Fernholz, Emily C

Abstract Background In 2021, the state of Arizona experienced the largest focal outbreak of West Nile virus (WNV) in US history. Timely and accurate diagnostic testing remains a challenge for WNV due to transient viremia and limited immunoassay specificity. Recent studies have identified whole blood (WB) and urine as more sensitive specimen types for the detection of WNV RNA. Methods We evaluated ordering practices, test performance, and patient characteristics of probable and confirmed cases. In total, we identified 190 probable and proven cases, including 127 patients (66.8%) with neuroinvasive disease. Results Among all cases, only 29.5% had WNV polymerase chain reaction (PCR) testing ordered on WB, of which 80.3% resulted as positive, including 7 cases in which WNV serologic testing was negative and 5 cases for which serologic testing was not ordered. In comparison, only 23.7% of cases that had cerebrospinal fluid (CSF) PCR ordered had a positive result, including 3 cases that were negative by PCR on WB. In contrast, WNV PCR on WB detected 12 neuroinvasive cases that were CSF PCR negative. WNV PCR testing in urine was only ordered on 2 patients, both of whom were positive. Crossing cycle threshold (Ct) values were not significantly different between WB and CSF specimen types, nor was there a correlation between Ct value and days from symptom onset at the time of sample collection; all specimen types and time points had Ct values, with 98% above 30. WB was positive by WNV PCR in several patients for >7 days (range, 7–25 days) after symptom onset, as was the CSF PCR. Conclusions Taken together, these findings indicate that WNV PCR testing on WB may be the best initial test for timely diagnosis of WNV infection, irrespective of clinical manifestation; however, if negative in patients with suspected neuroinvasive disease, WNV PCR testing on CSF should be ordered.

Abstract Objectives Recent work has demonstrated that automated fluorescence flow cytometry (FLC) is a potential alternative for the detection and quantification of Plasmodium parasites. The objective of this study was to apply this novel FLC method to detect and quantify Babesia parasites in venous blood and compare results to light microscopy and polymerase chain reaction methods. Methods An automated hematology/malaria analyzer (XN-31; Sysmex) was used to detect and quantify B microti–infected red blood cells from residual venous blood samples (n = 250: Babesia positive, n = 170; Babesia negative, n = 80). As no instrument software currently exists for Babesia, qualitative and quantitative machine learning (ML) algorithms were developed to facilitate analysis. Results Performance of the ML models was verified against the XN-31 software using P falciparum–infected samples. When applied to Babesia-infected samples, the qualitative ML model demonstrated an area under the curve (AUC) of 0.956 (sensitivity, 95.9%; specificity, 83.3%) relative to polymerase chain reaction. For valid scattergrams, the qualitive model achieved an AUC of 1.0 (sensitivity and specificity, 100%), while the quantitative model demonstrated an AUC of 0.986 (sensitivity, 94.4%; specificity, 100%). Conclusions This investigation demonstrates that Babesia parasites can be detected and quantified directly from venous blood using FLC. Although promising, opportunities remain to improve the general applicability of the method.