Increased incidence of multidrug resistant (MDR) Gram negative infection has resulted in high rates of morbidity and mortality. Klebsiella pneumoniae is one of the commonest MDR pathogens causing bacteraemia with limited therapeutic options such as colistin and tigecycline. Present study focused on molecular characterisation of MDR K. pneumoniae from bloodstream infection and their clinical outcome. A total of 115 K. pneumoniae from January 2015 to September 2016 were included in the study which comprised of phenotypically identified ESBL and carbapenem resistant (CR) isolates. Multiplex PCR was performed for detection of resistance genes encoding β-lactam resistance. This includes bla, bla, bla, bla, bla, bla, bla, bla, bla, bla, bla, bla, bla and bla. Co-expression of bla, bla and bla was predominant with 64% (74/115) prevalence. CTX-M-1 was the variant produced by all the isolates producing CTX-M. AmpC was uncommon, seen in 5% of the isolates (6/115). Among the carbapenemases co-expression of bla and bla was observed in 28% (32/115) and bla in 19% (22/115) and bla in 13% (15/115). bla was absent. Overall mortality was observed to be 57% (64/113) and mortality among CR K. pneumoniae (Kp) was 68% (50/73). The antibiotics that were administered for treatment of CRKp were colistin in 90% (66/73) and tigecycline in 7% (5/73) and in 99% combined with meropenem (72/73). Prevalence of community acquired and nosocomial infections were 5% (4/73) and 95% (69/73) respectively among CRKp. Minocycline and meropenem susceptibilities were comparable and hence minocycline can be a carbapenem sparing agent. The resistance to β-lactam antibiotics is steadily increasing and are plasmid mediated, their containment in healthcare setting is a challenge.
Students in the age group of 18–25 years witnessed their first pandemic in the form of the coronavirus (COVID-19). This had negative effects on their mental health, ranging from mild to severe. These effects also affected their personal and professional lives. The purpose of this study is to measure the anxiety and depression levels in college students due to COVID-19, along with the significant factors that contribute to that effect. We use the benchmark Hospital Anxiety and Depression Scale [HADS] questionnaire, as the basis of an online survey to capture the anxiety and depression levels amongst college students in various disciplines and at different levels. This survey was circulated through social media networks such as Facebook, WhatsApp, and so on. The responses were collected and analysed using Linear Regression and Random Forest algorithms for understanding the significant factors leading to the anxiety and depression of college students between ages 20 and 24.
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