High burden of ESBL and carbapenemase-producing gram-negative bacteria in bloodstream infection patients at a tertiary care hospital in Addis Ababa, Ethiopia.

BACKGROUND: Bloodstream infection due to beta-lactamase and carbapenemase-producing gram-negative bacteria poses a substantial challenge to the effectiveness of antimicrobial treatments. Therefore, this study aimed to investigate the magnitude of beta-lactamase, carbapenemase-producing gram-negative bacteria, and associated risk factors of bloodstream infections in patients at a tertiary care hospital, in Addis Ababa, Ethiopia. METHODS: An institutional-based cross-sectional study was conducted with convenience sampling techniques from September 2018 to March 2019. Blood cultures were analyzed from 1486 bloodstream infection suspected patients across all age groups. The blood sample was collected using two BacT/ALERT blood culture bottles for each patient. Gram stain, colony characteristics, and conventional biochemical tests were used to classify the gram-negative bacteria at the species level. Antimicrobial susceptibility testing was carried out to screen beta-lactam and carbapenem drug-resistant bacteria. The E-test was conducted for extended-spectrum-beta-lactamase and AmpC-beta-lactamase-producers. A modified and EDTA-modified carbapenem inactivation method was conducted for carbapenemase and metallo-beta-lactamases producers. Data collected using structured questionnaires and medical records were reviewed, encoded, and cleaned using EpiData V3.1. software. The cleaned data were exported and analyzed using SPSS version 24 software. Descriptive statistics and multivariate logistic registration models were used to describe and assess factors associated with acquiring drug-resistant bacteria infection. A p-value <0.05 was considered statistically significant. RESULT: Among 1486 samples, 231 gram-negative bacteria were identified; of these, 195(84.4%) produce drug-hydrolyzing enzymes, and 31(13.4%) produce more than one drug-hydrolyzing enzyme. We found 54.0% and 25.7% of the gram-negative bacteria to be extended-spectrum-beta-lactamase and carbapenemase-producing, respectively. The extended-spectrum-beta-lactamase plus AmpC-beta-lactamase-producing bacteria account for 6.9%. Among the different isolates Klebsiella pneumonia 83(36.7%) was the highest drug-hydrolyzing enzyme-producing bacteria. Acinetobacter spp 25(53.2%) was the most carbapenemase producer. Extended-spectrum-beta-lactamase and carbapenemase-producing bacteria were high in this study. A significant association between age groups and extended-spectrum-beta-lactamase producer bacterial infection was seen, with a high prevalence in neonates (p = <0.001). Carbapenemase showed a significant association with patients admitted to the intensive care unit (p = 0.008), general surgery (p = 0.001), and surgical intensive care unit (p = 0.007) departments. Delivery of neonates by caesarean section, and insertion of medical instruments into the body were exposing factors for carbapenem-resistant bacterial infection. Chronic illnesses were associated with an extended-spectrum-beta-lactamase-producing bacterial infection. Klebsiella pneumonia and Acinetobacter species showed the greatest rates of extensively drug-resistant (37.3%) and pan-drug-resistance (76.5%), respectively. According to the results of this study, the pan-drug-resistance prevalence was found to be alarming. CONCLUSION: Gram-negative bacteria were the main pathogens responsible for drug-resistant bloodstream infections. A high percentage of extended-spectrum-beta-lactamase and carbapenemase-producer bacteria were found in this study. Neonates were more susceptible to extended-spectrum-beta-lactamase and AmpC-beta-lactamase-producer bacteria. Patients in general surgery, caesarean section delivery, and intensive care unit were more susceptible to carbapenemase-producer bacteria. The suction machines, intravenous lines, and drainage tubes play an important role in the transmission of carbapenemase and metallo-beta-lactamase-producing bacteria. The hospital management and other stakeholders should work on infection prevention protocol implementation. Moreover, special attention should be given to all types of Klebsiella pneumoniae and pan-drug resistance Acinetobacter spp transmission dynamics, drug resistance genes, and virulence factors.

Antimicrobial Resistance and Associated Risk Factors of Gram-Negative Bacterial Bloodstream Infections in Tikur Anbessa Specialized Hospital, Addis Ababa.

Background: Bloodstream infections (BSIs) are significant causes of morbidity and mortality in Ethiopia and worldwide. Alarming is the rapid global spread of antimicrobial resistance (AMR) in bacteria. Objective: To determine the microbial profile, antimicrobial susceptibility pattern, and associated risk factors for bloodstream infections in Tikur Anbessa Specialized Hospital (TASH) Addis Ababa Ethiopia. Methods: A cross-sectional study was conducted between September 2018 and March 2019. Blood collected twice from each septicemia suspected patient were processed following standard bacteriological procedures. AST was performed by using the disk diffusion test according to CLSI 2017 and 2018 guidelines. Data captured in Epidata were cleaned and analyzed by SPSS version 21 software. Results: The prevalence of BSI was 28.06% and a higher proportion of pathogene detected were gram-negative bacteria (GNB) (54.5%) and gram-positive bacteria (GPB) (45.43%). The most abundant bacterial species were Klebsiella pneumoniae 17.6%, CoNS 15.2%, and Acinetobacter spp 11.0%. Culture positivity was associated with age below 6 years, neonates AOR p=<0.001, infants AOR p=<0.001, Pre-school P=0.002, ICU admission COR p=<0.001, length of admission >5 days COR P=0.016, temperature greater than 38°C, AOR p=0.013, instrument usage during medical care AOR, p=<0.001, chronic illness AOR p=0.027, and neonatal incubation AOR p=0.013. GNB average drug resistance rate was 57.9% of the commonly used antibiotics and the most efficient and inefficient drugs were amikacin (10.8%) and ampicillin (94.6%). The gram-negative isolates showed a 95.3% rate of multi-drug resistance; and MDR, XDR, and PDR were observed at 55.8%, 32.2%, and 7.3%, of isolates respectively. This finding shows children especially neonates were highly affected by drug resistant BSI. Conclusion: Pediatric patients and ICU patients are more affected by BSI, and drug-resistant bacteria are a major problem. Therefore, appropriate intervention approaches need to be implemented.

