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@article{1317093,
author = {Chudobova, Dagmar and Cihalova, Kristyna and Guran, Roman and Dostalova, Simona and Smerkova, Kristyna and Veselý, Radek and Gumulec, Jaromír and Masařík, Michal and Heger, Zbynek and Adam, Vojtech and Kizek, Rene},
article_location = {Rio de Janeiro},
article_number = {6},
doi = {http://dx.doi.org/10.1016/j.bjid.2015.08.013},
keywords = {Bacterial strains; MALDI-TOF; Sequencing; Superficial wounds},
language = {eng},
issn = {1413-8670},
journal = {Brazilian Journal of Infectious Diseases},
title = {Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration},
url = {http://dx.doi.org/10.1016/j.bjid.2015.08.013},
volume = {19},
year = {2015}
}
TY - JOUR
ID - 1317093
AU - Chudobova, Dagmar - Cihalova, Kristyna - Guran, Roman - Dostalova, Simona - Smerkova, Kristyna - Veselý, Radek - Gumulec, Jaromír - Masařík, Michal - Heger, Zbynek - Adam, Vojtech - Kizek, Rene
PY - 2015
TI - Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration
JF - Brazilian Journal of Infectious Diseases
VL - 19
IS - 6
SP - 604-613
EP - 604-613
PB - Elsevier Brazil
SN - 14138670
KW - Bacterial strains
KW - MALDI-TOF
KW - Sequencing
KW - Superficial wounds
UR - http://dx.doi.org/10.1016/j.bjid.2015.08.013
N2 - Background Infections, mostly those associated with colonization of wound by different pathogenic microorganisms, are one of the most serious health complications during a medical treatment. Therefore, this study is focused on the isolation, characterization, and identification of microorganisms prevalent in superficial wounds of patients (n = 50) presenting with bacterial infection. Methods After successful cultivation, bacteria were processed and analyzed. Initially the identification of the strains was performed through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on comparison of protein profiles (2–30 kDa) with database. Subsequently, bacterial strains from infected wounds were identified by both matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and sequencing of 16S rRNA gene 108. Results The most prevalent species was Staphylococcus aureus (70%), and out of those 11% turned out to be methicillin-resistant (mecA positive). Identified strains were compared with patients’ diagnoses using the method of artificial neuronal network to assess the association between severity of infection and wound microbiome species composition. Artificial neuronal network was subsequently used to predict patients’ prognosis (n = 9) with 85% success. Conclusions In all of 50 patients tested bacterial infections were identified. Based on the proposed artificial neuronal network we were able to predict the severity of the infection and length of the treatment.
ER -
CHUDOBOVA, Dagmar, Kristyna CIHALOVA, Roman GURAN, Simona DOSTALOVA, Kristyna SMERKOVA, Radek VESELÝ, Jaromír GUMULEC, Michal MASAŘÍK, Zbynek HEGER, Vojtech ADAM and Rene KIZEK. Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration. \textit{Brazilian Journal of Infectious Diseases}. Rio de Janeiro: Elsevier Brazil, 2015, vol.~19, No~6, p.~604-613. ISSN~1413-8670. Available from: https://dx.doi.org/10.1016/j.bjid.2015.08.013.
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