The performance of point-of-care antibody test for COVID-19 diagnosis in a tertiary hospital in Bandung, Indonesia.

INTRODUCTION: We aim to describe the performance of combined IgM and IgG point-of-care antibody test (POC-Ab) (Wondfo®) compared to real-time reverse transcriptase (rRT-PCR) (Allplex™ 2019-nCoV Assay) in detecting coronavirus disease 2019 (COVID-19). METHODOLOGY: We compared POC-Ab with rRT-PCR results among patients in a tertiary hospital from January to March 2020 in Bandung, Indonesia. We selected presumptive COVID-19 patients with positive rRT-PCR consecutively and 20 patients with negative rRT-PCR results were selected randomly from the same group of patients as controls. We described the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) with corresponding 95% confidence interval using serum and capillary blood samples. We also tested POC-Ab using non-COVID-19 (confirmed dengue and typhoid) patients' sera. RESULTS: Twenty-seven patients with positive rRT-PCR result and 20 negative controls were included (68.1% males, mean age 46 (SD: 15.4)). Using the serum, the sensitivity of the POC-Ab was 63.0% (42.4-80.6), specificity was 95.0% (75.1-99.9), PPV was 94.4% (72.7-99.8), NPV was 65.5% (45.7-82.1). A subset of 20 patients was tested using a capillary blood sample. The accuracy of the capillary blood sample is lower compared to serum (50.0% vs. 78.7%). None of the non-COVID-19 sera tested were reactive. CONCLUSIONS: POC-Ab for COVID-19 has a high specificity with no false-positive result in non-COVID-19 sera. Therefore, it can be used to guide diagnostic among symptomatic patients in resource limited settings. Given its low sensitivity, patients with high suspicion of COVID-19 but non-reactive result should be prioritized for rRT-PCR testing.

A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia.

BACKGROUND: Distinguishing arboviral infections from bacterial causes of febrile illness is of great importance for clinical management. The Infection Manager System (IMS) is a novel diagnostic algorithm equipped on a Sysmex hematology analyzer that evaluates the host response using novel techniques that quantify cellular activation and cell membrane composition. The aim of this study was to train and validate the IMS to differentiate between arboviral and common bacterial infections in Southeast Asia and compare its performance against C-reactive protein (CRP) and procalcitonin (PCT). METHODOLOGY/PRINCIPAL FINDINGS: 600 adult Indonesian patients with acute febrile illness were enrolled in a prospective cohort study and analyzed using a structured diagnostic protocol. The IMS was first trained on the first 200 patients and subsequently validated using the complete cohort. A definite infectious etiology could be determined in 190 of 463 evaluable patients (41%), including 89 arboviral infections (81 dengue and 8 chikungunya), 94 bacterial infections (26 murine typhus, 16 salmonellosis, 6 leptospirosis and 46 cosmopolitan bacterial infections), 3 concomitant arboviral-bacterial infections, and 4 malaria infections. The IMS detected inflammation in all but two participants. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the IMS for arboviral infections were 69.7%, 97.9%, 96.9%, and 77.3%, respectively, and for bacterial infections 77.7%, 93.3%, 92.4%, and 79.8%. Inflammation remained unclassified in 19.1% and 22.5% of patients with a proven bacterial or arboviral infection. When cases of unclassified inflammation were grouped in the bacterial etiology group, the NPV for bacterial infection was 95.5%. IMS performed comparable to CRP and outperformed PCT in this cohort. CONCLUSIONS/SIGNIFICANCE: The IMS is an automated, easy to use, novel diagnostic tool that allows rapid differentiation between common causes of febrile illness in Southeast Asia.