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Digitally measured exposed root surface area for predicting the effectiveness of modified coronally advanced tunnel combined de-epithelialized gingival grafting in the treatment of multiple adjacent gingival recessions.
Clinical Oral Investigations 2023 May 26
OBJECTIVES: To assess the predictive value of baseline digitally measured exposure root surface area (ERSA) on the effectiveness of modified coronally advanced tunnel and de-epithelialized gingival grafting (MCAT + DGG) technique for the treatment of multiple adjacent gingival recessions (MAGRs).
MATERIALS AND METHODS: A total of 96 gingival recessions (48 RT1 and 48 RT2) from 30 subjects were included. ERSA was measured on the digital model obtained by intraoral scanner. Generalized linear model was used to analyze the possible correlation of ERSA, Cairo recession type (RT), gingival biotype, keratinized gingival width (KTW), tooth type, and cervical step-like morphology on the mean root coverage (MRC) and complete root coverage (CRC) at 1-year after MCAT + DGG. The predictive accuracy of CRC is tested using receiver-operator characteristic curves.
RESULTS: At 1-year postoperatively, the MRC for RT1 was 95.14 ± 10.25%, which was significantly higher than 78.42 ± 22.57% for RT2 (p < 0.001). ERSA (OR:1.342, p < 0.001), KTW (OR:1.902, p = 0.028) and lower incisors (OR:15.716, p = 0.008) were independent risk factors for predicting MRC. ERSA and MRC showed significant negative correlation in RT2(r = -0.558, p < 0.001), but not in RT1(r = 0.220, p = 0.882). Meanwhile, ERSA (OR:1.232, p = 0.005) and Cairo RT (OR:3.740, p = 0.040) were independent risk factors for predicting CRC. For RT2, the area under curve was 0.848 and 0.898 for ERSA without or with other correction factors, respectively.
CONCLUSIONS: Digitally measured ERSA may provide strong predictive values for RT1 and RT2 defects treated with MCAT + DGG.
CLINICAL RELEVANCE: This study demonstrates that digitally measured ERSA is a valid outcome predictor for root coverage surgery, especially applicable for predicting RT2 MAGRs.
MATERIALS AND METHODS: A total of 96 gingival recessions (48 RT1 and 48 RT2) from 30 subjects were included. ERSA was measured on the digital model obtained by intraoral scanner. Generalized linear model was used to analyze the possible correlation of ERSA, Cairo recession type (RT), gingival biotype, keratinized gingival width (KTW), tooth type, and cervical step-like morphology on the mean root coverage (MRC) and complete root coverage (CRC) at 1-year after MCAT + DGG. The predictive accuracy of CRC is tested using receiver-operator characteristic curves.
RESULTS: At 1-year postoperatively, the MRC for RT1 was 95.14 ± 10.25%, which was significantly higher than 78.42 ± 22.57% for RT2 (p < 0.001). ERSA (OR:1.342, p < 0.001), KTW (OR:1.902, p = 0.028) and lower incisors (OR:15.716, p = 0.008) were independent risk factors for predicting MRC. ERSA and MRC showed significant negative correlation in RT2(r = -0.558, p < 0.001), but not in RT1(r = 0.220, p = 0.882). Meanwhile, ERSA (OR:1.232, p = 0.005) and Cairo RT (OR:3.740, p = 0.040) were independent risk factors for predicting CRC. For RT2, the area under curve was 0.848 and 0.898 for ERSA without or with other correction factors, respectively.
CONCLUSIONS: Digitally measured ERSA may provide strong predictive values for RT1 and RT2 defects treated with MCAT + DGG.
CLINICAL RELEVANCE: This study demonstrates that digitally measured ERSA is a valid outcome predictor for root coverage surgery, especially applicable for predicting RT2 MAGRs.
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