The Beijing family of Mycobacterium tuberculosis (MTB) has been reported to have an exceptional capacity to spread tuberculosis (TB) and induce multi-drug resistance. A method has been developed to distinguish this family from the rest of the MTB families through real-time DNA amplification and subsequent analysis of the melting point of an amplicon. Two pools of multi-drug resistant (MDR) MTB samples collected at two different time periods from various regions in Syria have been selected. This preliminary screening indicated a complete absence of the Beijing family in all samples. This research presents an effective differentiation of bacterial Beijing strains, with minimal effort and cost through analysis of differential amplicon melting points.
Background: Antimicrobial Resistance (AMR) presents a pressing public health challenge globally which has been compounded by the COVID-19 pandemic. Elucidation of the impact of the pandemic on AMR evolution using population-level data that integrates clinical, laboratory and prescription data remains lacking.
Methods: Data was extracted from the centralized electronic platform which captures the health records of 60,551 patients across the network of public healthcare facilities in Dubai, United Arab Emirates. For all inpatients and outpatients diagnosed with bacterial infection between 01/01/2017 and 31/05/2022, structured and unstructured Electronic Health Record data, microbiological laboratory data including antibiogram, molecular typing and COVID-19 testing information as well as antibiotic prescribing data were extracted curated and linked. Various analytical methods, including time-series analysis, natural language processing (NLP) and unsupervised clustering algorithms, were employed to investigate the trends of antimicrobial usage and resistance over time, assess the impact of prescription practices on resistance rates, and explore the effects of COVID-19 on antimicrobial usage and resistance.
Results: Our findings identified a significant impact of COVID-19 on antimicrobial prescription practices, with short-term and long-lasting over-prescription of these drugs. Resistance to antimicrobials increased the odds ratio of mortality to an average of 2.5 and the effects of prescription practices on resistance were observed within one week of initiation. Significant trends in antimicrobial resistance, exhibiting fluctuations for various drugs and organisms, with an overall increasing trend in resistance levels, particularly post-COVI D-19 were identified.
Conclusion: This study provides a population-level insight into the evolution of AMR in the context of COVID-19 pandemic. The findings emphasize the long-term effect of COVID-19 on the AMR crisis and the critical need for improved antimicrobial stewardship to tackle AMR evolution.
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