Root Coverage for Single Deep Gingival Recessions: Outcomes Based on a Decision-Making Algorithm
Aim. The aim of this study is to report root coverage outcomes in single deep gingival recessions (GR) following a proposed decision-making algorithm. Materials and Methods. A retrospective, practice-based study included single deep (≥5 mm) Miller Class II and III defects. The step-by-step decision-...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | International Journal of Dentistry |
| Online Access: | http://dx.doi.org/10.1155/2019/1830765 |
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| author | João B. César Neto Marília C. Cavalcanti Ricardo T. Sekiguchi Claudio M. Pannuti Giuseppe A. Romito Dimitris N. Tatakis |
| author_facet | João B. César Neto Marília C. Cavalcanti Ricardo T. Sekiguchi Claudio M. Pannuti Giuseppe A. Romito Dimitris N. Tatakis |
| author_sort | João B. César Neto |
| collection | DOAJ |
| description | Aim. The aim of this study is to report root coverage outcomes in single deep gingival recessions (GR) following a proposed decision-making algorithm. Materials and Methods. A retrospective, practice-based study included single deep (≥5 mm) Miller Class II and III defects. The step-by-step decision-making algorithm led to a choice among three different flap designs (coronally advanced flap (CAF), double papilla envelope flap (DPE) or modified lateral sliding flap (LSF)) used with a connective tissue graft. Recession depth (RD) at 6 months follow-up and the corresponding root coverage (RC) were the primary outcomes assessed. Results. Sixteen GR defects were included, with baseline RD of 6.7 ± 1.8 mm. Six months postoperatively, RD was significantly reduced to 1.2 ± 0.8 mm (p<0.05). Mean RC was 81.7 ± 13.0%, without significant differences between Miller Class II (87.1 ± 9.2%; n=9) and Class III (74.6 ± 14.5%; n=7) GRs (p=0.07). Postoperatively, keratinized tissue width increase was greater for LSF (3.5 ± 1.1) and DPE (4.2 ± 1.4 mm) than for CAF (1.9 ± 0.9 mm). Conclusions. Following the proposed decision-making algorithm, root coverage outcomes for GR defects ≥5 mm were comparable to outcomes reported for shallow defects. Prospective clinical trials are needed to validate the proposed approach and techniques. Practical Implications. The proposed algorithm allows the clinician to select the appropriate surgical technique for treatment of single deep gingival recessions with good predictability. |
| format | Article |
| id | doaj-art-7459acb241624027a43109baf7543921 |
| institution | Kabale University |
| issn | 1687-8728 1687-8736 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Dentistry |
| spelling | doaj-art-7459acb241624027a43109baf75439212025-02-03T01:21:56ZengWileyInternational Journal of Dentistry1687-87281687-87362019-01-01201910.1155/2019/18307651830765Root Coverage for Single Deep Gingival Recessions: Outcomes Based on a Decision-Making AlgorithmJoão B. César Neto0Marília C. Cavalcanti1Ricardo T. Sekiguchi2Claudio M. Pannuti3Giuseppe A. Romito4Dimitris N. Tatakis5Division of Periodontology, College of Dentistry, University of São Paulo, São Paulo, BrazilDivision of Periodontology, College of Dentistry, University of São Paulo, São Paulo, BrazilDivision of Periodontology, College of Dentistry, University of São Paulo, São Paulo, BrazilDivision of Periodontology, College of Dentistry, University of São Paulo, São Paulo, BrazilDivision of Periodontology, College of Dentistry, University of São Paulo, São Paulo, BrazilDivision of Periodontology, College of Dentistry, The Ohio State University, Columbus, OH, USAAim. The aim of this study is to report root coverage outcomes in single deep gingival recessions (GR) following a proposed decision-making algorithm. Materials and Methods. A retrospective, practice-based study included single deep (≥5 mm) Miller Class II and III defects. The step-by-step decision-making algorithm led to a choice among three different flap designs (coronally advanced flap (CAF), double papilla envelope flap (DPE) or modified lateral sliding flap (LSF)) used with a connective tissue graft. Recession depth (RD) at 6 months follow-up and the corresponding root coverage (RC) were the primary outcomes assessed. Results. Sixteen GR defects were included, with baseline RD of 6.7 ± 1.8 mm. Six months postoperatively, RD was significantly reduced to 1.2 ± 0.8 mm (p<0.05). Mean RC was 81.7 ± 13.0%, without significant differences between Miller Class II (87.1 ± 9.2%; n=9) and Class III (74.6 ± 14.5%; n=7) GRs (p=0.07). Postoperatively, keratinized tissue width increase was greater for LSF (3.5 ± 1.1) and DPE (4.2 ± 1.4 mm) than for CAF (1.9 ± 0.9 mm). Conclusions. Following the proposed decision-making algorithm, root coverage outcomes for GR defects ≥5 mm were comparable to outcomes reported for shallow defects. Prospective clinical trials are needed to validate the proposed approach and techniques. Practical Implications. The proposed algorithm allows the clinician to select the appropriate surgical technique for treatment of single deep gingival recessions with good predictability.http://dx.doi.org/10.1155/2019/1830765 |
| spellingShingle | João B. César Neto Marília C. Cavalcanti Ricardo T. Sekiguchi Claudio M. Pannuti Giuseppe A. Romito Dimitris N. Tatakis Root Coverage for Single Deep Gingival Recessions: Outcomes Based on a Decision-Making Algorithm International Journal of Dentistry |
| title | Root Coverage for Single Deep Gingival Recessions: Outcomes Based on a Decision-Making Algorithm |
| title_full | Root Coverage for Single Deep Gingival Recessions: Outcomes Based on a Decision-Making Algorithm |
| title_fullStr | Root Coverage for Single Deep Gingival Recessions: Outcomes Based on a Decision-Making Algorithm |
| title_full_unstemmed | Root Coverage for Single Deep Gingival Recessions: Outcomes Based on a Decision-Making Algorithm |
| title_short | Root Coverage for Single Deep Gingival Recessions: Outcomes Based on a Decision-Making Algorithm |
| title_sort | root coverage for single deep gingival recessions outcomes based on a decision making algorithm |
| url | http://dx.doi.org/10.1155/2019/1830765 |
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