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脑性瘫痪危险因素分析 被引量:6

Study on the risk factors of cerebral palsy
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摘要 目的探讨脑性瘫痪的危险因素。方法利用本省病残儿数据库资料,应用Logistic回归模型,对992例脑性瘫痪患儿和627例后天伤残儿童做对照进行危险因素分析。结果脑性瘫痪组患儿分娩方式异常(26.3%)、异常分娩(44.3%)、母亲患先天性遗传性疾病(1.4%)、母亲孕期感染(23.5%)、母亲孕期服药(13.1%)、妊娠合并症(31.6%)、父亲工作环境接触化学物质(32.5%)和有烟酒嗜好(55.3%)与对照组(6.7%、11.8%、0.6%、10.0%、4.3%、19.9%、10.4%和25.8%)比较,差异有统计学意义(P<0.01);Logistic回归模型分析,分娩方式异常、异常分娩、母亲患有先天性遗传性疾病、母亲孕期服药、孕期感染、妊娠合并症、父亲工作接触化学物质及烟酒嗜好进入模型。结论在母亲患有先天性遗传性疾病、孕前用药、感染、父亲工作环境接触化学物质及患病等情况下,建议不要受孕,一旦受孕应当进行产前诊断和孕期诊断。 Objective To investigate the risk factors of cerebral palsy. Methods The provincial database of disabled children was applied to collect data. Logistic regression model was used to analyze risk factors of cerebral palsy on 992children with cerebral palsy and 627 controls with acquired diseases. Results Univariate analysis showed that, children with cerebral palsy were more likely to be with maternal complications during labor (44. 3 %), abnormal delivery mode ( 26. 3 %), maternal congenital genetical disease (1.4 %), pregnancy oral medicine use (13.1%), maternal infection during pregancy ( 23.5 %), pregnancy complications, paternal ( 31.6 %), paternal exposure to chemicals (32.5 %), paternal tobacco and alcohol use (55. 3 %) than controls (11.8 %, 6. 7 %.0. 6 %. 4. 3 %. 10. 0 %. 19. 9 %. 10. 4 %, 25. 8 %, respectively) ; Multi-variate Logistic modol confirmed 8 risk factors, including abnormal deliver mode. maternal complications during labor, maternal congenital genetical disease, maternal use of medicine, maternal infections during pregnancy, pregnancy complications, paternal exposure to chemicals and paternal tobacco and alcohol use. Conclusion We suggest that parents should not have babies when mother getting congenital genetic diseases, taking medicine and having infections, and paternal exposure to chemical substance. Prenatal health care and diagnosis should be strenghened if they have become pregnant.
出处 《中国生育健康杂志》 2007年第2期99-101,共3页 Chinese Journal of Reproductive Health
关键词 脑性瘫痪 危险因素 LOGISTIC回归模型 Cerebral palsy Risk factor Logistic Regression Model
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