Decision support tool may help diagnose Alzheimers
PredictAD, a project led by Jyrki Lötjönen, DSc, of the VTT Technical Research Centre of Finland, has created a decision support tool that compares measurements of a patient to measurements of other persons available in large databases and provides a simple index about the severity of the disease. The project has shown that the tool improves the accuracy of diagnosis and clinicians' confidence about their decision.
The current guidelines for the diagnosis of Alzheimer's disease emphasize the role of various biomarkers. These biomarkers include measures from MRI, PET, biomarkers from cerebrospinal fluid and genetic biomarkers in addition to evidenced memory impairment. No single patient measure provides enough information for diagnosis. Clinicians must make the final diagnosis by combining a collection of measurements with information from interviews of the patient and relatives, a process involving subjective reasoning and requiring strong expertise from the clinicians.
PredictAD’s approach takes these patient measures and compares them with measurements in pre-existing databases at hospitals. Systematic mathematical modeling then provides an index and graphical representation reflecting the state of the patient, creating an objective barometer of the disease.
Alzheimer's disease, the most common cause of dementia, alone accounts for costs equivalent to about 1 percent of the gross domestic product (GDP) of the entire world and the number of persons affected will double in the next 20 years, according to VTT Technical Research Centre of Finland. Delaying the onset of the disease by five years would cut the costs associated with Alzheimer’s disease in half.