Background: The aims of this study were (i) to test the reliability of a new classification system of gingival recessions using the level of interproximal clinical attachment as an identification criterion and (ii) to explore the predictive value of the resulting classification system on the final root coverage outcomes. Material and methods: Patients showing at least one buccal gingival recession were recruited by one operator. Three recession types (RT) were identified. While class RT1 included gingival recession with no loss of interproximal attachment, class RT2 recession was associated with interproximal attachment loss less than or equal to the buccal site and class RT3 showed higher interproximal attachment loss than the buccal site. The classification was tested by two examiners blinded to the data collected by the other examiner. Intra-rater and inter-rater agreement was assessed. Furthermore, the 6-month root coverage outcomes of consecutively treated gingival recessions were retrospectively evaluated in order to explore the predictive value of the proposed classification on the final recession reduction (Rec Red). Results: The new classification system of gingival recessions was tested in a total of 116 gingival recessions (mean 3.2±1.2 mm) in 25 patients. The intra-class correlation coefficient (ICC) for inter-rater agreement was 0.86, showing an almost perfect agreement between the examiners. The RT classification was predictive of the final Rec Red (p<0.0001) at the 6-month follow-up in 109 treated gingival recessions. Conclusions: The evaluation of interproximal clinical attachment level may be used to classify gingival recession defects and to predict the final root coverage outcomes. © 2011 John Wiley & Sons A/S.

The interproximal clinical attachment level to classify gingival recessions and predict root coverage outcomes: An explorative and reliability study / Cairo F.; Nieri M.; Cincinelli S.; Mervelt J.; Pagliaro U.. - In: JOURNAL OF CLINICAL PERIODONTOLOGY. - ISSN 0303-6979. - ELETTRONICO. - 38:(2011), pp. 661-666. [10.1111/j.1600-051X.2011.01732.x]

The interproximal clinical attachment level to classify gingival recessions and predict root coverage outcomes: An explorative and reliability study

Cairo F.;Nieri M.;Cincinelli S.;Mervelt J.;Pagliaro U.
2011

Abstract

Background: The aims of this study were (i) to test the reliability of a new classification system of gingival recessions using the level of interproximal clinical attachment as an identification criterion and (ii) to explore the predictive value of the resulting classification system on the final root coverage outcomes. Material and methods: Patients showing at least one buccal gingival recession were recruited by one operator. Three recession types (RT) were identified. While class RT1 included gingival recession with no loss of interproximal attachment, class RT2 recession was associated with interproximal attachment loss less than or equal to the buccal site and class RT3 showed higher interproximal attachment loss than the buccal site. The classification was tested by two examiners blinded to the data collected by the other examiner. Intra-rater and inter-rater agreement was assessed. Furthermore, the 6-month root coverage outcomes of consecutively treated gingival recessions were retrospectively evaluated in order to explore the predictive value of the proposed classification on the final recession reduction (Rec Red). Results: The new classification system of gingival recessions was tested in a total of 116 gingival recessions (mean 3.2±1.2 mm) in 25 patients. The intra-class correlation coefficient (ICC) for inter-rater agreement was 0.86, showing an almost perfect agreement between the examiners. The RT classification was predictive of the final Rec Red (p<0.0001) at the 6-month follow-up in 109 treated gingival recessions. Conclusions: The evaluation of interproximal clinical attachment level may be used to classify gingival recession defects and to predict the final root coverage outcomes. © 2011 John Wiley & Sons A/S.
2011
38
661
666
Cairo F.; Nieri M.; Cincinelli S.; Mervelt J.; Pagliaro U.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1195864
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