Patterns of Healthcare-associated Infections in Patients at Kenyatta National Hospital Main Intensive Care Unit

Abstract

Background: Healthcare-Associated Infections refer to those infections that occur 48 hours after admission to healthcare facilities. Such infections are related to the use of invasive devices and procedures. Intensive Care Unit patients are at an increased risk of acquiring HCAIs, possibly due to inherent patient disease factors such as underlying co-morbidities and extremes of age. HCAIs create a three-pronged challenge to global health systems; first, by increasing patient mortality and morbidity; next, by contributing to increased health care costs; and finally, by worsening antimicrobial resistance (AMR). Prevention of HCAIs through evidence-based interventions and surveillance is of paramount importance. Objectives: To determine the incidence, etiology, and risk factors associated with HCAIs in patients admitted to Kenyatta National Hospital Main ICU. Materials and Methods: Using a prospective cohort study model and a consecutive convenience sampling approach, all patients regardless of age admitted at the KNH Main ICU during the study period (February to April 2023) were enrolled and followed up for seven days. The patients were screened daily for any HCAI starting 48 hours after admission, as defined by the Centre for Disease Prevention and Control guidelines 2022. A structured data collection tool was used for data collection and stored in a Microsoft Excel 2016 database that was password protected. The data collected included age, gender, admitting diagnosis, surgical intervention, length of surgery, co-morbidities, patients’ vitals, presence of invasive devices, and medication history. Data Analysis: Patients' demographic and clinical data were cleaned and analyzed using the Stata Statistics software version 15. Continuous variables were presented in the form of mean, median, and interquartile ranges and tested for normality with the Shapiro-Wilk test. Categorical variables were submitted in the form of tables, and a comparison of distribution between these groups was tested using the Chi-square test. The time to occurrence of infection was presented using Kaplan- Meier Survival curve. Multivariate logistic regression analyses were used to predict the association between risk factors and HCAIs. Significance of the Study: The study revealed the incidence of HCAIs, and the microorganisms involved and highlighted the risk factors associated with these infections. This information will form the basis for assessing our infection prevention protocols and guiding improvements to our current therapy modalities