Eberly, Allison R.

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.

Multidrug-resistant Pseudomonas aeruginosa isolates are a serious public health concern due to their resistance to nearly all or all of the available antibiotics, including carbapenems. Utilizing molecular approaches in conjunction with antibiotic susceptibility prediction software warrants investigation for use in the clinical laboratory workflow.

Antibiotic resistance, particularly to carbapenems, is of increasing concern in Bacteroides fragilis . Carbapenem resistance in B. fragilis is most often mediated by the activation of chromosomally encoded metallo-β-lactamase cfiA by the presence of an upstream insertion sequence (IS).

Abstract Background In 2018, the Clinical Microbiology Laboratory at our institution adopted updated daptomycin Enterococcus–susceptible dose-dependent breakpoints. While the introduction of susceptible dose-dependent (SDD) was intended to guide practice toward optimal dosing, the understanding and application of daptomycin SDD breakpoints for enterococci were unknown. Methods This mixed-methods study combined a clinician survey with a retrospective pre–post prescribing analysis. An 8-question survey was distributed to infectious diseases (ID) and internal medicine (IM) clinicians. A retrospective chart review of hospitalized adults with infections due to Enterococcus spp. was conducted before (pre-SDD) and after (post-SDD) adoption of SDD reporting for enterococci. Results Survey response rates were 40 of 98 (41%) for IM and 22 of 34 (65%) for ID clinicians. ID clinicians scored significantly higher than IM clinicians in knowledge of SDD. Chart review of 474 patients (225 pre- vs 249 post-SDD) showed that daptomycin dosage following susceptibility testing was significantly higher post-SDD compared with pre-SDD (8.5 mg/kg vs 6.4 mg/kg; P < .001) with no difference in empiric dosing (6.3 mg/kg vs 6.2 mg/kg; P = .67). Definitive daptomycin use varied between the pre- and post-SDD periods (35.1% vs 16.9%; P < .001). Conclusions The survey revealed that ID clinicians placed more importance on and had more confidence in the SDD category over IM clinicians. SDD reporting was associated with a change in definitive daptomycin dosing. ID specialist involvement is recommended in the care of infections due to enterococci for which daptomycin is reported as SDD given their expertise.