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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/49844
Title: | 支持性牙周病治療階段失牙風險的統計分析模型 Statistical analysis of the risk for tooth loss during supportive periodontal therapy |
Authors: | Hsuan Meng 孟璇 |
Advisor: | 杜裕康(Yu-Kang Tu) |
Keyword: | 牙齒脫落,積極性牙周病治療前,支持性牙周病治療階段,羅吉斯迴歸,卜瓦松迴歸,廣義估計方程式, tooth loss,before active periodontal therapy,supportive periodontal therapy (SPT),logistic regression,Poisson regression,generalized estimating equations (GEE), |
Publication Year : | 2016 |
Degree: | 碩士 |
Abstract: | Background
Dental caries and periodontal disease are the two most common oral diseases. In comparison to tooth decay, periodontal disease is harder to be detected and more likely to be overlooked. Periodontal disease is a disease affecting tissue surrounding the teeth, caused by dental plaque attached to the tooth surface. If left untreated, it will lead to loosening and subsequent loss of teeth. Recent researches showed that periodontal disease and tooth loss can also affect systemic health, such as an increased risk for myocardial infarction, arteriosclerosis, stroke and so on. Objective The aim of this study was to investigate the risk factors for tooth loss measured before active periodontal therapy (APT) and during supportive periodontal therapy (SPT). These risk factors related to tooth loss were collected and measured at the patient level and tooth level. Materials and Methods In three private practices in the UK, 100 patients with periodontal diseases were recruited and treated by the same periodontist. Clinical and radiographic measurements were undertaken from each patient on three occasions, including before the active periodontal therapy, supportive periodontal therapy and the last follow-up. Tooth loss was recorded in the last follow-up. We first analyze the associations between the risk factors and tooth loss at the patient level. In the logistic regression, the tooth loss was coded 1 for patients who lost at least one tooth and 0 for those who did not lose any tooth during the supportive periodontal therapy. Then in the Poisson regression analysis, the number of tooth loss (counts) was used as the outcome variable. For the tooth-level analysis, as some patients lost more than 1 tooth, we used the generalized estimating equations to take into account the clustering of teeth within patients. Results We found that patient’s age significantly increased the risk for tooth loss at the patient level. The prognosis based on PR score system was effective in the tooth loss. Age, endodontic, furcation and prognosis significantly contribute to tooth loss before active periodontal therapy. The tooth level factors associated with tooth loss were age, furcation involvement and prognosis scores. Conclusion The following patient level of risk factors for tooth loss were age and prognosis (PR score system). The following tooth level of risk factors for tooth loss were endodontic, furcation involvement and prognosis scores. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/49844 |
DOI: | 10.6342/NTU201602245 |
Fulltext Rights: | 有償授權 |
Appears in Collections: | 統計碩士學位學程 |
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File | Size | Format | |
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ntu-105-1.pdf Restricted Access | 1.7 MB | Adobe PDF |
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