Summary General presentation Resistance of bacteria to antibiotics is a universal problem. With the increase in the rate of resistance, knowledge of susceptibility patterns is essential to guide antimicrobial therapy. In Lebanon, many studies investigated this subject. Objectives Determine the rate of multidrug and extremely drug-resistant bacteria as well as the patterns of resistance and the factors associated with this resistance. Materials and methods A cross-sectional study was performed using the cultures from the labs of two university hospitals in Lebanon. Bacteria were divided into four groups: sensitive, multidrug-, extremely- and pan-drug resistant. Patient information was obtained from the medical records. Using the SPSS software for Windows, version 20 (IBM, Armonk, USA), the frequency of the bacteria, their susceptibilities and the association of resistance with seven potential factors (age, gender, diabetes mellitus, cancer, chronic kidney disease, dialysis, previous hospitalization) were studied. Results The frequency of resistance was 53.7% (39.9% multidrug-resistant and 13.8% extremely drug-resistant). Escherichia coli strains were mostly susceptible to carbapenems and tigecycline; and nitrofurantoine and fosfomycin in urine. Pseudomonas and Acinetobacter species were mostly sensitive to colistin. Klebsiella species were mostly susceptible to amikacin and carbapenems. MRSA rates were 34.8%. Association was seen between the resistant bacteria and older age, chronic kidney disease, dialysis, and previous hospitalization. Conclusion Resistance of bacteria to drugs in Lebanon is increasing. Significant association is seen between these bacteria and older age, chronic kidney disease, dialysis, and previous hospitalization.
Introduction: Lebanon has the highest Syrian refugee density worldwide. The influx of Syrian refugees has had various impacts on Lebanon, with one of the most significant effects observed in the already exhausted healthcare system. This study aimed to determine the reasons for hospitalization among registered Syrian refugees in Beirut who were admitted to Rafik Hariri University Hospital (RHUH) between December 2017 and June 2020.Methods: Data from 7,480 diagnosed cases were collected from the RHUH archives between December 2017 and June 2020 and were analyzed using SPSS (IBM Corp., Armonk, NY, USA). The collected data included information related to demographics, admission date, primary diagnosis, and other related medical problems. Variations and correlations were then tested.Results: Of the cases, 73.4% were females; the mean age was 28 ± 16.23 years. Fifty-seven percent of the admitted cases were solely due to pregnancy, childbirth, and puerperium reasons, and 91.14% of the deliveries were single deliveries by cesarean section. Common reasons for hospitalization were injuries (5.8%) and diseases of the digestive system (6.8%), circulatory system (4.7%), and respiratory system (4.4%). Non-communicable diseases (NCDs) constituted 61% of all hospital admissions, while only 6.6% belonged to communicable diseases. Reasons for hospitalization and the type of diagnosed diseases were associated with gender and age groups (p-values <0.001). Conclusion:The major reasons for hospitalization among Syrian refugees were related to pregnancies and NCDs. The burden of the Syrian refugee influx on the Lebanese healthcare system can be alleviated by improving community health education, public health services, and conditions for refugees.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.