Mild Cognitive Impairment (MCI)PrevAlNCT07731191
Digital Solutions for Predicting the Biological Mechanisms of Alzheimer's Disease Through the Analysis of Risk Factors
A study testing Digital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factors in people with Mild Cognitive Impairment (MCI) and Subjective Cognitive Decline (SCD), run by IRCCS Centro San Giovanni di Dio Fatebenefratelli at 2 sites in Italy.
Trial summary
Population ageing is one of the main factors responsible for the global increase in the prevalence of dementia. Recent evidence suggests that modifiable risk factors, such as cardiovascular disease and lifestyle, may increase the risk of developing dementia and contribute to its progression. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Mild Cognitive Impairment (MCI), Subjective Cognitive Decline (SCD)
- What is being tested?
- Digital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factors
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 240 participants
- Where
- 2 sitesItaly
- Study dates
- 24 Jun 2026to 15 Nov 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Male or female subjects aged more than 18 years at the time of signing the informed consent form;
- Subjects with MCI or SCD who, at the time of their first visit, did not have a clinical diagnosis of dementia (MMSE ≥ 24);
- Smartphone user.
Who cannot join
- Age younger than that stated in the inclusion criterion;
- Inability to understand.
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
Italy2 sites, 2 recruiting
- Recruiting
ASST Spedali Civili di Brescia
Brescia, BS, 25123
Alessandro Padovani, MD, +39 0303995632, alessandro.padovani@unibs.it
Luisa Alessandrini, +39 0303996968, grant.office@asst-spedalicivili.it
- Recruiting
IRCCS Istituto Centro San Giovanni Di Dio - Fatebenefratelli
Brescia, BS, 25125
Barbara Borroni, MD, +39 0303501213, bborroni@fatebenefratelli.eu
Barbara Borroni, MD
About this study
Official title: Development of Digital Solutions for the Prediction of the Biological Mechanisms of Alzheimer's Disease Through the Analysis of Risk Factors (PrevAI)
Population ageing is one of the main factors responsible for the global increase in the prevalence of dementia. Recent evidence suggests that modifiable risk factors, such as cardiovascular disease and lifestyle, may increase the risk of developing dementia and contribute to its progression. Furthermore, the use of non-invasive plasma biomarkers enables the identification of individuals with neurodegenerative diseases, even in the prodromal stage. However, the relationship between the cumulative burden of risk factors and plasma biomarkers is still poorly understood.
The main objective of this study is to identify and estimate the risk associated with modifiable and non-modifiable predictors (risk factors) linked to the development of Alzheimer's disease (AD) and non-AD dementia, as well as biological alterations consistent with AD or non-AD, through the development of a predictive tool based on Artificial Intelligence algorithms (Machine Learning model). The study also aims to provide a range of technological tools (an app for active patient monitoring and a web platform for clinicians) that could improve risk stratification and the personalisation of care pathways.
The study is divided into two different phases. Firstly, a retrospective phase is conducted in order to construct a predictive model for the risk of dementia and biological alterations consistent with AD. Secondly, a prospective phase is performed for the validation of the predictive model.
- Being tested
- Digital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factors
- Medical subject headings
- Cognitive Dysfunction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Digital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factorsDevice
Also called App for active patient monitoring
The intervention consists of a mobile application ("app") for risk monitoring with gamified patient engagement, which is design to support remote health monitoring and participant adherence to the study. Participants will enter informative clinical variables every 3 months, including weight, height, age, systolic/diastolic blood pressure, and blood glucose levels. The app generates a qualitative risk assessment (low/medium/high) based on entered data, intended as a clinical monitoring support tool for the participating sites and not as a diagnostic tool that replaces medical evaluation and/or clinical judgment.
Unlike standard data collection apps, the intervention provides continuous engagement incentives in the form of visual feedback and motivational messaging.
| Study group | Role | What they receive |
|---|---|---|
| Subjects with MCI or SCD | Experimental | Not described Receives: Device: Digital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factors |
What is being measured
The primary outcome is the main question the study is designed to answer.
