A 2020 review on the role of procalcitonin in different clinical settings: an update conducted with the tools of the Evidence Based Laboratory Medicine

Biomarkers to guide treatment decisions antibiotics has been proposed as an effective way to increase the use of more appropriate antibiotics. As a biomarker, procalcitonin (PCT) has been found to have good specificity to distinguish bacterial from non-bacterial inflammation. Decisions regarding the use of antibiotics in complex individual patient and should be based on the pre-test probability of bacterial infection, the severity of the presentation and the results of serum PCT concentrations.

In the context of high pre-test probability for bacterial infections and / or high-risk patients with sepsis, PCT monitoring from time to time helps to track the resolution of the initial infection and the decision about stopping of antibiotic treatment. As outlined by the Evidence-Based Medicine Laboratory (EBLM), not only pre-test probability but also the effect of the positive likelihood ratio test performance truly diagnostic. This aspect should be taken into account in the interpretation of results of clinical trials evaluating the performance of the PCT to guide antibiotic therapy.

modern clinical laboratories must confirm that the procedures used for certain tests that are reliable and valid. There are several sources of error and disturbance can undo the results. medical validation refers to check the plausibility of the results of the test. Results unreasonable indicate that something is wrong with the power of a sample taken from the patient, for example, a blood sample gets contaminated with other liquids, which require re-examination. Here, we describe how a business intelligence (BI) tools can be developed based on an integrated R that improve the efficiency of medical validation at the Institute of Clinical Chemistry (ICC) of the University Hospital Zurich. A BI software environment enables us to digitalize the steps in the manual validation process conducted in an Excel spreadsheet, for example, importing data, calculating percentiles, and produce graphical output.

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities – proof of concept in the laboratory conditions.

High-throughput sequencing (HTS) allows the generation of large amounts of genome sequence data at a reasonable cost. Organisms within the microbial community mix can now be sorted and identified by culture-independent manner, typically using amplicon sequencing of DNA barcodes. Bulk RNA-seq (metatranscriptomics) has several advantages compared to amplicon-based DNA sequencing: less susceptible to bias amplification, it captures only living organism, and it enables a larger set of genes to be used for taxonomic identification. Using a mock society model comprising 17 fungal isolates, we evaluated whether metatranscriptomics can accurately identify fungal species and subspecies in mixed communities.

Overall, 72.9% of the RNA transcripts are classified, of which the majority (99.5%) were correctly identified at the species level. Of the 15 species of sequencing, 13 were captured and identified properly. We also detected strain-level variation in complex Cryptococcus species: 99.3% of the transcripts assigned to Cryptococcus classified as one of the four strains used in the community pretending. laboratory contaminants and / or misclassifications diverse, but only represents 0.44% of the transcripts.

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Therefore, these results show that it is possible to obtain an accurate species- and strain-level fungal identification of the data metatranscriptome during taxa identified at low abundance discarded to avoid false-positives that come from contamination or misclassifications. This study highlights both the benefits and challenges in the implementation metatranscriptomics currently in clinical mycology and ecology studies.

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