Simple Test May Take Guesswork Out Of Autism Diagnosis
In what could open the door to earlier autism diagnosis, researchers said Tuesday that they can reliably pinpoint who does and does not have the disorder using a readily-available test.
The finding comes from the largest and most intensive study to date looking at detecting autism using an electroencephalogram, or EEG.
For the study, researchers at Harvard Medical School and Children’s Hospital Boston conducted EEG tests — which measure brain activity — on nearly 1,000 children ages 2 to 12, including 430 with autism and 554 who were typically developing.
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When researchers examined the way various parts of the children’s brains connected, they found clear differences between the two groups, with those diagnosed with autism generally displaying less connectivity overall.
Ultimately scientists were able to pinpoint 33 factors that separated the children with autism from those without, according to the study published in the journal BMC Medicine.
Currently, autism is spotted through clinical evaluation and diagnosis is generally believed to be accurate as early as age 2. Researchers are hopeful that the study findings may lead to autism diagnosis and intervention at younger ages before behavioral symptoms are fully apparent.
While this is not the first study to look at the benefits of EEG in identifying autism, researchers said their closely defined group of participants makes their findings significant.
All of the kids with autism who were studied had classic autism, not high-functioning or Asperger’s syndrome, and were free of any known genetic disorder like fragile X syndrome. Additionally, researchers excluded children with other conditions like seizures and those taking medication in order to ensure the accuracy of the patterns they discovered.
“We studied the typical autistic child seeing a behavioral specialist — children who typically don’t cooperate well with EEGs and are very hard to study,” said Frank Duffy of Harvard and Children’s Hospital Boston who was one of the study authors. “These factors allowed us to make a discriminatory rule that was highly significant and highly replicable.”
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