Conversion rate to dementia
Risk score that assesses the individual risk associated with predictors linked to (i) the development of AD and non-AD dementia, and (ii) biological biological changes consistent with AD or non-AD pathology.
Measured: From enrollment to 3-6 months after enrollment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Jul 2026
- Study start24 Jun 2026
- Primary completion15 Nov 2026 (estimated)
- Study completion15 Nov 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (25)Papers the sponsor has linked to this study.
- Other trials for Mild Cognitive Impairment (MCI)Studies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 240 participants (estimated)
Sponsor and investigators
- Lead sponsor
- IRCCS Centro San Giovanni di Dio Fatebenefratelli
- Sponsor type
- University, hospital or other
- Collaborators
- Asst Degli Spedali Civili Di Brescia
- Responsible party
- Principal investigator, Prof. Barbara Borroni, IRCCS Centro San Giovanni di Dio Fatebenefratelli
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07731191
- Sponsor's protocol ID
- PrevAl
- Acronym
- PrevAl
- Status last verified
- Jul 2026
- First submitted
- 23 Jul 2026
- Last updated
- 28 Jul 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Redolfi A, Manset D, Barkhof F, Wahlund LO, Glatard T, Mangin JF, Frisoni GB; neuGRID Consortium, for the Alzheimer's Disease Neuroimaging Initiative. Head-to-head comparison of two popular cortical thickness extraction algorithms: a cross-sectional and longitudinal study. PLoS One. 2015 Mar 17;10(3):e0117692. doi: 10.1371/journal.pone.0117692. eCollection 2015.
PubMed 25781983Mitchell AJ, Shiri-Feshki M. Rate of progression of mild cognitive impairment to dementia--meta-analysis of 41 robust inception cohort studies. Acta Psychiatr Scand. 2009 Apr;119(4):252-65. doi: 10.1111/j.1600-0447.2008.01326.x. Epub 2008 Feb 18.
PubMed 19236314Martinez-Dubarbie F, Guerra-Ruiz A, Lopez-Garcia S, Lage C, Fernandez-Matarrubia M, Infante J, Pozueta-Cantudo A, Garcia-Martinez M, Corrales-Pardo A, Bravo M, Lopez-Hoyos M, Irure-Ventura J, Valeriano-Lorenzo E, Garcia-Unzueta MT, Sanchez-Juan P, Rodriguez-Rodriguez E. Diagnostic Accuracy of Plasma p-tau217 for Detecting Pathological Cerebrospinal Fluid Changes in Cognitively Unimpaired Subjects Using the Lumipulse Platform. J Prev Alzheimers Dis. 2024;11(6):1581-1591. doi: 10.14283/jpad.2024.152.
PubMed 39559871Sathyan A, Weinberg AI, Cohen K. Interpretable AI for bio-medical applications. Complex Eng Syst. 2022 Dec;2(4):18. doi: 10.20517/ces.2022.41. Epub 2022 Dec 28.
PubMed 37025127Padovani A, Galli A, Bazzoli E, Tolassi C, Caratozzolo S, Gumina B, Benussi A, Libri I, Outeiro TF, Pilotto A. The role of insulin resistance and APOE genotype on blood-brain barrier integrity in Alzheimer's disease. Alzheimers Dement. 2025 Feb;21(2):e14556. doi: 10.1002/alz.14556.
PubMed 39992249Jessen F, Amariglio RE, Buckley RF, van der Flier WM, Han Y, Molinuevo JL, Rabin L, Rentz DM, Rodriguez-Gomez O, Saykin AJ, Sikkes SAM, Smart CM, Wolfsgruber S, Wagner M. The characterisation of subjective cognitive decline. Lancet Neurol. 2020 Mar;19(3):271-278. doi: 10.1016/S1474-4422(19)30368-0. Epub 2020 Jan 17.
