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Using data routinely collected by HPA surveillance systems and clinicians, public health experts at the HPA have produced a simple model which can be used to assess whether or not a suspected case of meningitis is bacterial or viral in origin.
Swift diagnosis of bacterial meningitis is crucial to protecting public health as it means potentially lifesaving interventions can be put in place - such as prescribing antibiotics to the patient and people they have been in contact with.
Currently, diagnosis of bacterial or viral meningitis depends upon analysis of spinal fluid obtained via a lumbar puncture procedure. While this process, referred to as a CSF examination is the gold-standard for confirming the cause of meningitis, it is a difficult test to carry out and results in some patients may be difficult to interpret.
Dr Toyin Ejidokun, a HPA Consultant in Communicable Disease who led the study team, said the work had produced a predictive model with a simple set of criteria that could be used alongside the current tests.
She said: "Meningitis is a potentially life threatening disease in children and young people and some survivors go on to develop lifelong complications. Therefore prompt diagnosis, and early intervention, is crucial in protecting those with suspected meningitis and their close contacts.
"At present, doctors sometimes have to carry out a lumbar puncture to take a sample of spinal fluid which is then tested for bacteria or viruses but this test is not straight-forward and can be very uncomfortable for the patient. In some cases clinicians need to take swift action before the CSF results are available."
After examining the clinical symptoms, biochemistry and microbiology of 385 confirmed cases of meningitis over a 12 month period, the team identified three factors based on routine clinical assessment and early available laboratory test results that help differentiate between bacterial and viral meningitis.
The presence or not of these factors were then 'scored' and a total obtained.
Dr Ejidokun said: "The total score allows a treating clinician to simply and quickly assess the likelihood of whether or not the case is bacterial meningitis by checking it against the predictive probabilities we have developed following our study of 385 confirmed cases.
"While further testing needs to take place to test the accuracy of the model, this simple model offers the prospect of a rapid predictive tool to help clinical and public health management of suspected bacterial meningitis cases."
