Mithal Leena B, Yogev Ram, Palac Hannah L, Kaminsky Daniel, Gur Ilan, Mestan Karen K
Department of Pediatrics, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Department of Pediatrics, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Early Hum Dev. 2018 Feb;117:83-89. doi: 10.1016/j.earlhumdev.2018.01.008. Epub 2018 Jan 23.
Nonspecific clinical signs and suboptimal diagnostic tests limit accurate identification of late onset sepsis (LOS) and necrotizing enterocolitis (NEC) in premature infants, resulting in significant morbidity and antibiotic overuse. An infant's systemic inflammatory response may be identified earlier than clinical suspicion through analysis of multiple vital signs by a computerized algorithm (RALIS).
To evaluate the revised RALIS algorithm for detection of LOS and NEC in preterm infants.
In this nested case-control study, VS data (heart rate, respiratory rate, temperature, desaturations, bradycardias) were extracted from medical records of infants 23-32 weeks gestation. RALIS generated an output, with score ≥ 5 triggering an alert. Patient episodes were classified based on culture, radiograph, and antibiotic data into categories: LOS, expanded LOS, NEC, and controls. Paired t-tests, linear regression and cross-validation analyses were used to evaluate the relationship between RALIS alert and LOS/NEC.
Among 155 infants with 161 episodes, there were 41 expanded LOS (+blood, CSF, urine, respiratory culture), 31 LOS (+blood, CSF, urine), 9 NEC, and 93 controls. RALIS alert was 43.1 ± 79 h before culture in LOS (p = .012). There was a significant association between RALIS alert and LOS/NEC (β = 0.72, p < .0001). Sensitivity and specificity for LOS/NEC were 84% and 80%, (PPV = 63%; NPV = 93%). The regression model demonstrated an AUC of 89.9%.
For infants ≤32 weeks, RALIS detects systemic inflammatory responses in LOS and NEC in the first month of life. The algorithm can identify infection earlier than clinical suspicion, even for NEC with negative cultures. RALIS has high NPV to rule-out LOS and NEC, and may, after prospective validation, aid in antibiotic treatment decisions.
非特异性临床体征和欠佳的诊断测试限制了对早产儿晚发性败血症(LOS)和坏死性小肠结肠炎(NEC)的准确识别,导致显著的发病率和抗生素过度使用。通过计算机算法(RALIS)分析多个生命体征,可能比临床怀疑更早地识别婴儿的全身炎症反应。
评估修订后的RALIS算法在检测早产儿LOS和NEC中的作用。
在这项嵌套病例对照研究中,从妊娠23 - 32周婴儿的医疗记录中提取生命体征数据(心率、呼吸频率、体温、血氧饱和度下降、心动过缓)。RALIS生成一个输出结果,分数≥5会触发警报。根据培养、X光片和抗生素数据将患者发作情况分为以下几类:LOS、扩展LOS、NEC和对照。采用配对t检验、线性回归和交叉验证分析来评估RALIS警报与LOS/NEC之间的关系。
在155名婴儿的161次发作中,有41次扩展LOS(血液、脑脊液、尿液、呼吸道培养阳性),31次LOS(血液、脑脊液、尿液培养阳性),9次NEC,以及93次对照。在LOS中,RALIS警报比培养结果提前43.1±79小时(p = 0.012)。RALIS警报与LOS/NEC之间存在显著关联(β = 0.72,p < 0.0001)。LOS/NEC的敏感性和特异性分别为84%和80%(阳性预测值 = 63%;阴性预测值 = 93%)。回归模型显示曲线下面积为89.9%。
对于孕周≤32周的婴儿,RALIS可在出生后第一个月检测出LOS和NEC中的全身炎症反应。该算法能够比临床怀疑更早地识别感染,即使对于培养结果为阴性的NEC也是如此。RALIS具有较高的阴性预测值以排除LOS和NEC,并且在前瞻性验证后,可能有助于抗生素治疗决策。