Varshney Pranshu, Khan Saima Y, Jindal Mahendra K, Azim Yasser, Bhardwaj Aditi, Kumar Vinod
Department of Pediatric and Preventive Dentistry, Dr Ziauddin Ahmad Dental College, Aligarh Muslim University, Aligarh, Uttar Pradesh, India.
Department of Applied Chemistry, Zakir Hussain College of Engineering and Technology, Aligarh Muslim University, Aligarh, Uttar Pradesh, India.
Int J Clin Pediatr Dent. 2024 Jul;17(7):754-765. doi: 10.5005/jp-journals-10005-2905.
The goal of this paper is to find an association between the staining capacity of dental restorations used in pediatric patients and food items and to develop an optimum model to predict the most informative factor that causes the highest amount of color change through machine learning algorithms.
Color changes in restorative materials occur as a result of intrinsic and extrinsic factors, such as the type of restorative material, food items used, polished status of the material, and time interval.
This was an " study" conducted at Aligarh Muslim University, Aligarh, Uttar Pradesh, India. The study included 200 specimens, that is, 40 in each group A (orange juice), group B (Amul Kool Café), group C (Pepsi), group D (Amul Kesar Milk), and group E (artificial saliva). The materials were glass ionomer cement (GIC), resin-modified glass ionomer cement (RMGIC), microhybrid composite resin, and nanohybrid composite resin. These were further divided into polished and unpolished groups. The optimum modeling of the prediction of color change in materials by different effective factors was done by machine learning decision tree. We applied two algorithms: Chi-square automatic interaction detector (CHAID) and classification and regression tree (CART). In prediction modeling in the decision tree by CHAID and CART, color change is taken as the dependent variable, and group (type of restorative material), food items, time interval, and polished status are taken as independent variables.
The various beverages caused significant color variation due to different pigmentation agents. The agent that caused the highest color change was Kool Café. The Kesar Milk had the lowest pigmentation capacity. The greatest color variation was found on Glasionomer FX-II submerged in Pepsi and the least on Ivoclar Te-Econom Plus in Kesar Milk. The mean absolute error for the training dataset in the CART model and CHAID model is 0.379 and 0.332, and for the testing data set, it is 0.398 and 0.333, respectively. Therefore, the prediction of color change by the CHAID model is optimum, and we found that the restorative materials have a maximum predictor importance of 0.86 (86%), time interval 0.07 (7%), food items 0.04 (4%), and polished status has the least importance, that is, 0.03 (3%).
The staining capacity of restorative material highly depends on the material itself, the initial time interval, and least on the food items used.
The clinical performance of dental restorations could be affected by various beverages consumed by children. This study thus provides important clinical insights into esthetic dentistry by offering valuable information on long-term color stability and the effect of polishing on common esthetic restorative materials used in pediatric dentistry.
Varshney P, Khan SY, Jindal MK, Quantification of Color Variation of Various Esthetic Restorative Materials in Pediatric Dentistry. Int J Clin Pediatr Dent 2024;17(7):754-765.
本文旨在探寻儿科患者使用的牙科修复体的染色能力与食物之间的关联,并通过机器学习算法开发一个最优模型,以预测导致最大颜色变化量的最具信息量的因素。
修复材料中的颜色变化是由内在和外在因素引起的,如修复材料的类型、所使用的食物、材料的抛光状态以及时间间隔。
这是一项在印度北方邦阿里格尔的阿里格尔穆斯林大学开展的“研究”。该研究包括200个样本,即A组(橙汁)、B组(酷儿咖啡)、C组(百事可乐)、D组(阿穆尔藏红花牛奶)和E组(人工唾液)各40个。材料有玻璃离子水门汀(GIC)、树脂改性玻璃离子水门汀(RMGIC)、微混合复合树脂和纳米混合复合树脂。这些材料进一步分为抛光组和未抛光组。通过机器学习决策树对不同影响因素导致材料颜色变化的预测进行最优建模。我们应用了两种算法:卡方自动相互作用检测器(CHAID)和分类与回归树(CART)。在CHAID和CART决策树的预测建模中,颜色变化作为因变量,组(修复材料类型)、食物、时间间隔和抛光状态作为自变量。
由于不同的色素沉着剂,各种饮料导致了显著的颜色变化。导致颜色变化最大的因素是酷儿咖啡。藏红花牛奶的色素沉着能力最低。在百事可乐中浸泡的玻璃离子FX-II颜色变化最大,而在藏红花牛奶中的义获嘉Te-Econom Plus颜色变化最小。CART模型和CHAID模型中训练数据集的平均绝对误差分别为0.379和0.332,测试数据集的平均绝对误差分别为0.398和0.333。因此,CHAID模型对颜色变化的预测是最优的,我们发现修复材料的预测重要性最高为0.86(86%),时间间隔为0.07(7%),食物为0.04(4%),抛光状态的重要性最低,即0.03(3%)。
修复材料的染色能力高度依赖于材料本身、初始时间间隔,而对所使用的食物依赖程度最低。
儿童饮用的各种饮料可能会影响牙科修复体的临床性能。因此,本研究通过提供有关儿科牙科中常用美学修复材料长期颜色稳定性和抛光效果的宝贵信息,为美容牙科提供了重要的临床见解。
Varshney P, Khan SY, Jindal MK, 儿科牙科中各种美学修复材料颜色变化的量化。《国际临床儿科牙科学杂志》2024;17(7):754 - 765。