Rethinking Seizure Care Blog

Automating Detection of SUDEP Risk Factors

Posted by RSC Diagnostics on Jun 25, 2019

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Many people around the world suffer from epilepsy and even though there have been efforts made to help those who have the condition, much is still unknown. Currently, there is no cure for epilepsy, but there are treatments that can help to better control the seizures. However, these treatments are not effective for everyone. In some cases, Sudden Unexpected Death in Epilepsy (SUDEP) occurs. Little is truly known about SUDEP, which often means there is a gap in counseling provided by doctors to their patients with epilepsy.

A Potential Solution

Fortunately, there may be a potential solution available due to automatic detection of risk factors from electronic medical records. If there is automated risk detection, it is possible to allow the automation to prompt the medical professionals to provide their patients with counseling. A recent study looked into how feasible this would be. Also, it looked at the “generalizability of using regular expressions to identify risk factors in EMRs and barriers to generalizability.”

How Was the Research Conducted?

The data that was used in the research included physician notes for 3,000 patients from a single medical center they termed the home center, as well as 1,000 from five additional medical centers they called away centers. During the review of the patient charts, the researchers were able to identify three SUDEP risk factors – generalized tonic-clonic seizures, refractory epilepsy and epilepsy surgery candidacy.

They manually created regular expressions of risk factors with home training data. The performance was evaluated with both home test and away test data. The researchers evaluated performance by “sensitivity, positive predictive value and F-measure.” They defined generalizability “as an absolute decrease in performance by <0.10 for away versus home test data.” In order to evaluate the underlying barriers to generalizability, they looked at causes of errors that were seen more often in away data than in the home data.

The researchers wanted to show how it would be possible for small revisions to improve generalizability. They did this by removing “three boilerplate standard text phrases from away notes and repeated performance.”

What Were the Results of the Study?

The researchers were able to find high performance in the home test data, while the away test data was low to high. Once they removed the aforementioned three boilerplate phrases, they were able to find improvements to the performance and improved generalizability in nearly all of the measures. Out of 171 errors, the boilerplate phrases that were used accounted for 104 of them, or 61%. Their removal was able to make quite a positive difference.

What does this mean for doctors and patients in terms of SUDEP? It means that regular expressions are a “feasible and probably a generalized method to identify variables related to SUDEP risk.” Therefore, it will be possible to implement the methods that were used in the study as a way to create larger patient cohorts for more research and to “generate electronic prompts for SUDEP counseling.”

How Much of a Problem is SUDEP?

Each year, about one out of every 1,000 people with epilepsy die from SUDEP. In fact, this is the top cause of death in people who have uncontrolled seizures. Many people are not getting the education and counseling they need on SUDEP, but with the implementation of the automated methods from the study, it should be able to provide clinicians with a better understanding of the patients who are most at risk and who should have counseling. At that point, it is the responsibility of healthcare professionals to provide that counseling.



Topics: Sudden Unexpected Death in Epilepsy (SUDEP)