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. 2021 Jun 1;39(3):300-305.
doi: 10.7518/hxkq.2021.03.009.

Salivary biochemical indices related to early childhood caries

[Article in English, Chinese]
Ying Zhang  1   2 , Song-Bo Jia  3 , Fan Li  1   2 , Shan-Shan Li  1 , Li-Juan Zhang  1   2 , Kai-Xuan Tan  2 , Jie Lu  2 , Fang Yang  2
Affiliations

Salivary biochemical indices related to early childhood caries

[Article in English, Chinese]
Ying Zhang et al. Hua Xi Kou Qiang Yi Xue Za Zhi. .

Abstract
in English, Chinese

Objectives: This study aimed to compare the salivary biochemical indices between caries-free individuals and those with early childhood caries (ECC), and construct a saliva-based caries diagnostic model by analyzing the correlation between salivary biochemical indices and caries severity.

Methods: A total of 120 children aged 4-6 years were selected and divided into two groups: individuals with ECC (C group, n=60) and healthy children (H group, n=60). Salivary samples were collected to compare the pH, total protein, and ion concentrations between the two groups. The correlation between the salivary biochemical indices and caries severity was examined, and an ECC diagnostic model was established.

Results: The NO3- concentration significantly decreased in the C group, whereas the Cl-, Br-, NH4+, and Mg2+ concentrations significantly increased in the C group (P<0.05). In addition, the salivary caries severity had a significantly negative correlation with the NO3- concentration but had a positive correlation with Br-, Cl-, and NH4+ concentrations (P<0.05). The ECC diagnostic model based on salivary biochemical indices could yield satisfactory results in terms of distinguishing the C and H groups with over 85% accuracy.

Conclusions: Salivary biochemical indices can contribute to the diagnosis and risk assessment of ECC.

目的: 比较低龄儿童龋患者和健康者唾液生化指标的差异及其与龋病状态的关联，建立龋病诊断模型。方法: 选取4~6岁儿童共120名，分为2组：低龄儿童龋患者（C组）和健康儿童（H组）各60名，采集唾液样本，比较pH、总蛋白以及离子浓度的差异，分析唾液生化指标与龋病状态的相关性，并建立龋病诊断模型。结果: C组NO3-浓度显著低于H组，而Cl-、Br-、NH4+、Mg2+浓度显著高于H组（P<0.05）；唾液NO3-浓度与患龋状态呈负相关，Br-、Cl-、NH4+浓度与患龋状态呈正相关（P<0.05）。利用唾液生化参数建立的龋病风险评估模型区分C组和H组的准确率可达85%以上。结论: 唾液pH、总蛋白和离子浓度有助于诊断和评估低龄儿童龋。.

Keywords: biochemical indices; correlation; diagnosis model; early childhood caries; saliva.

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Conflict of interest statement

利益冲突声明：作者声明本文无利益冲突。

Figures

图 1
图 1. 口腔唾液生化参数与dmft指数的关联性
Fig 1 Correlation between salivary biochemical indices and dmft index A：NO3−浓度与dmft指数呈负相关；B：Br−浓度与dmft指数呈正相关；C：Cl−浓度与dmft指数呈正相关；D：NH4+浓度与dmft指数呈正相关。
图 2
图 2. 基于全部生化参数建立的模型变量的重要性分布
Fig 2 Importance of variables in the model based on all biochemical parameters 所有生化指标按其对模型精度的重要性由高到低排列，线条长度表示所有指标对基于其建立模型的平均重要性。
图 3
图 3. 基于5个筛选参数建立的模型变量的重要性分布
Fig 3 Importance of five variables in the model based on selected parameters 筛选出的5个生化指标按其对模型精度的重要性由高到低排列，线条长度表示这5个筛选指标对基于其建立模型的贡献。
图 4
图 4. 基于全部唾液生化参数建立的ECC风险评估模型的性能图
Fig 4 Performance of ECC risk assessment model based on all salivary biochemical parameters 基于全部生化指标的诊断模型的ROC曲线，通过曲线下面积（AUC=86.78%）测量诊断模型区分低龄儿童龋患者组和健康组的准确性，95%置信区间为79.84%~93.71%。AUC值越接近1，提示模型的诊断性能越好。
图 5
图 5. 基于5个筛选参数建立的ECC风险评估模型的性能图
Fig 5 Performance of ECC risk assessment model based on five selected parameters 基于5个筛选参数的诊断模型的ROC曲线，通过曲线下面积（AUC=86.75%）测量诊断模型区分低龄儿童龋患者组和健康组的准确性，95%置信区间为79.98%~93.52%。AUC值越接近1，提示模型的诊断性能越好。
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