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摘要:
目的 在循证医学的基础上利用Rothman-Keller模型建立出生缺陷发病风险预测模型, 为中国有针对性的制定干预措施提供依据。 方法 通过评价Meta分析的文献获得出生缺陷危险因素及相应比值比(odds ratio, OR)值, 构建Rothman-Keller模型的危险评分表, 再利用模拟数据构建模型, 确定风险预测危险程度划分界值, 并采用实际数据验证。 结果 通过17篇文献收集了先天畸形家族史和居住地有污染源等20个出生缺陷的主要危险因素。在山西省的实际数据中, Rothman-Keller模型筛选出的高危人群实际发病率为10.9%, 并与其他组有统计学差异(χ2=147.58, P < 0.001)。除此之外, Rothman-Keller模型能将先天畸形家族史的患者100%识别到高危人群。 结论 通过中国出生缺陷的Meta分析文献, 找出出生缺陷主要危险因素, 构建风险预测模型, 可用于预测出生缺陷的发病风险, 帮助筛选高危人群。同时为预测其他疾病的发病风险提供了思路。 Abstract:Objective The Rothman-Keller model was used to establish a predictive model for the risk of birth defects on the basis of evidence-based medicine, which so as to provide the basis for pertinent interventions in China. Methods First, the odds ratio (OR) value of risk factors for birth defects was obtained by evaluating the literature of meta-analysis, and the risk score table of the Rothman-Keller model was constructed. Then the simulation data was used to build the model, the risk boundary value of risk prediction, and finally the actual data to was used for verification. Results The main risk factors for 20 birth defects were collected through 17 articles. In the actual data of Shanxi Province, the actual incidence rate of high-risk populations screened by Rothman-Keller model was 10.9%, and it was statistically different from other groups (χ2=147.58, P < 0.001). In addition, the rothman-keller model identified all patients with a family history of birth defects as high-risk. Conclusions Through the meta-analysis literature on birth defects in China, the study find the main risk factors and construct a risk prediction model. It can be used to predict the risk of birth defects and help screen high-risk groups. At the same time, it provides ideas for predicting the risk of other diseases. -
Key words:
- Birth defects /
- Evidence-based medicine /
- Risk factors /
- Risk prediction model
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图 1 Rothman-Keller模型风险等级划分节点图
Figure 1. Rothman-Keller model risk classification node map
表 1 模型中危险暴露因素的效应值表
Table 1. Effect value table of risk exposure factors in the model
危险因素 OR1 βi 人群暴露率(%) 危险分数 人群归因危险度(PAR%) 先天畸形家族史 否 0.843 是 36.22[6] 3.59 1.67[12] 10.268 0.157 异常孕产史 否 0.940 是 2.07[6] 0.73 6.67[13] 1.836 0.060 孕期服用叶酸 否 1.564 是 0.35[8] -1.05 56.60[14] 0.568 -0.564 孕期食用水果蔬菜或优质蛋白 否 1.339 是 0.67[6] -0.40 79.75[15] 0.914 -0.339 孕期感冒或发热 否 0.813 是 2.72[9] 1.00 15.51[9] 2.018 0.187 孕母患慢性病 否 0.986 是 1.92[6] 0.65 1.70[16] 1.450 0.014 孕期贫血 否 0.982 是 1.52[6] 0.42 3.90[17] 1.801 0.018 孕期负性精神刺激 否 0.988 是 1.98[7] 0.68 1.40[14] 1.854 0.012 孕期TORCH感染 否 0.970 是 1.44[10] 0.36 7.68[10] 1.363 0.030 孕期服用镇静药 否 0.993 是 3.19[6] 1.16 0.40[16] 2.821 0.007 孕期服用抗生素 否 0.994 是 1.65[10] 0.50 1.10[16] 1.582 0.006 孕母年龄(岁) ＜35 0.998 ≥35 1.06[5] 0.06 2.90[18] 1.055 0.002 孕期被动吸烟 否 0.444 是 5.80[7] 1.76 35.00[19] 2.032 0.556 近亲结婚 否 0.991 是 7.69[11] 2.04 0.20[17] 5.543 0.009 父亲经常饮酒 否 0.962 是 2.23[6] 0.80 3.60[17] 2.008 0.038 父亲吸烟 否 0.381 是 3.89[6] 1.36 69.30[17] 1.274 0.619 居住地有污染源 否 0.941 是 1.86[10] 0.62 8.10[16] 1.670 0.059 孕早期接触宠物 否 0.891 是 3.96[7] 1.38 5.10[16] 3.027 0.109 孕期接触有害物理因素 否 0.745 是 4.76[7] 1.56 11.70[14] 2.928 0.255 孕期接触农药 否 0.991 是 2.49[5] 0.91 0.70[11] 2.278 0.009 
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表 3 Rothman-Keller模型不同危险等级出生缺陷发病率的比较
Table 3. Comparison of the incidence of birth defects at different risk levels in the Rothman-Keller model
危险等级 是否出生缺陷[n(%)] χ2值 P值 缺陷组 非缺陷组 高危 242(10.9) 1 981(89.1) 147.58 ＜0.001 中危 106(4.8) 2 108(95.2) 低危 132(3.5) 3 689(96.5)
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表 4 Rothman-Keller模型在先天畸形家族史的危险等级划分
Table 4. Classification of hazard levels in the family history of congenital malformations by the Rothman-Keller model
危险等级 是否出生缺陷 总数 缺陷 非缺陷 低危 0 0 0 中危 0 0 0 高危 40 21 61 总数 40 21 61
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