New tool detects Parkinson's while sleeping
A key difficulty in PD drug development and disease management has been the lack of effective diagnostic biomarkers, the investigators note.
The current investigators used a large and diverse dataset created by pulling together datasets from numerous sources. The combined dataset contains more than 120,000 hours of nocturnal breathing signals from 757 patients with PD and 6914 individuals acting as the controls.Results showed that the AI model detected PD with high accuracy. For nights using breathing belt measurements, the model achieved an area under the curve of 0.889, with a sensitivity of 80.22% and a specificity of 78.62% .
Yang noted that the beauty of the system is that measurements can be"contactless" if using a wireless sensor and can be collected every night, allowing frequent assessment of severity."You just have to set up the device in the patient's home," he said. "We envision that the system could eventually be deployed in the homes of PD patients and individuals at high risk for PD to passively monitor their status and provide feedback to their provider," they write.
The investigators add that using the model may reduce the cost and duration of PD clinical trials, and so facilitate drug development. As it stands, PD drug development costs an average of $1.3 billion and takes about 13 years, which limits pursuit of new therapies for PD.
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