous ridges requiring prosthodontic treatment were considered for inclusion. Individuals with systemic conditions affecting healing, completely edentulous patients, and those with active periodontal infections were excluded. Impressions of dental arches were obtained, and the alveolar ridge dimensions were measured using digital calipers. Results The study included 122 participants, with a slight male predominance (n=65, 53.3%). The classification of alveolar ridge defects revealed that 71 (58.2%) were Class III, 33 (27.0%) were Class I, and 18 (14.8%) were Class II. A chi-square analysis indicated no significant association between sex and the classification of alveolar ridge defects (p=0.410). Conclusions The prevalence of Class III alveolar ridge defects highlights the need for tailored treatment approaches in prosthetic rehabilitation. While gender differences were observed, they did not significantly influence defect classification. Future research should investigate additional demographic factors to enhance understanding and improve treatment strategies.
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