Routine laboratory biomarkers used to predict Gram-positive or Gram-negative bacteria involved in bloodstream infections

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作者
Daniela Dambroso-Altafini
Thatiany C. Menegucci
Bruno B. Costa
Rafael R. B. Moreira
Sheila A. B. Nishiyama
Josmar Mazucheli
Maria C. B. Tognim
机构
[1] State University of Maringá,Laboratório de Microbiologia, Department of Basic Health Sciences
[2] University Paranaense,Department of Medicine
[3] State University of Maringá,Maringá University Hospital
[4] State University of Maringá,Department of Statistic
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Scientific Reports | / 12卷
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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.
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