Ma Mang Shin, Najirad Mohammadamin, Taqi Doaa, Retrouvey Jean-Marc, Tamimi Faleh, Dagdeviren Didem, Glorieux Francis H, Lee Brendan, Sutton Vernon Reid, Rauch Frank, Esfandiari Shahrokh
Faculty of Dentistry, McGill University, Montreal, Quebec, Canada.
Shriners Hospital for Children and McGill University, Montreal, Quebec, Canada.
Spec Care Dentist. 2019 Mar;39(2):214-219. doi: 10.1111/scd.12368. Epub 2019 Feb 13.
Dentinogenesis Imperfecta (DI) forms a group of dental abnormalities frequently found associated with Osteogenesis Imperfecta (OI), a hereditary disease characterized by bone fragility. The objectives of this study were to quantify the dental caries prevalence and experience among different OI-types in the sample population and quantify how much these values change for the subset with DI.
To determine which clinical characteristics were associated with increased Caries Prevalence and Experience (CPE) in patients with OI, the adjusted DFT scores were used to account for frequent hypodontia, impacted teeth and retained teeth in OI population. For each variable measured, frequency distributions, means, proportions and standard deviations were generated. Groups means were analyzed by the unpaired t-test or ANOVA as appropriate. For multivariate analysis, subjects with caries experience of zero were compared with those with caries experience greater than zero using logistic regression.
The stepwise regression analysis while controlling for all other variables demonstrated the presence of DI (OR 2.43; CI 1.37-4.32; P = 0.002) as the significant independent predictor of CPE in the final model.
This study found no evidence that CPE of OI subjects differs between the types of OI. The presence of DI when controlled for other factors was found to be the significant predictor of CPE.
牙本质发育不全(DI)是一组常见的牙齿异常,常与成骨不全(OI)相关,成骨不全是一种以骨骼脆弱为特征的遗传性疾病。本研究的目的是量化样本人群中不同OI类型的龋齿患病率和患病经历,并量化患有DI的亚组中这些值的变化情况。
为了确定哪些临床特征与OI患者龋齿患病率和患病经历(CPE)增加相关,使用调整后的DFT评分来考虑OI人群中常见的缺牙、阻生牙和滞留牙情况。对于每个测量变量,生成频率分布、均值、比例和标准差。根据情况,通过不成对t检验或方差分析对组均值进行分析。对于多变量分析,使用逻辑回归将龋齿经历为零的受试者与龋齿经历大于零的受试者进行比较。
在控制所有其他变量的情况下,逐步回归分析表明,DI的存在(OR 2.43;CI 1.37 - 4.32;P = 0.002)是最终模型中CPE的显著独立预测因素。
本研究未发现证据表明OI受试者的CPE在不同OI类型之间存在差异。在控制其他因素后,发现DI的存在是CPE的显著预测因素。