PubMed 31958406McKeith IG, Ferman TJ, Thomas AJ, Blanc F, Boeve BF, Fujishiro H, Kantarci K, Muscio C, O'Brien JT, Postuma RB, Aarsland D, Ballard C, Bonanni L, Donaghy P, Emre M, Galvin JE, Galasko D, Goldman JG, Gomperts SN, Honig LS, Ikeda M, Leverenz JB, Lewis SJG, Marder KS, Masellis M, Salmon DP, Taylor JP, Tsuang DW, Walker Z, Tiraboschi P; prodromal DLB Diagnostic Study Group. Research criteria for the diagnosis of prodromal dementia with Lewy bodies. Neurology. 2020 Apr 28;94(17):743-755. doi: 10.1212/WNL.0000000000009323. Epub 2020 Apr 2.
PubMed 32241955Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011 May;7(3):270-9. doi: 10.1016/j.jalz.2011.03.008. Epub 2011 Apr 21.
PubMed 21514249McKeith IG, Boeve BF, Dickson DW, Halliday G, Taylor JP, Weintraub D, Aarsland D, Galvin J, Attems J, Ballard CG, Bayston A, Beach TG, Blanc F, Bohnen N, Bonanni L, Bras J, Brundin P, Burn D, Chen-Plotkin A, Duda JE, El-Agnaf O, Feldman H, Ferman TJ, Ffytche D, Fujishiro H, Galasko D, Goldman JG, Gomperts SN, Graff-Radford NR, Honig LS, Iranzo A, Kantarci K, Kaufer D, Kukull W, Lee VMY, Leverenz JB, Lewis S, Lippa C, Lunde A, Masellis M, Masliah E, McLean P, Mollenhauer B, Montine TJ, Moreno E, Mori E, Murray M, O'Brien JT, Orimo S, Postuma RB, Ramaswamy S, Ross OA, Salmon DP, Singleton A, Taylor A, Thomas A, Tiraboschi P, Toledo JB, Trojanowski JQ, Tsuang D, Walker Z, Yamada M, Kosaka K. Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology. 2017 Jul 4;89(1):88-100. doi: 10.1212/WNL.0000000000004058. Epub 2017 Jun 7.
PubMed 28592453Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, Ogar JM, Rohrer JD, Black S, Boeve BF, Manes F, Dronkers NF, Vandenberghe R, Rascovsky K, Patterson K, Miller BL, Knopman DS, Hodges JR, Mesulam MM, Grossman M. Classification of primary progressive aphasia and its variants. Neurology. 2011 Mar 15;76(11):1006-14. doi: 10.1212/WNL.0b013e31821103e6. Epub 2011 Feb 16.
PubMed 21325651Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, van Swieten JC, Seelaar H, Dopper EG, Onyike CU, Hillis AE, Josephs KA, Boeve BF, Kertesz A, Seeley WW, Rankin KP, Johnson JK, Gorno-Tempini ML, Rosen H, Prioleau-Latham CE, Lee A, Kipps CM, Lillo P, Piguet O, Rohrer JD, Rossor MN, Warren JD, Fox NC, Galasko D, Salmon DP, Black SE, Mesulam M, Weintraub S, Dickerson BC, Diehl-Schmid J, Pasquier F, Deramecourt V, Lebert F, Pijnenburg Y, Chow TW, Manes F, Grafman J, Cappa SF, Freedman M, Grossman M, Miller BL. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011 Sep;134(Pt 9):2456-77. doi: 10.1093/brain/awr179. Epub 2011 Aug 2.
PubMed 21810890McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011 May;7(3):263-9. doi: 10.1016/j.jalz.2011.03.005. Epub 2011 Apr 21.
