Method searches healthcare records for undiagnosed AADC deficiency
New tool could help clinicians identify patients eligible for further testing
Researchers in the U.K. have developed a new method to help identify people with undiagnosed AADC deficiency based on data from healthcare records.
The method was described in a study, “Interrogation of coded healthcare data to facilitate identification of patients with a rare neurotransmitter disorder; Aromatic L-Amino Acid Decarboxylase Deficiency,” that was published in Intelligence-Based Medicine.
The work was funded by PTC Therapeutics, the company that markets the AADC gene therapy Kebilidi (eladocagene exuparvovec-tneq), sold as Upstaza in Europe and the U.K.
AADC deficiency is a genetic disorder caused by mutations in the gene that provides instructions to make the enzyme AADC (aromatic L-amino acid decarboxylase), which is necessary to make certain neurotransmitters, or signaling molecules that cells in the brain use to communicate with each other. As a result of the mutations, people with AADC deficiency have lower-than-normal neurotransmitter levels, which ultimately leads to disease symptoms.
Diagnosing AADC deficiency can be challenging, especially because the condition is extremely rare. Getting an accurate diagnosis is essential to allow patients to get the appropriate treatment, and this is especially important now since a gene therapy for AADC deficiency is available.
Specific search terms used to identify patients who may have AADC deficiency
In this study, scientists tested a method to look for missed cases of AADC deficiency in U.K. healthcare records. The method relies on a tool called a structured language query, which is essentially a specific set of search terms that can be used to identify records from patients that show signs indicative of AADC deficiency. Doctors can then look over the identified records to see if any of the patients should be tested for the condition.
“This novel and adjustable approach provides opportunities to clinicians to identify patient cohorts eligible for specialist investigations,” the researchers wrote.
For this study, the structured language query method was used to analyze records from seven hospitals in the U.K. The query identified records from 340 patients showing potential signs of AADC deficiency. After looking at the records in more depth, doctors determined that 31 of the patients were suitable for further testing.
Nine of these patients were tested but none of them had AADC deficiency. The researchers noted this negative finding isn’t all that surprising given that AADC deficiency is extremely rare.
The scientists said that more work could be done to test this method in other settings and to refine the search tool to maximize its ability to detect undiagnosed cases of AADC deficiency. They also noted a similar method could be used to look for undiagnosed people with other rare conditions.
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