The Development of a Novel Algorithm for Detection of Common Bacterial, Viral and Fungal Aetiologic Agents of Meningoencephalitis

Abstract

The incidence of meningitis and encephalitis in developing countries is underestimated due to inadequate diagnosis as it is mostly based on conventional techniques with a limited detection capacity for viral, bacterial and fungal aetiological agents. This results in prescription of a combination of anti-viral, antifungal or antibiotics, as the aetiologic agent is unidentified. Accurate diagnostic results are required for appropriate treatment options. Aim: This research was designed to make a contribution in improving quality of diagnostic and accuracy of meningoencephalitis in Rwanda. Objectives: 1.To develop a novel algorithm for the detection of the most common bacterial, viral and fungal etiological agents of meningoencephalitis using both culture and Real-time Multiplex PCR methods. 2.To determine the drug susceptibility pattern of the detected bacterial agents of meningoencephalitis. 3.To evaluate and demonstrate the utility of molecular diagnostic method compared with conventional diagnostic methods in detection of etiologic agents of central nervous system infections in Rwanda. Materials and Methods: Using cross sectional laboratory based study design, 845 hospitalized patients with meningitis and encephalitis from four referral and four satellite hospitals were enrolled into the study. From each patient four sterile tubes were used to collect Cerebral Spinal Fluid (CSF) specimens for analysis using conventional and RT-Multiplex PCR methods. Two tubes were analysed on site for routine diagnosis: One for bacteriology and fungal detection and the other for cytology and biochemistry. The remaining two tubes were sent to the National Reference Laboratory (NRL) for conventional and RT- Multiplex PCR.

Results: Objective 1: From the study, 152 viral, 49 fungal and 105 bacterial etiological agents of meningoencephalitis were detected. This represents 18%, 6% and 22% diagnostic capacities for viral, fungal and bacterial aetiologic agents respectively. Objective 2: Klebsiella pneumonia and Streptococcus agalactiae were 100% sensitive to augmentin and 100% sensitive to cefotaxime respectively. Staphylococcus aureus was 90% sensitive to penicillin, oxacillin and methicillin. Objective 3: Using conventional techniques, no viruses were detected. However, with Real- time Multiplex PCR a range of viruses, 152/845 (18%) were detected. In addition, different types of bacteria 185/845(22%) were detected using Real-time Multiplex PCR compared with the 59/845(7%), detected using conventional techniques. Conclusion: The results from this study showed rapid and accurate diagnosis of etiological agents of Central Nervous System (CNS) infection. There was an improvement on diagnostic capacity from 9% using conventional methods, to 40% using a combination of conventional and Real time -Multiplex PCR methods. The use of RT- Multiplex PCR in detection of etiological agents of CNS infections will contribute to accurate diagnosis and early, appropriate treatment of patients with meningoencephalitis. Recommendation: The Ministry of Health in Rwanda should consider developing a policy that includes the use of this algorithm by Healthcare Professionals and laboratory networks in order to improve quality of diagnosis for better treatment of patients with meningoencephalitis at all levels in the country.