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Updated: Sep 11, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Clinical parameters predicted the progression to dementia in oldest old patients with mild cognitive impairment (MCI)
Nora Molina-Torres1, Carlos Platero2, Oscar Pérez-Berasategui3
1LAGENBIO, Laboratorio de Genética Bioquímica. Facultad de Veterinaria, Universidad de Zaragoza, C/ Miguel Servet 177, 50013 Zaragoza. Spain; Geriatrics Department, Hospital Nuestra Señora de Gracia, C. de Santiago Ramón y Cajal, 60, 50004, Zaragoza, Spain; Instituto de Investigación Sanitaria de Aragón (IIS Aragón). Centro de Investigación Biomédica de Aragón, C. de San Juan Bosco, 13, 50009 Zaragoza, Spain; Centre for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, 28029, Madrid, Spain.
Background:
This study intends to assess to what extent instruments commonly used in clinical practice, as well as plasma p-tau-181, can predict the progression from MCI to dementia. The usefulness of a disease progression model (DPM) is also explored.
Methods:
A longitudinal, prospective nested case-control study was conducted with patients from the Geriatrics outpatient clinics who met the MCI International Working Group criteria. The patients had a first clinical interview and two follow-ups after 12 and 24 months. Validated Spanish instruments were used for assessment, including the Mini-Mental State Examination (MMSE), the clock test, verbal fluency, the EURO-D depression scale, Barthel's Index, and Lawton's Index. P-tau-181 analysis was performed with SIMOA (Single MOlecule Array). A robust parametric disease progression model (RPDPM) was developed.
Results:
Fifty-nine patients fulfilled the inclusion criteria. The median age was 82.7 + /-8.7 years, 93 % had amnestic MCI and 45.8 % progressed to dementia (ICD-11 criteria) in two years. P-tau-181 was not prognostic. An RPDPM with the MMSE, clock test, and Lawton's Index could predict progression to dementia with an AUC of 0.945.
Conclusion:
A combination of the MMSE, clock test, and Lawton's Index in a DPM model predicted progression from MCI to dementia best. P-tau and other blood biomarkers did not predict progression. Our results highlight the strength of clinical variables to predict the progression of MCI.
Insights
Clinical assessments, including the Mini-Mental State Examination (MMSE), clock test, and Lawton
Area of Science:
- Neurology
- Geriatrics
- Biomarkers
Background:
- Mild Cognitive Impairment (MCI) progression to dementia is a significant clinical challenge.
- Predictive tools for MCI progression are crucial for timely intervention.
- Plasma biomarkers like p-tau-181 are being investigated for their prognostic value.
Purpose of the Study:
- To evaluate the predictive capability of clinical instruments and plasma p-tau-181 for MCI to dementia progression.
- To explore the utility of a disease progression model (DPM) in forecasting dementia development.
Main Methods:
- A prospective, nested case-control study involving 59 MCI patients.
- Longitudinal follow-up at 12 and 24 months.
- Assessment using validated Spanish instruments (MMSE, clock test, verbal fluency, EURO-D, Barthel, Lawton) and plasma p-tau-181 analysis via SIMOA.
Main Results:
- 45.8% of patients progressed to dementia within two years.
- Plasma p-tau-181 did not show prognostic value.
- A robust parametric disease progression model (RPDPM) incorporating MMSE, clock test, and Lawton's Index achieved an AUC of 0.945 for predicting dementia progression.
Conclusions:
- A DPM combining MMSE, clock test, and Lawton's Index effectively predicts MCI to dementia progression.
- Plasma biomarkers, including p-tau-181, were not found to be predictive.
- Clinical variables demonstrate significant strength in predicting MCI progression.
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