Document Type : Original Article
Authors
1
Department of Stomatology, Institute of Medical Sciences of Villa Clara, Santa Clara, Cuba
2
Department of Stomatology, University of Medical Sciences of Havana, Havana, Cuba
10.30485/ijsrdms.2026.566777.1693
Abstract
Background and aim: Ridge preservation and guided bone regeneration (GBR) are paramount to predictable hard and soft tissue outcomes in implant dentistry, especially with the increasing use of biologics and digital diagnostics. The present study aimed to quantitatively assess clinical procedures, treatment outcomes, workflow productivity, and clinician satisfaction in relation to RP, GBR, the application of biologics, and AI-supported diagnostics.
Material and methods: A structured questionnaire were used in a cross-sectional study involving 410 dental clinicians. The sample size was deemed sufficient using Cochran's formula. Information on ridge preservation protocols, GBR procedures, soft tissue augmentation, AI-assisted diagnostics, outcome measurements, composite documentation workflow, billing flow, and clinical efficiency and satisfaction was collected. Summary statistics were conducted, and findings were expressed in frequencies and percentages.
Results: Clinicians reported high patient satisfaction after regenerative procedures, with predictable ridge-width maintenance and a measurable increase in keratinized tissue. Favorable results were attributed mainly to careful assessment of the defect, selection of an optimal graft and biologics, and attention to surgical details. However, difficulties remained in soft-tissue handling, the biological cost of musculocutaneous flaps and their availability, documentation adherence, and billing patterns.
Conclusions: In this regard, effective prevention and treatment of contaminated wound environments could be improved by precise diagnostics, protocol standardization, and the sensible use of biologics, as well as by integrating AI tools to address workflow and cost conundrums, thereby improving clinical efficiency and predictability.
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