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与女性二次不孕症相关的预测风险因素:单变量和多变量逻辑回归分析

Wafa Fatima¹, Abdul Majeed Akhtar¹, Asif Hanif¹

¹Faculty of Allied Health Sciences, University Institute of Public Health, The University of Lahore, Lahore, Pakistan.

Frontiers in medicine

|April 9, 2024

概括

二次不孕症风险因素包括联合家庭生活和婚姻纠纷,早期结婚年龄是保护性的. 人工神经网络 (ANN) 显示出更高的预测准确度比物流回归识别这些风险.

科学领域:

生殖健康生殖健康
医疗信息学医疗信息学
流行病学流行病学

背景情况:

二次不孕症影响了以前怀孕过但无法再次怀孕的女性.
了解风险因素对于预防和管理策略至关重要.

研究的目的:

确定与二次不孕症相关的风险因素.
为了比较人工神经网络 (ANN) 和多重逻辑回归 (MLR) 模型在识别二次不孕症方面的预测准确度.

主要方法:

一项涉及690名年龄在20-45岁的女性 (345例,345例对照) 确诊的二次不孕症的病例控制研究.
从吉拉尼超声中心收集的数据.
使用多重逻辑回归 (MLR) 和人工神经网络 (ANN) 的分析.

主要成果:

生活在一个联合家庭 (OR=2.91) 和经历与丈夫的关系困难 (OR=2.35) 显著增加了二次不孕症的风险.
在较早的年龄结婚与降低风险相关 (OR=0.94).
与MLR模型 (ROC=0.852) 相比,ANN模型显示出更高的预测准确性 (ROC=0.87).

结论:

二次不孕症的关键风险因素,如联合家庭生活和婚姻纠纷,在很大程度上是可以修改的.
早期干预和对这些已识别的风险因素的管理可以帮助预防二次不孕症.
与传统的逻辑回归相比,人工神经网络为二次不孕症提供了更准确的预测工具.

关键词:

人工神经网络 (ANN) 是一个人工神经网络.后勤回归分析的分析多变量的多变量.二次性不孕不育的原因没有变异的.

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