| 摘要: |
| 目的 分析影响子宫腺肌病发病的影响因素，寻找子宫腺肌病的防治及干预措施，从而减少子宫腺肌病的发病风险。方法 采用病例对照研究的方法，以128 例患者为实验组，同期入院的非子宫腺肌病的患者256 例为对照组。收集可能影响子宫腺肌病的影响因素，包括一般情况、生育及月经情况、生物学指标情况。采用SPSS18.0 统计软件进行统计分析，先行单因素因素分析，根据单因素分析有统计学差异的因素进行多因素logistic 回归分析。结果 单因素分析发现年龄、职业、早产、人工流产次数、剖宫产、痛经、ER、PR 和CA125 阳性为危险因素。多因素logistic 回归分析证实年龄、职业、早产、剖宫产、人工流产次数、FR 阳性、ER 阳性和CA125 阳性为子宫腺肌病的影响因素。结论 年龄、职业、早产、剖宫产、人工流产次数、FR 阳性、ER 阳性和CA125阳性为子宫腺肌病的影响因素，对其危险因素进行干预，可为防治方式提供参考。 |
| 关键词: 子宫腺肌病 危险因素 logistic回归 病例对照研究 |
| DOI： |
| 分类号: |
| 基金项目:温州市医药卫生科学研究项目 |
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| A Logistic Regression Analysis on Risk Factors of Uterine Adenomyosis |
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CHEN Qian, WANG Peifei, LIANG Yujie
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Yueqing People’s Hospital
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| Abstract: |
| Objective To explore the risk factors of uterine adenomyosis (AM). Methods The case-control study was used to find the risk factors of uterine adenomyosis through the clinical data of 128 patients with uterine adenomyosis in the hospital and 256 patients without uterine adenomyosis meanwhile. Data of factors which possibly is involved in uterine adenomyosis were collected, including general situation, birth and menstruation, biological indicators, was retrospectively analysed to explore risk factors for incidence in patients. First by multivariate analysis , then multiple-factor Logistic regression analysis by SPSS18.0. on statistically significant factors based on multivariate analysis. Results By single factor analysis, age, occupation, preterm birth, number of induced abortion, cesarean delivery, dysmenorrhea, positive ER, positive FR and positive CA125 were risk factors. Multivariate Logistic regression analysis confirmed that the age, occupation, abortion, premature delivery, cesarean delivery times, FR, ER, and CA125 positive were risk factors of uterine adenomyosis. Conclusion Age, occupation, premature delivery, number of induced abortion, positive FR, positive ER, and positive CA125 were risk factors of adenomyosis and the risk factors intervention, would provide reference for prevention and cure. |
| Key words: Uterine adenomyosis Risk factors logistic regression Multivariate analysis |
