Looking at Clinical Symptoms, Exposure Factors Irrespective of Etiology in Encephalitis


Encephalitis is an acute clinical syndrome of the central nervous system (CNS), often associated with fatal outcome or permanent damage, including cognitive and behavioral impairment, affective disorders and epileptic seizures. Infection of the central nervous system is considered to be a major cause of encephalitis and more than 100 different pathogens have been recognized as causative agents. However, a large proportion of cases have unknown disease etiology.

Jemila S. Hamid, working in surveillance and epidemiology for the Ontario Agency for Health Protection and Promotion in Toronto, Canada, and colleagues, performed a hierarchical cluster analysis on a multicenter England encephalitis data set with the aim of identifying sub-groups in human encephalitis. The researchers used the simple matching similarity measure which is appropriate for binary data sets and performed variable selection using cluster heatmaps. They also used heatmaps to visually assess underlying patterns in the data, identify the main clinical and laboratory features and identify potential risk factors associated with encephalitis. Their research was published in BMC Infectious Diseases.

The researchers says their results identified fever, personality and behavioural change, headache and lethargy as the main characteristics of encephalitis. Diagnostic variables such as brain scan and measurements from cerebrospinal fluids are also identified as main indicators of encephalitis. Our analysis revealed six major clusters in the England encephalitis data set. However, marked within-cluster heterogeneity is observed in some of the big clusters indicating possible subgroups. Overall, the results show that patients are clustered according to symptom and diagnostic variables rather than causal agents. Exposure variables such as recent infection, sick person contact and animal contact have been identified as potential risk factors.

It is in general assumed and is a common practice to group encephalitis cases according to disease etiology, Hamid, et al. say; however, they add that their results indicate that patients are clustered with respect to mainly symptom and diagnostic variables rather than causal agents. These similarities and/or differences with respect to symptom and diagnostic measurements might be attributed to host factors. The idea that characteristics of the host may be more important than the pathogen is also consistent with the observation that for some causes, such as herpes simplex virus (HSV), encephalitis is a rare outcome of a common infection.

The researchers note, "One of the challenges of encephalitis is that agents are not found in most of the patients where up to 60 percent to 85 percent of patients are of unknown etiology. This is because most infections of the central nervous system (CNS) are secondary infections, consequently, exposure factors (such as previous infection, sick person contact, animal contact as well as

insect bite) are important to understand etiology and epidemiology of encephalitis. Our results show that cases of unknown etiology are distributed throughout the six clusters. Clinicians might understand disease etiology and provide better diagnostics of these patients by investigating other patients with known etiology in the same cluster. In conclusion, we would like to mention that identifying infectious agents is important to control infectious encephalitis and most studies in the literature have used this approach. However, as treatment is available for only some types of encephalitis and the cause is unknown in most cases, we adopted a novel approach to look at clinical symptoms and exposure factors irrespective of etiology. We believe this method could also be helpfully applied to other syndromes for which a cause is often not found, such as acute respiratory and gastrointestinal disease, and may have numerous other applications in epidemiology."

Reference: Hamid JS, Meaney C, Crowcroft NS, Granerod J and Beyene J.Cluster analysis for identifying sub-groups and selecting potential discriminatory variables in human encephalitis. BMC Infectious Diseases 2010, 10:364 doi:10.1186/1471-2334-10-364.

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