Personalised Medicine in the Identification of Preclinical Cognitive Impairment. Development of a Predictive Risk Model
NCT ID: NCT06114290
Last Updated: 2024-01-11
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
1150 participants
OBSERVATIONAL
2023-11-01
2025-07-31
Brief Summary
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Detailed Description
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Multicentre, non-interventional, convergent mixed methods observational study, with a prospective observational design part and a qualitative design part. Sample recruited randomly among users of the public health system in the participating geographical locations. Data will be collected in 6 regions (Andalucia, Castilla-Mancha, Catalonia, Valencia, Madrid and the Basque Country) and their rural and urban Primary Care (PC) networks.
Non-institutionalised subjects, aged between 55 and 70 years, assigned to PC centres in the territories included in the study, with a "living history" (recorded in the last 12 months) and without an established diagnosis of CI.
A descriptive analysis of the characteristics of the population will be carried out using frequencies and percentages or measures of central tendency and dispersion, with their 95% confidence intervals. Baseline socio-demographic and clinical characteristics will be compared in order to study the homogeneity of the sample. For the comparison of qualitative variables, the Chi-square test or Fisher's exact test will be used and for the comparison of quantitative variables, the t-test or Wilcoxon test will be used. Logistic regression models are proposed to analyse health outcome factors associated with mild cognitive impairment. All models will include repeated measures for each individual. All models will adjust for different risk factors, and for those factors that may change over time, the interaction between time and that factor will be studied.
Initially, multivariate linear latent models will be used for the predictive model of cognitive impairment risk. The integration of data from multiple sources of information will be done using multivariate probabilistic models, in order to find a representation of the patient in a feature space influenced by all data sources (visits).
Web tools such as Ingenuity Pathway Analysis will allow the integration of data at different molecular levels (genetic, protein and autoantibody), while artificial intelligence tools will allow the integration of such data, data derived from electrochemical sensors and data related to clinical and behavioural data with cognitive impairment in order to obtain a predictive model of cognitive impairment, neurodegeneration and AD.
Conditions
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Study Design
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OTHER
PROSPECTIVE
Eligibility Criteria
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Inclusion Criteria
* Aged between 55 and 70 years, attached to the PC centres of the territories included in the study
* Living history (at least one record in the last 12 months)
* Without an established diagnosis of CI.
Exclusion Criteria
* Those in whom genetic or biological testing may be affected by an underlying genetic or health condition.
* Underlying genetic or health condition.
* Patients who are hospitalised or institutionalised during follow-up will be excluded.
55 Years
70 Years
ALL
No
Sponsors
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Instituto de Investigación Biomédica de Salamanca
OTHER
Carlos III Health Institute
OTHER_GOV
Universidad Complutense de Madrid
OTHER
Biomedical Research Networking Centre on Frailty and Healthy Ageing
UNKNOWN
Biomedical Research Networking Centre on Mental Health
UNKNOWN
Institute of Biomedical Research of Lleida
UNKNOWN
Institute of Health and Biomedical Research of Alicante
UNKNOWN
Carlos III University of Madrid
UNKNOWN
University of Vigo
OTHER
Foundation for Biosanitary Research and Innovation in Primary Health Care
UNKNOWN
Biomedical Research Networking Centre on Epidemiology and Public Health
UNKNOWN
Research Network on Chronicity, Primary Care and Health Prevention and Promotion
UNKNOWN
Instituto de Salud Carlos III
OTHER_GOV
Responsible Party
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Teresa Moreno Casbas
Director of National Healthcare Research Unit Investén-isciii
Principal Investigators
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Angeles Almeida, PhD
Role: PRINCIPAL_INVESTIGATOR
Consejo Superior de Investigaciones Científicas (CSIC)
Rodrigo Barderas, PhD
Role: PRINCIPAL_INVESTIGATOR
Instituto de Salud Carlos III
MARIA TERESA MORENO-CASBAS, PhD
Role: PRINCIPAL_INVESTIGATOR
Nursing and Healthcare Research Unit (Investén-isciii). Instituto de Salud Carlos III. Madrid
Locations
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Sant Vicent I Health Center
San Vicent del Raspeig, Alicante, Spain
Camps Blanc Health Center
Sant Boi de Llobregat, Barcelona, Spain
Zone 8 Health Center
Albacete, Castille-La Mancha, Spain
Gibraleón Health Center
Gibraleón, Huelva, Spain
Punta Umbría Health Center
Punta Umbría, Huelva, Spain
Irala Health Center
Bilbao, , Spain
Onze de Setembre Health Center
Lleida, , Spain
San Andres Health Centre
Madrid, , Spain
Countries
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Central Contacts
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Facility Contacts
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María Isabel Orts
Role: primary
Mª Isabel Feria
Role: primary
María Emilia Villena
Role: primary
Rafaela Camacho
Role: primary
Rafaela Camacho
Role: primary
Mª Ángeles Cidoncha
Role: primary
Esther Rubinat
Role: primary
Pedro Otones
Role: primary
Other Identifiers
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PMP22/00084
Identifier Type: -
Identifier Source: org_study_id
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