Risk factor analysis of device-related infections: value of re-sampling method on the real-world imbalanced dataset
Risk factor analysis of device-related infections: value of re-sampling method on the real-world imbalanced dataset
复制标题
设备相关感染的风险因素分析：重采样方法在现实世界不平衡数据集上的价值
DOI：
10.1186/s12911-019-0899-4
复制
发表时间：
2019-09-11
影响因子：
3.5
通讯作者：
Li, Yi-Gang
中科院分区：
文献类型：
--
作者：
Feng, Xiang-Fei;Ya, Ling-Chao;Li, Yi-Gang
背景心脏植入式电子设备感染（CIEDI）的发病率较低，通常属于典型的不平衡数据集。我们试图描述我们的经验，对不平衡的CIEDI dataset.MethodsDatabase的管理从2001年至2016年接受设备植入的患者的两个中心进行了回顾性审查。重新采样技术被用来提高分类器的accuracy. ResultsCIEDI被确定在28 4959程序（0.56%）;一个高度的不平衡存在的患者配置文件的大小。单因素分析显示，置换术和男性患者的CIEDI增加（53.6%vs.23.4，0.8%vs.0.3%，P <0.01）。多因素Logistic回归分析显示，性别（比值比，OR = 3.503），年龄（OR = 1.032），置换术（OR = 3.503），以及抗生素的使用（OR = 0.250）仍然是CIEDI的独立预测因素（均P <0.05）在调整糖尿病、术后发热和器械类型后，在重新采样后，在分析的队列中有616个欠采样病例和123个过采样病例。结论应用再抽样技术可以产生有用的合成样本，用于不平衡数据的分类，提高CIEDI疗效预测的准确性。对于男性和老年患者以及接受替代手术的患者，应加强围手术期评估CIEDI的风险。
BackgroundThe incidence of cardiac implantable electronic device infection (CIEDI) is low and usually belongs to the typical imbalanced dataset. We sought to describe our experience on the management of the imbalanced CIEDI dataset.MethodsDatabase from two centers of patients undergoing device implantation from 2001 to 2016 were reviewed retrospectively. Re-sampling technique was used to improve the classifier accuracy.ResultsCIEDI was identified in 28 out of 4959 procedures (0.56%); a high imbalance existed in the sizes of the patient profiles. In univariate analyses, replacement procedure and male were significantly associated with an increase in CIEDI: (53.6% vs. 23.4, 0.8% vs. 0.3%,P< 0.01). Multivariate logistic regression analysis showed that gender (odds ratio, OR = 3.503), age (OR = 1.032), replacement procedure (OR = 3.503), and use of antibiotics (OR = 0.250) remained as independent predictors of CIEDI (allP< 0.05) after adjustment for diabetes, post-operation fever, and device style, device company.There were 616 under-sampled cases and 123 over-sampled cases in the analyzed cohort after re-sampling. The re-sampling and bootstrap results were robust and largely like the analysis results prior re-sampling method, while use of antibiotics lost the predicting capacity for CIEDI after re-sampling technique (P> 0.05).ConclusionThe application of re-sampling techniques can generate useful synthetic samples for the classification of imbalanced data and improve the accuracy of predicting efficacy of CIEDI. The peri-operative assessment should be intensified in male and aged patients as well as patients receiving replacement procedures for the risk of CIEDI.