网站首页期刊介绍通知公告编 委 会投稿须知电子期刊广告合作联系我们
最新消息:
支持向量机与Logistic回归模型在早期识别早产儿革兰阴性菌晚发型败血症中的研究
作者:高正平  程序  寇晨 
单位:首都医科大学附属北京妇产医院/北京妇幼保健院 新生儿科, 北京 100026
关键词:支持向量机 Logistic回归 革兰阴性杆菌 晚发型败血症 倾向性评分匹配 早产儿 
分类号:R446.5
出版年·卷·期(页码):2024·52·第二期(173-181)
摘要:

目的:探讨支持向量机(SVM)与Logistic回归(LR)模型在早期识别早产儿革兰阴性菌晚发型败血症中的应用。方法:回顾分析2015年1月至2019年12月期间我院早产儿监护病房晚发型败血症血培养阳性患儿的临床资料。根据临床资料分为革兰阴性杆菌败血症组及非革兰阴性杆菌败血症组,采用倾向性评分1:1的比例对两组病例组中的混淆因素进行匹配,匹配成功后通过临床指标进行分析,分别采用SVM和LR建立预测模型。根据模型实用性,采用敏感度、特异度、阳性预测值、阴性预测值及受试者工作特征曲线下面积(AUC)等指标进行模型效果评价。应用净重新分类指数(NRI)评价两个模型的预测能力。结果:2015年1月至2019年12月住院期间晚发型败血症血培养阳性的早产儿共84例,其中革兰阴性杆菌败血症31例,非革兰阴性杆菌败血症53例。分别对两组混淆因素进行倾向性评分,成功匹配29对。选取19个临床指标经过SVM和LR建模后,最终SVM筛选出4个危险因素进行建模,LR筛选出3个危险因素进行建模。SVM模型的敏感度、特异度、阳性预测值、阴性预测值及AUC均优于LR模型。经过NRI计算,SVM模型的预测能力高于LR模型(P<0.05)。结论:在小样本分类预测方面,SVM模型比LR模型更具有实用价值。白细胞计数、中心静脉导管留置时长、脉压差和C-反应蛋白可以作为早期识别早产儿革兰阴性菌晚发型败血症的危险因素。

Objective: To investigate the application of support vector machine(SVM) and Logistic regression(LR) in the early identification of late-onset sepsis caused by gram-negative bacteria in preterm infants. Methods: A retrospective analysis was conducted on the clinical data of patients exhibiting positive blood cultures for late-onset sepsis in the neonatal intensive care unit from January 2015 to December 2019. Based on the clinical data, patients were categorized into the gram-negative bacilli sepsis group and the non-gram-negative bacilli sepsis group. Confounding factors in both groups were meticulously matched using a propensity score matching(PSM) of 1:1. Subsequently, clinical indicators were analyzed post-successful matching, and predictive models were formulated using SVM and LR. The models were assessed for practicality, incorporating sensitivity, specificity, positive predictive value, negative predictive value, and the area under the receiver operating characteristic curve(AUC). The net reclassification index(NRI) was employed to evaluate the predictive capabilities of both models. Results: A total of 84 preterm infants with positive blood cultures for late-onset sepsis were identified, comprising 31 cases of gram-negative bacilli sepsis and 53 cases of non-gram-negative bacilli sepsis. PSM was applied to the confounding factors in both groups, resulting in 29 successfully matched pairs. Nineteen clinical indicators were selected and modeled using SVM and LR, with SVM identifying 4 risk factors and LR identifying 3 risk factors. The SVM model demonstrated superiority over the LR model in terms of sensitivity, specificity, positive predictive value, negative predictive value, and AUC. Post-NRI calculation, the predictive ability of the SVM model was significantly higher than that of the LR model(P<0.05). Conclusion: The SVM model exhibits greater practical value than the LR model in the classification prediction of small sample sizes. White blood cell count, duration of central venous catheterization, pulse pressure, and C-reatative protein can be considered as viable risk factors for the early identification of late-onset sepsis caused by gram-negative bacteria in preterm infants.