PubMed 21514250Jack CR Jr, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, Hansson O, Ho C, Jagust W, McDade E, Molinuevo JL, Okonkwo OC, Pani L, Rafii MS, Scheltens P, Siemers E, Snyder HM, Sperling R, Teunissen CE, Carrillo MC. Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup. Alzheimers Dement. 2024 Aug;20(8):5143-5169. doi: 10.1002/alz.13859. Epub 2024 Jun 27.
PubMed 38934362Biessels GJ, Despa F. Cognitive decline and dementia in diabetes mellitus: mechanisms and clinical implications. Nat Rev Endocrinol. 2018 Oct;14(10):591-604. doi: 10.1038/s41574-018-0048-7.
PubMed 30022099Hooper C, Coley N, Delrieu J, Guyonnet S. Lifestyle factors and plasma biomarkers of Alzheimer's disease: A narrative review. J Prev Alzheimers Dis. 2025 Jun;12(6):100130. doi: 10.1016/j.tjpad.2025.100130. Epub 2025 Mar 12.
PubMed 40082178
Study at a glance
From the registry record, last updated by the sponsor on 28 Jul 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of Digital Solutions for the Prediction of the Biological Mechanisms of Alzheimer's Disease Through the Analysis of Risk Factors (PrevAI)
- ClinicalTrials.gov ID
- NCT07731191
- Acronym / sponsor ID
- PrevAl / PrevAl
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 240 participants (estimated)
- Lead sponsor
- IRCCS Centro San Giovanni di Dio FatebenefratelliUniversity, hospital or other
- Collaborators
- Asst Degli Spedali Civili Di Brescia
- Study start
- 24 Jun 2026 (actual)
- Primary completion
- 15 Nov 2026 (estimated)
- Study completion
- 15 Nov 2026 (estimated)
- First posted
- 28 Jul 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Population ageing is one of the main factors responsible for the global increase in the prevalence of dementia. Recent evidence suggests that modifiable risk factors, such as cardiovascular disease and lifestyle, may increase the risk of developing dementia and contribute to its progression. Furthermore, the use of non-invasive plasma biomarkers enables the identification of individuals with neurodegenerative diseases, even in the prodromal stage. However, the relationship between the cumulative burden of risk factors and plasma biomarkers is still poorly understood.
The main objective of this study is to identify and estimate the risk associated with modifiable and non-modifiable predictors (risk factors) linked to the development of Alzheimer's disease (AD) and non-AD dementia, as well as biological alterations consistent with AD or non-AD, through the development of a predictive tool based on Artificial Intelligence algorithms (Machine Learning model). The study also aims to provide a range of technological tools (an app for active patient monitoring and a web platform for clinicians) that could improve risk stratification and the personalisation of care pathways.
The study is divided into two different phases. Firstly, a retrospective phase is conducted in order to construct a predictive model for the risk of dementia and biological alterations consistent with AD. Secondly, a prospective phase is performed for the validation of the predictive model.
Study design
- Primary purpose
- Screening
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Subjects with MCI or SCD | Experimental | Device: Digital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factors |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Male or female subjects aged more than 18 years at the time of signing the informed consent form;
- Subjects with MCI or SCD who, at the time of their first visit, did not have a clinical diagnosis of dementia (MMSE ≥ 24);
- Smartphone user.
Key exclusion criteria (2 listed)
- Age younger than that stated in the inclusion criterion;
- Inability to understand.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Digital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factorsAlso: App for active patient monitoringThe intervention consists of a mobile application ("app") for risk monitoring with gamified patient engagement, which is design to support remote health monitoring and participant adherence to the study. Participants will enter informative clinical variables every 3 months, including weight, height, age, systolic/diastolic blood pressure, and blood glucose levels. The app generates a qualitative risk assessment (low/medium/high) based on entered data, intended as a clinical monitoring support tool for the participating sites and not as a diagnostic tool that replaces medical evaluation and/or clinical judgment. Unlike standard data collection apps, the intervention provides continuous engagement incentives in the form of visual feedback and motivational messaging. | Device | Subjects with MCI or SCD |
Primary outcome
Conversion rate to dementia
Time frame: From enrollment to 3-6 months after enrollment
Risk score that assesses the individual risk associated with predictors linked to (i) the development of AD and non-AD dementia, and (ii) biological biological changes consistent with AD or non-AD pathology.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Jul 2026.
