Vujevic Matea, Benzon Benjamin, Markic Josko
University of Split School of Medicine, Soltanska 2.
University Hospital Centre Split, Department of Pediatrics, Spinciceva 1, Split, Croatia.
Turk J Pediatr. 2017;59(3):261-268. doi: 10.24953/turkjped.2017.03.005.
Vujevic M, Benzon B, Markic J. New prediction model for diagnosis of bacterial infection in febrile infants younger than 90 days. Turk J Pediatr 2017; 59: 261-268. Due to non-specific clinical presentation in febrile infants, extensive laboratory testing is often carried out to distinguish simple viral disease from serious bacterial infection (SBI). Objective of this study was to compare efficacy of different biomarkers in early diagnosis of SBI in infants < 90 days old. Also, we developed prediction models with whom it will be possible to diagnose SBI with more accuracy than with any biomarkers independently. Febrile < 90-day-old infants hospitalized in 2-year-period at Department of Pediatrics, University Hospital Centre Split with suspicion of having SBI were included in this study. Retrospective cohort analysis of data acquired from medical records was performed. Out of 181 enrolled patients, SBI was confirmed in 70. Most common diagnosis was urinary tract infection (68.6%), followed by pneumonia (12.9%), sepsis (11.4%), gastroenterocolitis (5.7%) and meningitis (1.4%). Male gender was shown to be a risk factor for SBI in this population (p=0.008). White blood cell count (WBC), absolute neutrophil count (ANC) and C-reactive protein (CRP) were confirmed as the independent predictors of SBI, with CRP as the best one. Two prediction models built by combining biomarkers and clinical variables were selected as optimal with sensitivities of 74.3% and 75.7%, and specificities of 88.3% and 86%. Evidently, CRP is a more superior biomarker in diagnostics of SBI comparing to WBC and ANC. Prediction models were shown to be better in predicting SBI than independent biomarkers. Although both showed high sensitivity and specificity, their true strength should be determined using validation cohort.
武耶维奇M、本宗B、马尔基奇J。90日龄以下发热婴儿细菌感染诊断的新预测模型。《土耳其儿科学杂志》2017年；59：261 - 268。由于发热婴儿的临床表现不具特异性，常需进行广泛的实验室检查以区分单纯病毒性疾病与严重细菌感染（SBI）。本研究的目的是比较不同生物标志物在90日龄以下婴儿SBI早期诊断中的效能。此外，我们开发了预测模型，与单独使用任何生物标志物相比，利用这些模型能够更准确地诊断SBI。本研究纳入了在斯普利特大学医院中心儿科住院两年期间疑似患有SBI的90日龄以下发热婴儿。对从病历中获取的数据进行了回顾性队列分析。在181名登记患者中，70例确诊为SBI。最常见的诊断是尿路感染（68.6%），其次是肺炎（12.9%）、败血症（11.4%）、胃肠结肠炎（5.7%）和脑膜炎（1.4%）。在该人群中，男性被证明是SBI的一个危险因素（p = 0.008）。白细胞计数（WBC）、绝对中性粒细胞计数（ANC）和C反应蛋白（CRP）被确认为SBI的独立预测指标，其中CRP是最佳指标。通过结合生物标志物和临床变量构建的两个预测模型被选为最优模型，其灵敏度分别为74.3%和75.7%，特异度分别为88.3%和86%。显然，与WBC和ANC相比，CRP在SBI诊断中是更优越的生物标志物。预测模型在预测SBI方面比独立生物标志物表现更好。尽管两者都显示出高灵敏度和特异度，但它们的真正优势应通过验证队列来确定。
