predicting

The diagnosis of the neurodegenerative diseases You face a problem at the time the diagnosis is made, since in many cases it is diagnosed when the symptoms are already evident and this makes the brain damage irreversible. But… What if we could peer into the future of the brain years before the disease shows its face? This is precisely what a Spanish team has done with a new biomarker. The study. The future of medicine involves making increasingly earlier diagnoses so that the success of treatments is much greater, and now in a recent published article in Science Report The door opens for this to be a reality in dementia. To get here, what the researchers propose, where have you participated Rubén Armañanzas, from the DATAI Institute of the University of Navarra, is the use of a test such as the electroencephalogram together with artificial intelligence to develop a biomarker capable of predicting the risk of dementia with up to seven years in advance. Your methodology. To understand the magnitude of this advance, we must look at the population on which the study was carried out, which are people with subjective cognitive impairment. These are patients who go to the doctor because they notice that their memory is failing, but when they undergo standard cognitive tests, the results are completely normal, so they cannot be given a clear diagnosis even though it seems that something is not right. Until now, medicine found a blind spot in this phase as there was no way to know if these ‘complaints’ in memory were the prelude to Alzheimer’s or simply confusion. But now, the study with 88 older adults with this situation has shown that the brain emits alarm signals long before psychological tests detected them. You just had to know how to ‘read’ them. A new method. Here the research has unified different metrics to be able to read these warning signs. The first thing of all is to use an electroencephalogram to measure brain activity, which is a cheap, quick and non-invasive test. From here, the BrainScope technology platform analyzes this data by looking for 14 specific features related to neuronal connectivity and brain wave behavior. Once these characteristics are ‘found’, an AI algorithm comes in that processes the patterns and determines whether the patient analyzed can progress towards mild cognitive impairment or dementia such as Alzheimer’s. And the results are spectacular, since it has demonstrated outstanding precision when separating patients who develop the disease from those who do not. The future. The great value of this biomarker is not only technological, but also clinical, since the most reliable current tests to predict pathologies such as Alzheimer’s require painful lumbar punctures or scans that are not cheap. A system based on EEG and AI could be easily integrated into primary care clinical protocols or routine neurological consultations as it does not have a very high cost and, above all, is not invasive. The important thing here is to detect neurodegeneration in the earliest phases in order to gain golden time so that new drugs can act at the beginning of the disease and gain years of quality of life. Images | Robina Weermeijer In Xataka | We have a new “theory of everything” to understand Alzheimer’s. Its key is in some small granules