- Background: PubMed 25781983Redolfi A, Manset D, Barkhof F, Wahlund LO, Glatard T, Mangin JF, Frisoni GB; neuGRID Consortium, for the Alzheimer's Disease Neuroimaging Initiative. Head-to-head comparison of two popular cortical thickness extraction algorithms: a cross-sectional and longitudinal study. PLoS One. 2015 Mar 17;10(3):e0117692. doi: 10.1371/journal.pone.0117692. eCollection 2015.
- Background: PubMed 19236314Mitchell AJ, Shiri-Feshki M. Rate of progression of mild cognitive impairment to dementia--meta-analysis of 41 robust inception cohort studies. Acta Psychiatr Scand. 2009 Apr;119(4):252-65. doi: 10.1111/j.1600-0447.2008.01326.x. Epub 2008 Feb 18.
- Background: PubMed 39559871Martinez-Dubarbie F, Guerra-Ruiz A, Lopez-Garcia S, Lage C, Fernandez-Matarrubia M, Infante J, Pozueta-Cantudo A, Garcia-Martinez M, Corrales-Pardo A, Bravo M, Lopez-Hoyos M, Irure-Ventura J, Valeriano-Lorenzo E, Garcia-Unzueta MT, Sanchez-Juan P, Rodriguez-Rodriguez E. Diagnostic Accuracy of Plasma p-tau217 for Detecting Pathological Cerebrospinal Fluid Changes in Cognitively Unimpaired Subjects Using the Lumipulse Platform. J Prev Alzheimers Dis. 2024;11(6):1581-1591. doi: 10.14283/jpad.2024.152.
- Background: PubMed 37025127Sathyan A, Weinberg AI, Cohen K. Interpretable AI for bio-medical applications. Complex Eng Syst. 2022 Dec;2(4):18. doi: 10.20517/ces.2022.41. Epub 2022 Dec 28.
- Background: PubMed 39992249Padovani A, Galli A, Bazzoli E, Tolassi C, Caratozzolo S, Gumina B, Benussi A, Libri I, Outeiro TF, Pilotto A. The role of insulin resistance and APOE genotype on blood-brain barrier integrity in Alzheimer's disease. Alzheimers Dement. 2025 Feb;21(2):e14556. doi: 10.1002/alz.14556.
- Background: PubMed 31958406Jessen F, Amariglio RE, Buckley RF, van der Flier WM, Han Y, Molinuevo JL, Rabin L, Rentz DM, Rodriguez-Gomez O, Saykin AJ, Sikkes SAM, Smart CM, Wolfsgruber S, Wagner M. The characterisation of subjective cognitive decline. Lancet Neurol. 2020 Mar;19(3):271-278. doi: 10.1016/S1474-4422(19)30368-0. Epub 2020 Jan 17.
- Background: PubMed 32241955McKeith IG, Ferman TJ, Thomas AJ, Blanc F, Boeve BF, Fujishiro H, Kantarci K, Muscio C, O'Brien JT, Postuma RB, Aarsland D, Ballard C, Bonanni L, Donaghy P, Emre M, Galvin JE, Galasko D, Goldman JG, Gomperts SN, Honig LS, Ikeda M, Leverenz JB, Lewis SJG, Marder KS, Masellis M, Salmon DP, Taylor JP, Tsuang DW, Walker Z, Tiraboschi P; prodromal DLB Diagnostic Study Group. Research criteria for the diagnosis of prodromal dementia with Lewy bodies. Neurology. 2020 Apr 28;94(17):743-755. doi: 10.1212/WNL.0000000000009323. Epub 2020 Apr 2.
