Accuracy Of Partial-Mouth Examination Protocols For Extent And Severity Estimates Of Periodontitis: A Study In A Chinese Population With Chronic Periodontitis

JOURNAL OF PERIODONTOLOGY(2015)

引用 16|浏览1
暂无评分
摘要
Background: Partial-mouth periodontal examination (PMPE) has been widely used in periodontal epidemiologic studies. In this study, the authors evaluate the accuracy of extent and severity estimates from PMPE protocols in a Chinese population.Methods: The study enrolled 200 individuals with periodontitis, ages 22 to 64 years. Full-mouth examination was performed to determine probing depth (PD), attachment loss (AL), and bleeding on probing (BOP) at mesio-buccal (MB), mid-buccal (B), disto-buccal (DB), mesio-lingual (ML), mid-lingual (L), and disto-lingual (DL) sites per tooth. Extent and severity estimates from 15 PMPE protocols were derived from and compared to full-mouth data. Relative bias (RB) and intraclass correlation coefficients (ICCs) were calculated. Bland-Altman plots were used to evaluate the agreement patterns across disease levels.Results: Of the 15 PMPE protocols, the random half-mouth six-sites per tooth (r6sites) protocol performed best in both extent (AL >= 2, >= 4, or >= 6 mm; PD >= 4 or >= 6 mm; and BOP) and severity (AL and PD) estimates, with RB within 5.0% and ICCs >= 0.950 in most cases. MB-B-DB and MB-B-DL protocols generally resulted in RB within 20.0% for extent and within 5.0% for severity. Protocols involving only interproximal sites (MB-DB, MB-DL, and MB-DB-ML-DL) showed good accuracy in AL (RB within 20.0% for extent and within 3.0% for severity), but overestimated PD (RB 12.5% to 54.2% for extent and >10.0% for severity). The community periodontal index teeth protocol caused severe overestimation of up to 110.4% for extent and 14.6% for severity.Conclusion: The r6sites protocol is best for assessing extent and severity for AL, PD, and BOP under the study conditions.
更多
查看译文
关键词
Bias (epidemiology),health surveys,oral examination,periodontal index,periodontitis,severity of illness index
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要