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BackgroundOutcomes in well-resourced, intensive care units (ICUs) in Kenya are thought to be comparable to those in high-income countries (HICs) but risk-adjusted mortality data is unavailable. We undertook an evaluation of the Aga Khan University Hospital, Nairobi ICU to analyze patient clinical-demographic characteristics, compare the performance of Sequential Organ Failure Assessment (SOFA), delta-SOFA at 48 hours and Mortality Prediction Model-III (MPM-III) mortality prediction systems, and identify factors associated with increased risk of mortality.MethodsA retrospective cohort study was conducted of adult patients admitted to the ICU between January 2015 and September 2017. SOFA and MPM-III scores were determined at admission and SOFA repeated at 48 hours.ResultsApproximately 33% of patients did not meet ICU admission criteria. Mortality among the population of critically ill patients in the ICU was 31.7%, most of whom were male (61.4%) with a median age of 53.4 years. High adjusted odds of mortality were found among critically ill patients with leukemia (aOR 6.32, p0.05) while delta-SOFA was borderline (p = 0.05).ConclusionMortality among the critically ill was higher than expected in this well-resourced ICU. 48-hour SOFA performed better than admission SOFA, MPM-III and delta-SOFA in our cohort. While a large proportion of patients did not meet admission criteria but were boarded in the ICU, critically ill patients stepped-up from the step-down unit were unlikely to survive. Patients admitted following a cardiac arrest, and those with advanced disease such as leukemia, stage-4 HIV and metastatic cancer, had particularly poor outcomes. Policies for fair allocation of beds, protocol-driven admission criteria and appropriate case selection could contribute to lowering the risk of mortality among the critically ill to a level on par with HICs.

BACKGROUND:Relevant seroprevalence data for endemic pathogens in a given region provide insight not only into a population's susceptibility to acute infection or risk for reactivation disease but also into the potential need for policy initiatives aimed at reducing these risks. Data from sub-Saharan Africa are sparse and since Aga Khan University Hospital Nairobi is an internationally accredited hospital equipped with a laboratory electronic medical record system, analysis of pertinent local seroprevalence data has been made possible. METHODS:We have analyzed serology data from laboratory electronic records at a 300 bed tertiary private teaching hospital in Kenya for the dates, 2008 to 2017 for Toxoplasma gondii, cytomegalovirus, and rubella, which were used primarily for antenatal screening. We also analyzed the data from hepatitis A and amebiasis serologies, which were used primarily for diagnostic purposes. RESULTS:For T. gondii, cytomegalovirus, and rubella, we used IgG serology to determine seroprevalence, finding rates of 32%, 86%, and 89%, respectively. There was no significant age-related difference in the 20 to 49 year old age range for any of these three pathogens. Of the Hepatitis A IgM tests that were ordered, 33% were positive with a peak positive rate of 70% in the five to nine year old age range. The seroprevalence of amebiasis was 4% and all cases of seropositivity were accompanied by compatible clinical illness (hepatic abscess). CONCLUSIONS:These data provide insight into seroprevalence rates of selected pathogens that can be used to guide screening and diagnostic laboratory testing as well as private and public immunization practices.

BACKGROUND:Accurate local prevalence of microbial diseases and microbial resistance data are vital for optimal treatment of patients. However, there are few reports of these data from developing countries, especially from sub-Saharan Africa. The status of Aga Khan University Hospital Nairobi as an internationally accredited hospital and a laboratory with an electronic medical record system has made it possible to analyze local prevalence and antimicrobial susceptibility data and compare it with other published data. METHODS:We have analyzed the spectrum of microbial agents and resistance patterns seen at a 300 bed tertiary private teaching hospital in Kenya using microbial identity and susceptibility data captured in hospital and laboratory electronic records between 2010 and 2014. RESULTS:For blood isolates, we used culture collection within the first three days of hospitalization as a surrogate for community onset, and within that group, Escherichia coli was the most common, followed by Staphylococcus aureus. In contrast, Candida spp. and Klebsiella pneumoniae were the most common hospital onset causes of bloodstream infection. Antimicrobial resistance rates for the most commonly isolated Gram negative organisms was higher than many recent reports from Europe and North America. In contrast, Gram positive resistance rates were quite low, with 94% of S. aureus being susceptible to oxacillin and only rare isolates of vancomycin-resistant enterococci. CONCLUSIONS:The current report demonstrates high rates of antimicrobial resistance in Gram negative organisms, even in outpatients with urinary tract infections. On the other hand, rates of resistance in Gram positive organisms, notably S. aureus, are remarkably low. A better understanding of the reasons for these trends may contribute to ongoing efforts to combat antimicrobial resistance globally.