Construction of an Early Risk Prediction Model for Type 2 Diabetic Peripheral Neuropathy Based on Random Forest.

IF 1.3 4区 医学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Zhengang Wei, Xiaohua Wang, Liqin Lu, Su Li, Wenyan Long, Lin Zhang, Shaolin Shen
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引用次数: 0

Abstract

Diabetic peripheral neuropathy is a major cause of disability and death in the later stages of diabetes. A retrospective chart review was performed using a hospital-based electronic medical record database to identify 1020 patients who met the criteria. The objective of this study was to explore and analyze the early risk factors for peripheral neuropathy in patients with type 2 diabetes, even in the absence of specific clinical symptoms or signs. Finally, the random forest algorithm was used to rank the influencing factors and construct a predictive model, and then the model performance was evaluated. Logistic regression analysis revealed that vitamin D plays a crucial protective role in preventing diabetic peripheral neuropathy. The top three risk factors with significant contributions to the model in the random forest algorithm eigenvalue ranking were glycosylated hemoglobin, disease duration, and vitamin D. The areas under the receiver operating characteristic curve of the model ware 0.90. The accuracy, precision, specificity, and sensitivity were 0.85, 0.83, 0.92, and 0.71, respectively. The predictive model, which is based on the random forest algorithm, is intended to support clinical decision-making by healthcare professionals and help them target timely interventions to key factors in early diabetic peripheral neuropathy.

基于随机森林的 2 型糖尿病周围神经病变早期风险预测模型的构建
糖尿病周围神经病变是糖尿病晚期致残和致死的主要原因。我们利用医院电子病历数据库进行了一次回顾性病历审查,确定了 1020 名符合标准的患者。本研究的目的是探索和分析 2 型糖尿病患者发生周围神经病变的早期风险因素,即使没有特定的临床症状或体征。最后,采用随机森林算法对影响因素进行排序并构建预测模型,然后对模型的性能进行评估。逻辑回归分析表明,维生素 D 在预防糖尿病周围神经病变方面起着至关重要的保护作用。在随机森林算法特征值排序中,对模型有显著贡献的前三个风险因素是糖化血红蛋白、病程和维生素 D。准确度、精确度、特异性和灵敏度分别为 0.85、0.83、0.92 和 0.71。该预测模型基于随机森林算法,旨在为医护人员的临床决策提供支持,帮助他们针对早期糖尿病周围神经病变的关键因素及时采取干预措施。
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来源期刊
Cin-Computers Informatics Nursing
Cin-Computers Informatics Nursing 工程技术-护理
CiteScore
2.00
自引率
15.40%
发文量
248
审稿时长
6-12 weeks
期刊介绍: For over 30 years, CIN: Computers, Informatics, Nursing has been at the interface of the science of information and the art of nursing, publishing articles on the latest developments in nursing informatics, research, education and administrative of health information technology. CIN connects you with colleagues as they share knowledge on implementation of electronic health records systems, design decision-support systems, incorporate evidence-based healthcare in practice, explore point-of-care computing in practice and education, and conceptually integrate nursing languages and standard data sets. Continuing education contact hours are available in every issue.
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