FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections.

Due to the high prevalence of patients attending with urinary tract infection (UTI) symptoms, the use of flow-cytometry as a rapid screening tool to avoid unnecessary cultures is becoming a widely used system in clinical practice. However, the recommended cut-points applied in flow-cytometry systems differ substantially among authors, making it difficult to obtain reliable conclusions. Here, we present FlowUTI, a shiny web-application created to establish optimal cut-off values in flow-cytometry for different UTI markers, such as bacterial or leukocyte counts, in urine from patients with UTI symptoms. This application provides a user-friendly graphical interface to perform robust statistical analysis without a specific training. Two datasets are analyzed in this manuscript: one composed of 204 urine samples from neonates and infants (≤3 months old) attended in the emergency department with suspected UTI; and the second dataset including 1174 urines samples from an elderly population attended at the primary care level. The source code is available on GitHub (https://github.com/GuillermoMG-HUVR/Microbiology-applications/tree/FlowUTI/FlowUTI). The web application can be executed locally from the R console. Alternatively, it can be freely accessed at https://covidiario.shinyapps.io/flowuti/. FlowUTI provides an easy-to-use environment for evaluating the efficiency of the urinary screening process with flow-cytometry, reducing the computational burden associated with this kind of analysis.

Optimization and adaptation of the diagnostic capacity for the performance of large volumes of SARS-CoV-2 RT-PCR☆ Optimización y adecuación de la capacidad diagnóstica para la realización de grandes volúmenes de RT-PCR de SARS-CoV-2

Introduction In the present manuscript we describe the planning carried out in our hospital to adapt our diagnostic capability to perform large numbers of SARS-CoV-2 RT-PCR. Methods The analysis and prediction of workflow included the number of RT-PCR per week from the beginning of the pandemic, with a total of 31971 determinations. The planning phase was developed based on the different scenarios previously predicted. Results According to the predictions obtained, an automated custom solution was chosen, based on the use of the OT-2 open-source liquid-handling robots (Opentrons), to design a reproducible workflow that achieved a production capacity of 5640 samples/day, with a time of response of four hours per procedure. Conclusions The analysis and prediction of workflow, along with the use of the robotic platforms OT-2, provided a robust structure to deal with the high demand of determinations that this pandemic requires.

Optimization and adaptation of the diagnostic capacity for the performance of large volumes of SARS-CoV-2 RT-PCR.

INTRODUCTION: In the present manuscript we describe the planning carried out in our hospital to adapt our diagnostic capability to perform large numbers of SARS-CoV-2 RT-PCR. METHODS: The analysis and prediction of workflow included the number of RT-PCR per week from the beginning of the pandemic, with a total of 31971 determinations. The planning phase was developed based on the different scenarios previously predicted. RESULTS: According to the predictions obtained, an automated custom solution was chosen, based on the use of the OT-2 open-source liquid-handling robots (Opentrons), to design a reproducible workflow that achieved a production capacity of 5640 samples/day, with a time of response of four hours per procedure. CONCLUSIONS: The analysis and prediction of workflow, along with the use of the robotic platforms OT-2, provided a robust structure to deal with the high demand of determinations that this pandemic requires.

Optimization and adaptation of the diagnostic capacity for the performance of large volumes of SARS-CoV-2 RT-PCR. / Optimización y adecuación de la capacidad diagnóstica para la realización de grandes volúmenes de RT-PCR de SARS-CoV-2.

INTRODUCTION: In the present manuscript we describe the planning carried out in our hospital to adapt our diagnostic capability to perform large numbers of SARS-CoV-2 RT-PCR. METHODS: The analysis and prediction of workflow included the number of RT-PCR per week from the beginning of the pandemic, with a total of 31971 determinations. The planning phase was developed based on the different scenarios previously predicted. RESULTS: According to the predictions obtained, an automated custom solution was chosen, based on the use of the OT-2 open-source liquid-handling robots (Opentrons), to design a reproducible workflow that achieved a production capacity of 5640 samples/day, with a time of response of four hours per procedure. CONCLUSIONS: The analysis and prediction of workflow, along with the use of the robotic platforms OT-2, provided a robust structure to deal with the high demand of determinations that this pandemic requires.

Impact of the COVID-19 Pandemic on Antimicrobial Consumption and Hospital-Acquired Candidemia and Multidrug-Resistant Bloodstream Infections.

During the COVID-19 pandemic, the implementation of antimicrobial stewardship strategies has been recommended. This study aimed to assess the impact of the COVID-19 pandemic in a tertiary care Spanish hospital with an active ongoing antimicrobial stewardship programme (ASP). For a 20-week period, we weekly assessed antimicrobial consumption, incidence density, and crude death rate per 1000 occupied bed days of candidemia and multidrug-resistant (MDR) bacterial bloodstream infections (BSI). We conducted a segmented regression analysis of time series. Antimicrobial consumption increased +3.5% per week (p = 0.016) for six weeks after the national lockdown, followed by a sustained weekly reduction of -6.4% (p = 0.001). The global trend for the whole period was stable. The frequency of empirical treatment of patients with COVID-19 was 33.7%. No change in the global trend of incidence of hospital-acquired candidemia and MDR bacterial BSI was observed (+0.5% weekly; p = 0.816), nor differences in 14 and 30-day crude death rates (p = 0.653 and p = 0.732, respectively). Our work provides quantitative data about the pandemic effect on antimicrobial consumption and clinical outcomes in a centre with an active ongoing institutional and education-based ASP. However, assessing the long-term impact of the COVID-19 pandemic on antimicrobial resistance is required.