- Background: PubMed 21514249Albert MS, DeKosky ST, Dickson D, Dubois B, Feldman HH, Fox NC, Gamst A, Holtzman DM, Jagust WJ, Petersen RC, Snyder PJ, Carrillo MC, Thies B, Phelps CH. The diagnosis of mild cognitive impairment due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011 May;7(3):270-9. doi: 10.1016/j.jalz.2011.03.008. Epub 2011 Apr 21.
- Background: PubMed 28592453McKeith IG, Boeve BF, Dickson DW, Halliday G, Taylor JP, Weintraub D, Aarsland D, Galvin J, Attems J, Ballard CG, Bayston A, Beach TG, Blanc F, Bohnen N, Bonanni L, Bras J, Brundin P, Burn D, Chen-Plotkin A, Duda JE, El-Agnaf O, Feldman H, Ferman TJ, Ffytche D, Fujishiro H, Galasko D, Goldman JG, Gomperts SN, Graff-Radford NR, Honig LS, Iranzo A, Kantarci K, Kaufer D, Kukull W, Lee VMY, Leverenz JB, Lewis S, Lippa C, Lunde A, Masellis M, Masliah E, McLean P, Mollenhauer B, Montine TJ, Moreno E, Mori E, Murray M, O'Brien JT, Orimo S, Postuma RB, Ramaswamy S, Ross OA, Salmon DP, Singleton A, Taylor A, Thomas A, Tiraboschi P, Toledo JB, Trojanowski JQ, Tsuang D, Walker Z, Yamada M, Kosaka K. Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology. 2017 Jul 4;89(1):88-100. doi: 10.1212/WNL.0000000000004058. Epub 2017 Jun 7.
- Background: PubMed 21325651Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, Ogar JM, Rohrer JD, Black S, Boeve BF, Manes F, Dronkers NF, Vandenberghe R, Rascovsky K, Patterson K, Miller BL, Knopman DS, Hodges JR, Mesulam MM, Grossman M. Classification of primary progressive aphasia and its variants. Neurology. 2011 Mar 15;76(11):1006-14. doi: 10.1212/WNL.0b013e31821103e6. Epub 2011 Feb 16.
- Background: PubMed 21810890Rascovsky K, Hodges JR, Knopman D, Mendez MF, Kramer JH, Neuhaus J, van Swieten JC, Seelaar H, Dopper EG, Onyike CU, Hillis AE, Josephs KA, Boeve BF, Kertesz A, Seeley WW, Rankin KP, Johnson JK, Gorno-Tempini ML, Rosen H, Prioleau-Latham CE, Lee A, Kipps CM, Lillo P, Piguet O, Rohrer JD, Rossor MN, Warren JD, Fox NC, Galasko D, Salmon DP, Black SE, Mesulam M, Weintraub S, Dickerson BC, Diehl-Schmid J, Pasquier F, Deramecourt V, Lebert F, Pijnenburg Y, Chow TW, Manes F, Grafman J, Cappa SF, Freedman M, Grossman M, Miller BL. Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain. 2011 Sep;134(Pt 9):2456-77. doi: 10.1093/brain/awr179. Epub 2011 Aug 2.
- Background: PubMed 21514250McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011 May;7(3):263-9. doi: 10.1016/j.jalz.2011.03.005. Epub 2011 Apr 21.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
IRCCS Istituto Centro San Giovanni Di Dio - Fatebenefratelli
Brescia, Italy
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Digital solution for the prediction of the biological mechanisms of Alzheimer's disease through the analysis of risk factors in people with Mild Cognitive Impairment (MCI) and Subjective Cognitive Decline (SCD), run by IRCCS Centro San Giovanni di Dio Fatebenefratelli at 2 sites in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 28 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Conversion rate to dementia (time frame: From enrollment to 3-6 months after enrollment). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07731191, which also lists 25 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 28 Jul 2026.