Laboratório de Microbiologia, Department of Basic Health Sciences, State University of Maringá, Avenida Colombo 5790, Maringá, Paraná, 87020-900, Brazil.
Maringá University Hospital, State University of Maringá, Maringá, Paraná, Brazil.
Sci Rep. 2022 Sep 14;12(1):15466. doi: 10.1038/s41598-022-19643-1.
This study evaluated routine laboratory biomarkers (RLB) to predict the infectious bacterial group, Gram-positive (GP) or Gram-negative (GN) associated with bloodstream infection (BSI) before the result of blood culture (BC). A total of 13,574 BC of 6787 patients (217 BSI-GP and 238 BSI-GN) and 68 different RLB from these were analyzed. The logistic regression model was built considering BSI-GP or BSI-GN as response variable and RLB as covariates. After four filters applied total of 320 patients and 16 RLB remained in the Complete-Model-CM, and 4 RLB in the Reduced-Model-RM (RLB p > 0.05 excluded). In the RM, only platelets, creatinine, mean corpuscular hemoglobin and erythrocytes were used. The reproductivity of both models were applied to a test bank of 2019. The new model presented values to predict BSI-GN of the area under the curve (AUC) of 0.72 and 0.69 for CM and RM, respectively; with sensitivity of 0.62 and 0.61 (CM and RM) and specificity of 0.67 for both. These data confirm the discriminatory capacity of the new models for BSI-GN (p = 0.64). AUC of 0.69 using only 4 RLB, associated with the patient's clinical data could be useful for better targeted antimicrobial therapy in BSI.
本研究评估了常规实验室生物标志物（RLB），以在血液培养（BC）结果之前预测与血流感染（BSI）相关的感染性细菌群，革兰氏阳性（GP）或革兰氏阴性（GN）。分析了来自 6787 名患者的 13574 次 BC（217 次 BSI-GP 和 238 次 BSI-GN）和 68 种不同的 RLB。考虑到 BSI-GP 或 BSI-GN 作为因变量和 RLB 作为协变量，构建了逻辑回归模型。经过四个过滤器的应用，共有 320 名患者和 16 个 RLB 留在完整模型-CM 中，而简化模型-RM 中则有 4 个 RLB（排除 RLB p > 0.05）。在 RM 中，仅使用血小板、肌酐、平均红细胞血红蛋白和红细胞。这两个模型的重现性都应用于 2019 年的测试库。新模型对革兰氏阴性菌血流感染（BSI-GN）的预测表现出 0.72 和 0.69 的曲线下面积（AUC）值；CM 和 RM 的敏感性分别为 0.62 和 0.61，特异性均为 0.67。这些数据证实了新模型对 BSI-GN 的区分能力（p=0.64）。仅使用 4 个 RLB 获得的 0.69 AUC，与患者的临床数据相结合，可能有助于在 BSI 中更好地靶向抗菌治疗。
