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. Author manuscript; available in PMC: 2024 Jun 1.
Published in final edited form as: Alzheimers Dement. 2022 Dec 14;19(6):2497–2507. doi: 10.1002/alz.12875

Figure 3. Prediction algorithm for cognitive decline.

Figure 3.

Example of the implementation of the regression models at https://brainapps.shinyapps.io/PredictMMSE/. At this web-site it is possible to enter basic demographic data (age, sex and education), biomarker data (tau-PET temporal ROI SUVR and plasma NfL (pg/ml)) as well as raw cognitive test scores (MMSE, ADAS delayed recall, TMT-B and animal fluency). The example shows the predicted individual change in cognition for a 70-year old female who has 14 years of education, a pathological tau-PET (2.44 SUVR), a plasma NfL of 4.5 pg/ml, and a cortical thickness of 2.3 mm (please note that entering cortical thickness is optional). She has a baseline MMSE score of 27, scores seven errors on a ten-word delayed recall test, completes the Trail-Making Test B in 124 seconds and names twelve animals in 1 min.