Clinical trial NCT06710028: Trustworthy Artificial Intelligence for Improvement of Stroke Outcomes
Official title: Trustworthy Artificial Intelligence for Improvement of Stroke Outcomes. Phase II Prospective Study for AI Models Optimization
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Stroke, Acute
Stroke, Ischemic
Stroke
Lead sponsor: Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Sponsor class: OTHER
First posted: 2024-11-29
Enrollment: 1000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: All consecutive ischemic stroke patients admitted to the participating sites, who are older than 18 and who signed the informed consent (either signed by the patient himself or a next of kin).

Brief summary: Stroke is a leading cause of death and disability worldwide. The clinical validation of explainable and interpretable Artificial Intelligence (AI) solutions to assist a timely, personalised management of the acute phase of stroke, would have a major impact since it can greatly reduce the disability levels of patients. Also, the prediction of long-term outcomes is a crucial factor as it may determine critical decisions such as the discharge destination for the patient. Moreover, compliance with guideline-based secondary stroke prevention has been demonstrated to reduce stroke recurrence, but currently, only 40% of patients are adherent to preventive treatments 3 months after stroke. Therefore, patients´ outcomes can improve with proper patient communication and engagement packages. AI may have a dramatic impact on stroke patient journey, improving predictions, resulting in a better choice of secondary stroke strategies, as well as using evidence-based information to promote better adherence to treatment and reduction of vascular risk factors.

The aim of this multicentre observational prospective study is to develop and validate AI-based tools to predict short and long-term outcomes in ischemic stroke patients. Specifically, this study aims to demonstrate the accuracy of AI models in predicting the functional outcome of ischaemic stroke patients as measured by the National Institutes of health Stroke Scale (NIHSS, 0-42) and the modified Rankin Scale (mRS, 0-6) scores at hospital discharge and at 3, 6 and 12 months after discharge. Prospective ischemic stroke patients from 3 Large European centres will be recruited. The training and testing of local AI models will be performed using hospitalization data, collected during the standard of care procedures for stroke patient pathways, and outpatient monitored data from a remote home-care system (NORA app) during the follow-up after discharge. These local models will then be integrated into a federated learning system, where only a global AI model, derived from combined insights of all local models, is shared across participating hospitals. The individual local models and the original data are not shared, ensuring data privacy and security. The accuracy and performance of prospectively optimized AI models in predicting clinical outcomes over a 12-month follow-up period will be evaluated and compared to the actual outcomes of the patients.


Eligibility criteria: Inclusion Criteria:

1. Subject is 18 years of age or older
2. Diagnosis of acute ischemic stroke
3. Signature of the informed consent form by the patient or a next of kin

Exclusion Criteria:

* No exclusion criteria are contemplated for this study.

Primary outcomes:
measure: AI model's accuracy in predicting short-term functional stroke outcomes
timeFrame: 24 months
Secondary outcomes:
measure: AI model's accuracy in predicting long-term functional outcomes
timeFrame: 24 months
measure: AI model's accuracy in predicting stroke associated risks
timeFrame: 24 months
Other outcomes:
Locations:
city: Leuven
country: Belgium
facility: KATHOLIEKE UNIVERSITEIT LEUVEN (KU Leuven)
city: Roma
country: Italy
facility: Fondazione Policlinico Universitario A. Gemelli IRCCS, UOC Neurologia
state: Lazio
city: Barcelona
country: Spain
facility: Hospital Vall D'Hebron- Institut de Recerca (Vhir)
Study officials:
affiliation: Fondazione Policlinico Universitario A. Gemelli, IRCCS
name: Pietro Caliandro, MD
role: PRINCIPAL_INVESTIGATOR
References: