The aim of the study was to evaluate the drug-resistance patterns of infections in Baqiyatallah hospital within 2010-2019 and to present a novel monitoring and detection system making use of molecular laboratory methods teamed with molecular delimitation analyses. This in turn is a primary step to establishment of a digital health system within Baqiyatallah hospital as a perfect pilot instance for other hospitals to follow upon. Totally, 100 patients of Baqiyatallah hospital suspicious of infections were sampled. Bacterial identity confirmations were done using routine biochemical test. Antibiograms were made for all the patients in this study. Consequently, bacterial total DNA was extracted and 16S rDNA gene amplified and sequenced for all patients. To uncover any cryptic strain grouping within the samples, a molecular delimitation method, i.e. automated barcode gap discovery (ABGD), was done. Our results showed Ceftaroline to be the most and Erythromycin and Oxacillin the least effective drugs. Delimitation uncovered 19 groups out of which group 19 seemed to have location-specific genetic signals in regards to susceptibility of Erythromycin and Oxacillin. Our results indicate the importance of genetic identification of bacteria with respect to their genetic patterns before antibiotic administration in order to both reduce unnecessary medicine use and to biomonitor the bacterial patterns in respect to their behavior towards general antibiotics.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7758007PMC
http://dx.doi.org/10.22037/ijpr.2020.112966.14042DOI Listing

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