Prediction of coreceptor usage by five bioinformatics tools in a large Ethiopian HIV-1 subtype C cohort.

BACKGROUND: Genotypic tropism testing (GTT) has been developed largely on HIV-1 subtype B. Although a few reports have analysed the utility of GTT in other subtypes, more studies using HIV-1 subtype C (HIV-1C) are needed, considering the huge contribution of HIV-1C to the global epidemic. METHODS: Plasma was obtained from 420 treatment-naïve HIV-1C infected Ethiopians recruited 2009-2011. The V3 region was sequenced and the coreceptor usage was predicted by five tools: Geno2Pheno clinical-and clonal-models, PhenoSeq-C, C-PSSM and Raymond's algorithm. The impact of baseline tropism on antiretroviral treatment (ART) outcome was evaluated. RESULTS: Of 352 patients with successful baseline V3 sequences, the proportion of predicted R5 virus varied between the methods by 12.5% (78.1%-90.6%). However, only 58.2% of the predictions were concordant and only 1.7% were predicted to be X4-tropic across the five methods. Compared pairwise, the highest concordance was between C-PSSM and Geno2Pheno clonal (86.4%). In bivariate intention to treat (ITT) analysis, R5 infected patients achieved treatment success more frequently than X4 infected at month six as predicted by Geno2Pheno clinical (77.8% vs 58.7%, P = 0.004) and at month 12 by C-PSSM (61.9% vs 46.6%, P = 0.038). However, in the multivariable analysis adjusted for age, gender, baseline CD4 and viral load, only tropism as predicted by C-PSSM showed an impact on month 12 (P = 0.04, OR 2.47, 95% CI 1.06-5.79). CONCLUSION: Each of the bioinformatics models predicted R5 tropism with comparable frequency but there was a large discordance between the methods. Baseline tropism had an impact on outcome of first line ART at month 12 in multivariable ITT analysis but only based on prediction by C-PSSM which thus possibly could be used for predicting outcome of ART in HIV-1C infected Ethiopians.

Monophylogenetic HIV-1C epidemic in Ethiopia is dominated by CCR5-tropic viruses-an analysis of a prospective country-wide cohort.

BACKGROUND: CCR5 coreceptor using HIV-1 subtype C (HIV-1C) has been reported to dominate the Ethiopian epidemic. However, almost all data have been obtained from two large cities in the central and north-west regions and recent data is lacking. METHODS: Plasma were obtained from 420 treatment-naïve patients recruited 2009-2011 to a large country-wide Ethiopian cohort. The V3 region was sequenced and the co-receptor tropism was predicted by the clinical and clonal models of the geno2pheno tool at different false positive rates (fpr) and for subtype. In an intention to treat analysis the impact of baseline tropism on outcome of antiretroviral therapy was evaluated. RESULTS: V3 loop sequencing was successful in 352 (84%) patients. HIV-1C was found in 350 (99.4%) and HIV-1A in two (0.6%) patients. When comparing the geno2pheno fpr10% clonal and clinical models, 24.4% predictions were discordant. X4-virus was predicted in 17.0 and 19.0%, respectively, but the predictions were concordant in only 6%. At fpr5%, concordant X4-virus predictions were obtained in 3.1%. The proportion of X4-tropic virus (clonal fpr10%) increased from 5.6 to 17.3% (p < 0.001) when 387 Ethiopian V3 loop sequences dated from 1984 to 2003 were compared with ours. In an intention to treat analysis, 67.9% reached treatment success at month 6 and only 50% at month 12. Only age and not tropism predicted therapy outcome and no difference was found in CD4+ cell gain between R5-tropic and X4-tropic infected patients. At viral failure, R5 to X4 switch was rare while X4 to R5 switch occurred more frequently (month 6: p = 0.006; month 12: p = 0.078). CONCLUSION: The HIV-1C epidemic is monophylogenetic in all regions of Ethiopia and R5-tropic virus dominates, even in patients with advanced immunodeficiency, although the proportion of X4-tropic virus seems to have increased over the last two decades. Geno2pheno clinical and clonal prediction models show a large discrepancy at fpr10%, but not at fpr5%. Hence further studies are needed to assess the utility of genotypic tropism testing in HIV-1C. In ITT analysis only age and not tropism influenced the outcome.