Doctors Develop System That Can Predict Bipolar Disorder 4 Years Before Onset
The said study found, just 20 percent of individuals with the disorder and exhibiting with a ‘depressive incident’ are diagnosed with bipolar disorder within their first year of looking for treatment.
A team of international doctors has devised a machine learning system that can predict Bipolar Disorder development up to four years prior to onset in young individuals.
Specifically, at age 18, this new invention was able to predict which people were likely to develop the disorder at age 22.
This project was presented is published in a peer-reviewed Acta Psychiatrica Scandinavica journal and presented at the ECNP virtual congress.
According to Francisco Diego Rabelo-da-Ponte, the project's lead researcher, "This may be a new additional instrument" to diagnose bipolar disorder.
Rabelo-da emphasized the new system is not a replacement for the doctor's diagnosis. However, it may enable them to "take preventive measures" to delay or even avoid the condition's occurrence, and thus, "gain four years of preventive treatment."
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Machine Learning Techniques Used
The study authors from the United States, Brazil, and Canada said they followed more than 3,500 people born in Brazil in 1993, recording measurements and conducting interviews with the participants aged 11, 15, 18, and 22.
The study was investigating at the respondents' general health from birth, although it has had a specific application in mental condition.
When the 22-year follow up concluded, about 6.7 percent of the people were diagnosed with bipolar disorder.
Rabelo-da-Ponte, from the Brazil-based Federal University of Rio Grande, do Sul said what they found was that they could identify who was likely to develop a bipolar disorder for roughly four years prior to the condition's onset, by following those involved in the study from birth to adulthood.
While following the individuals, Rabelo-da-Ponte said they used "machine learning techniques" based on the similar approaches used for detecting such things as "spam and weather" prediction.
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Several Factors Referring to Greater Bipolar Disorder Risk
The study authors identified several factors which they said, "Tended to point to a greater risk for bipolar disorder."
For instance, the research specified, if 18-year-old individuals exhibit more suicidal tendencies, evidence of physical abuse, and financial problems," they then are likely to develop the disorder.
Specifically, it was the machine learning's job to weigh such factors and approximate the risk of having bipolar disorder.
According to reports, bipolar disorder is estimated to be the sixth in the world in terms of the cause of the bipolar disorder. Nonetheless, its proper identification still often signifies a challenge, with an average postponement of six years between experiencing the first symptoms and official diagnosis.
Furthermore, the said study found, just 20 percent of individuals with the disorder and exhibiting a "depressive incident" are diagnosed with bipolar disorder within their first year of looking for treatment.
Delays in diagnostic and treatment have dangerous consequences for clinical courses of illness, for instance, symptoms' greater severity and a shorter period, according to the study, "Between episodes of mood, cognitive and functional damage."
Detecting bipolar disorder early is found to be a growing interest as a lot of patients are reportedly mistreated, not to mention, misdiagnosed, avoiding the disease's progression.
The Challenge
Rabelo-da-Ponte also said, it is difficult and costly to supplicate such long-lasting research, although what they have found specifies that there is a need for more of these "longitudinal studies."
Additionally, the expert also said they had learned a lot from the project itself. For instance, the lead researcher elaborated, "If were to set it up now," they would engage many more parameters in terms of mental health, which they hope would enable them to determine "even more psychological benefits."
He shared, too, they have seen "too many false positives, indicating someone is at risk when they are not," to depend purely on this system alone.
Nonetheless, this system, he added, will enable doctors to detect who might be at risk, and the gain of four years prior to diagnosis could make a big difference to a young person's life.
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Sep 18, 2020 08:40 AM EDT
