Serum procalcitonin (PCT) and C-reactive protein (CRP) are biomarkers of infection. In patients with hematologic disorders with or without hematopoietic stem cell transplantation (HSCT), it is difficult to distinguish bloodstream infections from aseptic causes of febrile episodes. The objective of this study was to investigate diagnostic values of PCT and CRP in predicting systemic bacterial infection in patients with hematologic malignancies. Clinical and laboratory data of 614 febrile episode cases from 511 patients were analyzed. Febrile episodes were classified into four groups: (1) culture-positive bacterial infection by Gram-positive cocci (GPC), (2) culture-positive bacterial infection by Gram-negative bacilli (GNB), (3) fungal infection, and (4) viral infection or a noninfectious etiology. Of 614 febrile cases, systemic bacterial infections were confirmed in 99 (16.1%) febrile episodes, including 38 (6.2%) GPC and 61 (9.9%) GNB infections. PCT levels were significantly higher in GNB infectious episodes than those in febrile episodes caused by fungal infection (0.58 ng/mL (95% CI: 0.26–1.61) vs. 0.22 ng/mL (0.16–0.38), P = 0.047). Bacterial infectious episodes showed higher PCT and CRP levels than non-bacterial events (PCT: 0.49 (0.26–0.93) ng/mL vs. 0.20 (0.18–0.22) ng/mL, P < 0.001; CRP: 76.6 (50.5–92.8) mg/L vs. 58.0 (51.1–66.5) mg/L, P = 0.036). For non-neutropenic febrile episodes, both PCT and CRP discriminated bacteremia from non-bacteremia. However, in neutropenic febrile episodes, PCT only distinguished bacteremia from non-bacteremia. In non-neutropenic episode, both PCT and CRP showed good diagnostic accuracy (AUC: 0.757 vs. 0.763). In febrile neutropenia, only PCT discriminated bacteremia from non-bacterial infection (AUC: 0.624) whereas CRP could not detect bacteremia (AUC: 0.500, 95% CI: 0.439–0.561, P > 0.05). In this single-center observational study, PCT was more valuable than CRP for discriminating between bacteremia and non-bacteremia independent of neutropenia or HSCT.

Background and Objective Since the initial coronavirus disease outbreak in late 2019 (COVID-19), reverse-transcription real-time polymerase chain reaction (RT-qPCR) has become the gold standard test to detect severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2). However, a more sensitive and accurate diagnostic tool was required. Therefore, droplet digital polymerase chain reaction (ddPCR) was suggested as an alternative method. Here, we evaluated the performance of ddPCR to detect SARS-CoV-2 and compared it to the performance of RT-qPCR. Methods The analytical performances, including limit of blank and limit of detection, were established using positive and negative SARS-CoV-2 reference materials. A total of 366 RNA extracts (173 positive and 193 negative by RT-qPCR) were collected from four institutions and tested with a Bio-Rad SARS-CoV-2 ddPCR kit that detects the SARS-CoV-2 genome using primers for N1 and N2. Results Limit of blank was set at 0, and the limits of detection of N1 and N2 were 1.99 copies/μL and 5.18 copies/μL, respectively. Linearity was evaluated using serial dilution samples, which demonstrated good results (R²: 0.999, linear range: 5.88–6825.25 copies/μL for N1 and R²: 0.999, 5.53–5855.47 copies/μL for N2). The results of ddPCR and RT-qPCR revealed substantial agreement (Cohen’s kappa: 0.639, p < 0.01). The 63 samples with positive ddPCR but negative RT-qPCR showed low copy numbers, and 55% of them had COVID-19-related symptoms. Conclusions Droplet digital polymerase chain reaction demonstrated excellent sensitivity for SARS-Cov-2 detection and consistently agreed with the results from conventional RT-qPCR. Furthermore, ddPCR provided quantitative data that can be used to monitor changes in the viral load of patients with COVID-19.

Jaewoong Lee, M.D., Joonhong Park, Ph.D., Hayoung Choi, B.S., Jiyeon Kim, B.S., Ahlm Kwon, B.S., Woori Jang, Ph.D., Hyojin Chae, Ph.D., Myungshin Kim, Ph.D., Yonggoo Kim, Ph.D., Jae Wook Lee, Ph.D., Nack-Gyun Chung, Ph.D., and Bin Cho, Ph.D.. Ann Lab Med 2017;37:108-16. https://doi.org/10.3343/alm.2017.37.2.108

Lee J, et al. Ann Lab Med. 2017 Jan;37(1):39-44. https://doi.org/10.3343/alm.2017.37.1.39

Lee JM, et al. Ann Lab Med. 2018 Sep;38(5):492-494. https://doi.org/10.3343/alm.2018.38.5.492