scholarly journals Phenotypic and Genotypic Characterization of Metallo Beta Lactamases among Gram-Negative Uropathogens from a Tertiary Care Hospital in Egypt: A Cross Sectional Study

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Doaa Abo-Alella ◽  
Mahmoud Malek ◽  
Mai Malek
2021 ◽  
Vol 59 (241) ◽  
pp. 875-880
Author(s):  
Mahendra Shrestha ◽  
Ratna Baral ◽  
Lok Bahadur Shrestha

Introduction: Non-fermentative gram-negative bacilli are common causes of human infections especially nosocomial infections. These organisms are usually resistant to multiple antimicrobial agents including carbapenems. The study aimed to find out the prevalence of metallo-β-lactamase producing non-fermentative gram-negative bacilli among the samples which yielded growth of bacteria in a tertiary care hospital. Methods: This is a descriptive cross-sectional study conducted in a tertiary care hospital from February 2017 to May 2017. Convenience sampling method was used. Bacterial identification, characterization and antimicrobial susceptibility testing were done by following standard microbiological guidelines. Metallo-β-lactamase production was detected by using combined disk diffusion test and double-disc synergy test. Data were analyzed by using Statistical Package of Social Science software version 16. Point estimate at 95% confidence interval was calculated along with frequency and proportion for binary data. Results: Among 628 samples which yielded growth of bacteria, 118 (18.79%) at 95% Confidence Interval (15.74-21.84) were metallo-β-lactamase producing non-fermentative gram-negative bacilli. Among them, 54 (45.76%) were Pseudomonas aeruginosa and 64 (54.24%) were Acinetobacter baumannii. Conclusions: A high prevalence of metallo-β-lactamase production was observed among the nonfermentative gram-negative bacilli than the study done in similar settings. It is mandatory to perform routine monitoring of metallo-β-lactamase producing isolates in clinical laboratories in order to help the clinicians prescribe proper antibiotics.


Vacunas ◽  
2020 ◽  
Vol 21 (2) ◽  
pp. 95-104 ◽  
Author(s):  
Y.M. AlGoraini ◽  
N.N. AlDujayn ◽  
M.A. AlRasheed ◽  
Y.E. Bashawri ◽  
S.S. Alsubaie ◽  
...  

Author(s):  
Nandini Chatterjee ◽  
Supratick Chakraborty ◽  
Mainak Mukhopadhyay ◽  
Sinjon Ghosh ◽  
Bikramjit Barkandaj ◽  
...  

Author(s):  
Sujeet A. Divhare ◽  
Satyashil Ingale

Background: Potential importance of drug –drug interactions (DDIs) is increasing as polypharmacy becomes more prevalent. Because additional data on the incidence and pattern of potential DDIs among diabetic patients are lacking in India, and supplemental pharmacodynamic or clinical outcome information is needed to address importance of a drug- drug interaction. Aim and objectives: To identify and analyze the pattern of DDIs in patients being prescribed anti-diabetic drugs in a tertiary care hospital. Material and Methods: This prospective cross-sectional study was carried out for a period of three months in 200 Type 2 diabetes mellitus (Type 2 DM) patients who were taking at least one antidiabetic agent during the period of past six months, of any age and either sex admitted in medicine ward of a tertiary care teaching hospital. Only one prescription was included for each patient on his/her 3rd day of hospitalization in the ward. Results: A total of 1217 drugs were prescribed in 200 prescriptions, resulting in an average of 6.1 drugs per prescription. A total of 637 potential DDIs were noted. The majority were seen in middle aged and elderly people. No overall difference was detected in the patients on insulin or metformin therapy taking or not taking additional drugs with the potential to interact. Worse control was found in the group of patients on sulphonylurea therapy taking interacting drugs (P <0.05). This difference was most marked in the group of patients over 60 years of age, who also had the highest intake of potentially interacting drugs (57%; <35 years-37%). Conclusion: Antidiabetic drugs have numerous interactions. A good practice is to use a drug­–drug interaction checker if any questions arise, several are available online. Quality care starts with the clinician obtaining a complete medication list for each patient at the start of each visit. Keywords: diabetes mellitus, drug interactions, hypoglycemic agents, drug therapy, co-morbidity, polypharmacy


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