Amyloid Prediction in Early Stage Alzheimer's Disease From Acoustic and Linguistic Patterns of Speech - PAST Extension
Amyloid Prediction in Early Stage Alzheimer's Disease From Acoustic and Linguistic Patterns of Speech - PAST Extension
The primary objective of the study is to evaluate whether a set of algorithms analysing
 acoustic and linguistic patterns of speech can detect amyloid-specific cognitive impairment
 in early stage Alzheimer's disease, based on archival spoken or written language samples, as
 measured by the AUC of the receiver operating characteristic curve of the binary classifier
 distinguishing between amyloid positive and amyloid negative arms. Secondary objectives
 include (1) evaluating how many years before diagnosis of MCI such algorithms work, as
 measured on binary classifier performance of the classifiers trained to classify MCI vs
 cognitively normal (CN) arms using archival material from the following time bins before MCI
 diagnosis: 0-5 years, 5-10 years, 10-15 years, 15-20 years, 20-25 years; (2) evaluating at
 what age such algorithms can detect later amyloid positivity, as measured on binary
 classifier performance of the classifiers trained to classify amyloid positive vs amyloid
 negative arms using archival material from the following age bins: younger than 50, 50-55,
 55-60, 65-70, 70-75 years old.
Inclusion Criteria:

 -  Subjects are fully eligible for and have completed the AMYPRED (Amyloid Prediction in
 early stage Alzheimer's disease from acoustic and linguistic patterns of speech)
 study.

 (See https://clinicaltrials.gov/ct2/show/NCT04828122)

 -  Subject has access to audio or written recordings created by them that are available
 for collection.

 -  Subject consents to take part in PAST extension study.

 Exclusion Criteria:

 -  Subject hasn't completed the full visit day in the AMYPRED study.