首页> 外文期刊>BMC Pediatrics >Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
【24h】

Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study

机译:新生儿迟发菌血症筛查工具的开发,评估和验证–一项初步研究

获取原文
获取外文期刊封面目录资料

摘要

Clinical and laboratory parameters can aid in the early identification of neonates at risk for bacteremia before clinical deterioration occurs. However, current prediction models have poor diagnostic capabilities. The objective of this study was to develop, evaluate and validate a screening tool for late onset (?72?h post admission) neonatal bacteremia using common laboratory and clinical parameters; and determine its predictive value in the identification of bacteremia. A retrospective chart review of neonates admitted to a neonatal intensive care unit (NICU) between March 1, 2012 and January 14, 2015 and a prospective evaluation of all neonates admitted between January 15, 2015 and March 30, 2015 were completed. Neonates with late-onset bacteremia (?72?h after NICU admission) were eligible for inclusion in the bacteremic cohort. Bacteremic patients were matched to non-infected controls on several demographic parameters. A Pearson’s Correlation matrix was completed to identify independent variables significantly associated with infection (p??0.05, univariate analysis). Significant parameters were analyzed using iterative binary logistic regression to identify the simplest significant model (p??0.05). The predictive value of the model was assessed and the optimal probability cut-off for bacteremia was determined using a Receiver Operating Characteristic curve. Maximum blood glucose, heart rate, neutrophils and bands were identified as the best predictors of bacteremia in a significant binary logistic regression model. The model’s sensitivity, specificity and accuracy were 90, 80 and 85%, respectively, with a false positive rate of 20% and a false negative rate of 9.7%. At the study bacteremia prevalence rate of 51%, the positive predictive value, negative predictive value and negative post-test probability were 82, 89 and 11%, respectively. The model developed in the current study is superior to currently published neonatal bacteremia screening tools. Validation of the tool in a historic data set of neonates from our institution will be completed.
机译:临床和实验室参数可帮助在临床恶化发生之前及早识别出有菌血症风险的新生儿。但是,当前的预测模型的诊断能力较差。这项研究的目的是使用共同的实验室和临床参数,开发,评估和验证针对迟发性新生儿细菌血症(入院后≥72小时)的筛查工具。并确定其在菌血症鉴定中的预测价值。已完成对2012年3月1日至2015年1月14日入院的新生儿重症监护病房(NICU)的回顾性图表回顾,并对2015年1月15日至2015年3月30日入院的所有新生儿进行了前瞻性评估。迟发性菌血症的新生儿(入院重症监护病房后≥72小时)符合纳入菌群的条件。细菌血症患者在几个人口统计学参数上与未感染的对照组相匹配。培生相关系数矩阵得以完成,以识别与感染显着相关的自变量(p <0.05,单变量分析)。使用迭代二元logistic回归分析重要参数,以识别最简单的重要模型(p <0.05)。评估模型的预测值,并使用接收器工作特征曲线确定菌血症的最佳概率临界值。在重要的二元逻辑回归模型中,最高血糖,心率,中性粒细胞和条带被确定为菌血症的最佳预测指标。该模型的敏感性,特异性和准确性分别为90%,80%和85%,假阳性率为20%,假阴性率为9.7%。在研究的菌血症患病率为51%时,阳性预测值,阴性预测值和阴性后测概率分别为82%,89%和11%。本研究开发的模型优于当前发布的新生儿菌血症筛查工具。我们机构的新生儿历史数据集中的工具验证将完成。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号