The mass spectrometry technology MALDI-TOF (Matrix-Assisted Laser Desorption/Ionization Time- Of-Flight) for a more rapid and economic workflow in the clinical microbiology laboratory

Introduction: In order to improve the outcome of patients, reduce length of stay, costs and resources engaged in diagnostics, more rapid reports are requested to the clinical microbiologists.The purpose of this study is to assess the impact on workflow of MALDI-TOF technology, recently made available for use in routine diagnostics. Methods:The work list by the management information system is sent to the instrument MALDI-TOF, where are held at least three successive analytic sessions: the first includes bacteria isolated from CSF, blood cultures, and cases already reported as serious/urgent, the second includes all other germs isolated, the third, microorganisms that require extraction with trifluoroacetic acid (TFA) or formic acid (FA) for identification.The results of each session direct to the execution of different types of susceptibility testing. Results:The times of microbial identifications are reduced by 24 or 48 hours and made available to the clinician for the rational empirical therapy.The reagent costs are reduced by 40%.The subcultures were reduced by 80%, and microscopic examinations by 50%.The antibiotic susceptibility tests were immediately performed with the most appropriate method, based on the knowledge of local epidemiology and microbial species. Conclusion:The bacteriology is the less automated discipline among the clinical laboratory activities and results of diagnostic tests are poorly well-timed. The new interpretative algorithms of MALDI-TOF spectra, now available, allow the correct identification of bacteria in near real time, completely eliminating the wait is necessary for biochemical identification and guiding the operator in selecting the most appropriate antibiotic susceptibility tests. This technology makes work more rapid, economic and efficient, eliminating errors and, together with effective computerization of data, transforms the information content of the microbiological report, making it much more effective for the therapy and the patient care.