参考文献:

[1] DONG Y,SPEER C P.Late-onset neonatal sepsis:recent developments[J].Arch Dis Child Fetal Neonatal Ed,2015,100(3):257-263.
[2] 中国医师协会新生儿科医师分会感染专业委员会,中华医学会儿科学分会早产儿学组.新生儿败血症诊断及治疗专家共识(2019年版)[J].中华儿科杂志,2019,57(4):252.
[3] JEMAL M,TINSHKU F,NIGUSSIE Y,et al.Trend analysis of multidrug-resistant bacterial pathogens causing neonatal sepsis at University of Gondar Comprehensive Specialized Hospital,Northwest Ethiopia:a retrospective study[J].Int J Microbiol,2021,2021:9992994.
[4] TING J Y,SYNNES A,ROBERTS A,et al.association of antibiotic utilization and neurodevelopmental outcomes among extremely low gestational age neonates without proven sepsis or necrotizing enterocolitis[J].Am J Perinatol,2018,35(10):972-978.
[5] HUANG Y,YU X,LI W,et al.Development and validation of a nomogram for predicting late-onset sepsis in preterm infants on the basis of thyroid function and other risk factors:mixed retrospective and prospective cohort study[J].J Adv Res,2020,24:43-51.
[6] AUSTIN P C,STUART E A.The effect of a constraint on the maximum number of controls matched to each treated subject on the performance of full matching on the propensity score when estimating risk differences[J].Stat Med,2021,40(1):101-118.
[7] GUPTA R,SRIVASTAVA D,SAHU M,et al.Artificial intelligence to deep learning:machine intelligence approach for drug discovery[J].Mol Divers,2021,25(3):1315-1360.
[8] KIDD A C,MCGETTRICK M,TSIM S,et al.Survival prediction in mesothelioma using a scalable Lasso regression model:instructions for use and initial performance using clinical predictors[J].BMJ Open Respir Res,2018,5(1):e000240.
[9] World Health Organization.Newborn mortality[EB/OL].(2022-01-28)[2023-08-15].https://www.who.int/news-room/fact-sheets/detail/levels-and-trends-in-child-mortality-report-2021.
[10] 吴艳蓉,梁跃波,彭发兵,等.新生儿早发型败血症与晚发型败血症病原菌分布及炎性因子变化比较[J].现代医学,2022,50(1):90-94.
[11] 许燕萍,商祯茹,DORAZIO R M,等.经外周静脉穿刺中心静脉置管患儿相关性血源感染的危险因素分析[J].中国当代儿科杂志,2022,24(2):141-146.
[12] MOROWITZ M J,KATHERIA A C,POLIN R A,et al.The NICU Antibiotics and Outcomes(NANO) trial:a randomized multicenter clinical trial assessing empiric antibiotics and clinical outcomes in newborn preterm infants[J].Trials,2022,23(1):428.
[13] WÓJKOWSKA-MACH J,GULCZYSKA E,NOWICZEWSKI M,et al.Late-onset bloodstream infections of very-low-birth-weight infants:data from the Polish Neonatology Surveillance Network in 2009-2011[J].BMC Infect Dis,2014,14:339.
[14] PEDUZZI P,CONCATO J,KEMPER E,et al.A simulation study of the number of events per variable in logistic regression analysis[J].J Clin Epidemiol,1996,49(12):1373-1379.
[15] 刘嘉欣,程琳,关颖,等.不同病原菌所致早产儿败血症的临床特点分析[J].中华早产儿科杂志,2020(3):181-185.
[16] 梅玮.新生儿晚发型败血症病因、临床特点和病原学分析[J].淮海医药,2012,30(3):244-245.
[17] 朱倩倩,王琍琍.极低/超低出生体重儿细菌性与真菌性晚发型败血症临床分析[J].中国当代医药,2021,28(24):162-166.
[18] FANG K,WANG P,ZHANG X,et al.Structured sparse support vector machine with ordered features[J].J Appl Stat,2020,49(5):1105-1120.
[19] BECKER N,WERFT W,TOEDT G,et al.PenalizedSVM:a R-package for feature selection SVM classification[J].Bioinformatics,2009,25(13):1711-1712.
[20] DABAJA-YOUNIS H,ATRASH-NIMRI N,DIAB S,et al.A high percentage of hospital-acquired neonatal bacteraemia but rare resistance to standard antibiotic regimens[J].Acta Paediatr,2022,111(5):992-1001.
[21] YOFFE DERI S,MELAMED R,MARKS K,et al.Early versus late-onset necrotizing enterocolitis in very low birth infants in the neonatal intensive care unit[J].Pediatr Surg Int,2022,38(2):235-240.
[22] CHERIFI S,BYL B,DEPLANO A,et al.Comparative epidemiology of Staphylococcus epidermidis isolates from patients with catheter-related bacteremia and from healthy volunteers[J].J Clin Microbiol,2013,51(5):1541-1547.
[23] 赵小朋,周伟,李旭芳,等.极低/超低出生体重儿迟发型败血症发生情况及其危险因素分析[J].中国当代儿科杂志,2017,19(11):1129-1133.

服务与反馈:
文章下载】【发表评论】【查看评论】【加入收藏
提示:您还未登录,请登录!点此登录
您是第 749243 位访问者


 ©《现代医学》编辑部
联系电话:025-83272481;83272479
电子邮件: xdyx@pub.seu.edu.cn

苏ICP备09058541