ArticleJournal of Indian Society of Periodontology
Efficacy of surgical stripping and diode laser-assisted gingival depigmentation techniques in terms of patient's perspective, clinical and histological evaluation: A randomized clinical study.
Article in Journal of Indian Society of Periodontology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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3 authors.
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Abstract
Introduction: Gingival melanin pigmentation is one of the most important factors for esthetically sensitive candidates. Literature reveals various depigmentation techniques which are predominantly utilized for clinical assessment only. The present randomized clinical study was planned to evaluate the efficacy of surgical stripping and diode laser-assisted gingival depigmentation techniques in terms of patient's perspective, clinical, and histological outcome. Materials and Methods: Twenty patients with bilateral labial physiological gingival melanin pigmentation extended from the distal aspect of #13-23, 33-43 were selected as for the study. Dummet Oral Pigmentation Index (DOPI) and Hedin Melanin Index (HMI) were recorded, and incisional biopsies were taken at baseline to evaluate the density of melanin pigmentation. Both arches were equally treated by surgical stripping assisted gingival depigmentation and diode laser-assisted gingival depigmentation (SSAGD and DLAGD). Patients were re-evaluated at 3 and 6 months postoperatively for DOPI and HMI and at 6 months for the density of melanin pigmentation. Visual Analog Scale (VAS) was evaluated during surgery, 1 Results: DOPI and HMI were reported to be statistically significant ( Conclusion: SSAGD is best in terms of clinical and histological outcomes and induces less postoperative pain, and repigmentation is slow as compared to DLAGD.
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