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Voice recordings helped predict which patients with mild cognitive impairment developed Alzheimer's dementia in 6 years.

Combined with basic demographic information, speech patterns recorded in neuropsychological exams achieved an accuracy of 78.5% and a sensitivity of 81.1% in predicting progression from mild cognitive impairment to dementia in a 6-year window, reported Ioannis Paschalidis, PhD, of Boston University, and colleagues in .

"However, the specificity of predicting whether an individual with mild cognitive impairment will progress to Alzheimer's disease within 6 years was moderate, at 75%," Paschalidis and co-authors wrote. "To reduce the costs associated with recruiting subjects for clinical trials, it is important to improve the specificity."

The study leveraged AI methods for speech recognition and processed the resulting text using language models. The researchers used the content of the interview -- words spoken and how they were structured -- not acoustic features like enunciation or talking speed.

The approach could be developed into a remote screening tool for predicting progression to Alzheimer's dementia, the researchers noted. "If you can predict what will happen, you have more of an opportunity and time window to intervene with drugs, and at least try to maintain the stability of the condition and prevent the transition to more severe forms of dementia," Paschalidis said in a statement.

In previous work, Paschalidis and colleagues reported that a model using natural language processing (NLP) discerned normal cognition from mild cognitive impairment and dementia based on voice recordings. Other researchers have found that speech patterns in phone conversations could spot people with early-to-moderate Alzheimer's dementia.

The current study evaluated neuropsychological test interviews of 166 participants, including 90 people who had progressed from mild cognitive impairment to dementia within 6 years, and 76 people who had stable mild cognitive impairment in that period. The median age was 81, and nearly two-thirds of participants were women.

Neuropsychological test interviews were digitally recorded in the Framingham Heart Study. These hour-long interviews include cognitive tests like the Boston Naming Test, the Hooper Visual Organization Test, and the Wechsler Memory Scale.

"The neuropsychological test, triggered by patient history and in conjunction with a clinical examination, provides a comprehensive evaluation of cognitive function, including attention, memory, language, and visuospatial abilities," Paschalidis and co-authors observed.

"Researchers have explored computer-based approaches to predict the progression from mild cognitive impairment to dementia using neuropsychological tests, primarily relying on hand-crafted features and cognitive scores extracted from the neuropsychological test by clinicians," they pointed out. "However, these approaches have not yet achieved full automation, limiting their potential for more precise and efficient cognitive evaluations."

Paschalidis and colleagues used recorded neuropsychological test interviews to predict the likelihood of participants transitioning to Alzheimer's, training a model to spot connections among speech, demographics, diagnosis, and disease progression. The analysis used text automatically transcribed from the recordings.

The model's accuracy and sensitivity outperformed other measures at predicting progression to dementia in 6 years. Standard neuropsychological tests had an accuracy of 74.7% and sensitivity of 77.2%, for example. The Mini-Mental State Examination (MMSE) had an accuracy of predicting progression to dementia over 6 years of 62.9% and a sensitivity of 66.7%.

The study demonstrates the potential of automatic speech recognition and NLP techniques to develop a prediction tool to identify which patients with mild cognitive impairment are at risk of dementia, the researchers said.

"Our method achieved high accuracy and outperformed other non-invasive approaches," Paschalidis and co-authors wrote. "However, further prospective studies with larger populations are necessary to validate the generalizability of our models."

The definition of mild cognitive impairment needs to be standardized to better compare results, they noted. "With continued development and refinement, our approach may contribute to early intervention and selection in clinical trials for novel Alzheimer's disease treatments, ultimately improving patient outcomes," they wrote.

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