{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,19]],"date-time":"2025-10-19T15:46:28Z","timestamp":1760888788059},"reference-count":16,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2013,4,4]],"date-time":"2013-04-04T00:00:00Z","timestamp":1365033600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Clinic Periodontology"],"published-print":{"date-parts":[[2013,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background and Purpose<\/jats:title><jats:p>Periodontal maintenance is critical for the long\u2010term success of prosthodontic treatment. This study investigates the validity of questionnaires\/models in monitoring periodontitis for Chinese prosthodontic patients.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>In total, 114 patients completed the questionnaire. The chi\u2010squared test and classification and regression trees were used to screen for predictive items. Predictive models developed by Yamamoto et\u00a0al. and Dietrich et\u00a0al. were validated using <jats:styled-content style=\"fixed-case\">ROC<\/jats:styled-content> curves and calibration plots.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Univariate and multivariate analysis revealed that demographic features (age, gender, smoking history, education history and number of remaining teeth), symptoms(tooth mobility without injury, painful gums), dental recommendations (\u201cneed periodontal or gum treatment?\u201d) and treatment history (scaling and root planing) were predictive of periodontitis. The <jats:styled-content style=\"fixed-case\">AUC<\/jats:styled-content> values of the Yamamoto model and Dietrich's model\u2010a and model\u2010b were 0.67, 0.89, and 0.89 for moderate\/severe periodontitis and 0.78, 0.93, and 0.93 for severe periodontitis, respectively. The calibration plot showed that Dietrich's model\u2010a and model\u2010b accurately predicted the actual probability of moderate\/severe and severe periodontitis, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Questionnaires may be an efficient approach to monitor periodontal health in China. Dietrich's models, with age, smoking and self\u2010reported mobility as predictors, can be used to monitor periodontal health for Chinese prosthodontic patients.<\/jats:p><\/jats:sec>","DOI":"10.1111\/jcpe.12103","type":"journal-article","created":{"date-parts":[[2013,3,7]],"date-time":"2013-03-07T19:58:04Z","timestamp":1362686284000},"page":"616-623","source":"Crossref","is-referenced-by-count":16,"title":["Self\u2010reported questionnaire for surveillance of periodontitis in Chinese patients from a prosthodontic clinic: a validation study"],"prefix":"10.1111","volume":"40","author":[{"given":"Xiayi","family":"Wu","sequence":"first","affiliation":[{"name":"Guanghua School and Hospital of Stomatology and Guangdong Provincial Key Laboratory of Stomatology Sun Yat\u2010sen University Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiyan","family":"Weng","sequence":"additional","affiliation":[{"name":"Guanghua School and Hospital of Stomatology and Guangdong Provincial Key Laboratory of Stomatology Sun Yat\u2010sen University Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuefeng","family":"Lin","sequence":"additional","affiliation":[{"name":"Guanghua School and Hospital of Stomatology and Guangdong Provincial Key Laboratory of Stomatology Sun Yat\u2010sen University Guangzhou China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2013,4,4]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1177\/154405910508401003"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2011.110015"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-051X.2009.01400.x"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2007.060212"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2009.080607"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2012.110676"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2007.060395"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2007.060435"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2007.060199"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1902\/jop.2007.070110"},{"key":"e_1_2_8_12_1","unstructured":"Morlini I.(2002)Facing multicollinearity in data mining. 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