IntroductionInfection due to multidrug-resistant microorganisms is a growing threat in healthcare settings. Acinetobacter species specifically A. baumannii is increasingly becoming resistant to most antimicrobial agents recommended for treatment. This study aimed to determine the antimicrobial susceptibility pattern of Acinetobacter species isolated from patients in Kenyatta National Hospital.MethodsWe conducted a retrospective study based on VITEK 2 (BioMérieux) electronic records capturing identification and antimicrobial susceptibility of Acinetobacter isolates from patient samples analyzed between 2013 and 2015 at Kenyatta National Hospital microbiology laboratory. Generated data were analyzed using WHONET and SPSS.ResultsA total of 590 Acinetobacter isolates were analyzed. 85% of the isolates tested were multi-drug resistant (MDR). Among the 590 isolates, 273 (46%) were from tracheal aspirates and 285 (48%) from the critical care unit. A. baumannii was the most frequently isolated species with high susceptibility to amikacin (77%) and poor susceptibility to ciprofloxacin (69-76%), tobramycin (37%) and meropenem (27%). Both A. lwoffii and A. haemolyticus had high susceptibility to amikacin (80-100%) and meropenem (75-100%).ConclusionA. baumannii is resistant to commonly administered antibiotics. There is need for continuous antimicrobial resistance surveillance especially in health care facilities and strengthening of antibiotic stewardship programmes which will contribute to enhancement of infection control policies.

Introduction diabetic foot ulcer is the leading cause of hospital admissions, lower limb amputation and death among diabetic patients. Little information is available on fungal isolation in diabetic foot ulcer patients, especially in sub-Saharan Africa. This study aimed to describe Candida species infecting diabetic foot ulcers in patients receiving clinical care at Kenyatta National Hospital and assess their antifungal susceptibility profile. Methods this was a cross-sectional study carried out at Kenyatta National Hospital among adult diabetic foot ulcer patients over a three-month period. Species identification of Candida was performed using VITEK - 2 System and further confirmed by Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry. Antifungal susceptibility testing was determined using VITEK-2 System. Data were analysed using WHONET and SPSS. Results among the 152 study patients recruited, 98% (n=149) had type 2 diabetes. Sixty one percent of the participants were male. The mean age of the study participants was 50.7 years (SD 12.9). A total of 36 Candida species were isolated, of which 75% (n=27) were Candida albicans. Candida lusitaniae (8%, n=3) and C. dubliniensis (5%, n=2) were the predominant non-albicans Candida species. The overall prevalence of diabetic foot ulcer candidiasis was 20% (n=31). C. albicans isolates (26%) were resistant to caspofungin, fluconazole, micafungin, and voriconazole but highly susceptible to amphotericin B and flucytosine (81-96%). Non-albicans Candida species isolated were susceptible (90-100%) to a majority of the antifungal agents tested. Conclusion Candida albicans was the predominant species isolated and showed low resistance rates to the commonly administered antifungal agents. There is need to include fungal diagnosis in the investigation of diabetic foot ulcer infection.

We report the draft genome sequences and annotation of three beta-lactamase-producing Escherichia coli (E.coli) strains isolated from fecal samples of healthy camels in Laikipia county, Kenya. This data adds to the online genome resources to support the ongoing antimicrobial resistance surveillance in the livestock-wildlife interface.

Diarrhea is among the leading causes of morbidity and mortality in children aged < 5 years globally. In underdeveloped countries, diarrheagenic Escherichia coli (DEC) accounts for 30% -40% of childhood diarrhea cases. To identify the pathotypes involved in diarrheal outbreaks in Kenya, we analyzed archived E. coli isolates from children < 5 years old presenting with diarrhoea at three outpatient facilities in an informal settlement between January 2017 and September 2018. E. coli confirmation and antimicrobial susceptibility testing were done using the VITEK ® 2 instrument. Pathotype identification was performed via conventional polymerase chain reaction. Of 175 E. coli isolates, 48 (27%) were DEC pathotypes, with enteroaggregative E. coli (EAEC) predominating (71%, 34/48). Enterohemorrhagic (EHEC) and enteropathogenic E. coli (EPEC) represented 19% and 10% of isolates, respectively. Enteroinvasive and enterotoxigenic pathotypes were not identified. All DEC isolates were susceptible to amikacin, ertapenem, imipenem, meropenem and tigecycline. Conversely, most (>80%) isolates were resistant to ampicillin, ampicillin-sulbactam and sulfamethoxazole-trimethoprim. Half of all EAEC and EPEC strains were resistant to cefazolin while half of EHEC isolates were resistant to ciprofloxacin and moxifloxacin. In total, 18 resistance phenotypes were identified with "ampicillin-cefazolin-ampicillin/ sulbactam-sulfamethoxazole/trimethoprim" predominating (33%, 16/48). The majority (81%) of DEC isolates were multidrug-resistant, with extendedspectrum beta-lactamase production identified in 8% of these isolates. This

Existing breakpoint guidelines are not optimal for interpreting antimicrobial resistance data from animal studies and low-income countries, and therefore their utility for analysing such data is limited. There is need to integrate diverse data sets, such as those from low-income populations and animals, to improve data interpretation. There is very limited research on the relative merits of clinical breakpoints, epidemiological cut-offs, and normalised resistance interpretation breakpoints in interpreting microbiological data, particularly in animal studies and studies from low-income countries. The aim of this study was to compare antimicrobial resistance in E. coli isolates using ECOFFS, CLSI, and NRI breakpoints. A total of 69 non-repetitive poultry isolates were selected for investigation based on lactose fermentation on MacConkey agar and subsequent identification and confirmation as E. coli using chromogenic agar and uidA Polymerase Chain Reaction. Kirby Bauer disc diffusion technique was used for susceptibility testing. For each antimicrobial agent, inhibition zone diameters were measured, and ECOFFs, CLSI, and NRI bespoke breakpoints used for resistance interpretation. According to the interpretation of all breakpoints except ECOFFs, tetracycline resistance was significantly higher (TET) (67.8% – 69.5%), than ciprofloxacin (CIPRO) (18.6%– 32.2%), imipenem (IMI) (3.4% – 35%), and ceftazidime (CEF) (1.7% – 45.8%). Prevalence estimates of antimicrobial resistance (AMR) using CLSI and NRI bespoke breakpoints did not differ for CEF (1.7% CB and 1.7% COWT), IMI (3.4% CB and 4.0% COWT) and TET (67.8% CB and 69.5% COWT). However, with ECOFFs, antimicrobial resistance estimates for CEF, IMI, and CIP were significantly higher (45.8%, 35.6%, and 64.4%, respectively; P < 0.01). Across all the three breakpoints, resistance to ciprofloxacin varied significantly (32.2% CB, 64.4% ECOFFs, and 18.6% COWT). Antimicrobial resistance interpretation is influenced by the breakpoint used, necesscitating further standardisation, especially for microbiological breakpoints, in order to harmonise outputs. The AMR ECOFFs estimates in the present study were significantly higher compared to CLSI and NRI.