Modeling Trajectories of Functional Outcome in Patients With Severe Acquired Brain Injuries Using a Non-Linear Dynamic Evolution Approach.
Trial ID: NCT06162091
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2024-01-10
Completion date: 2025-05-31
Sponsor: Istituto per la Ricerca e l'Innovazione Biomedica
Collaborators: Istituto S.Anna Crotone; IRCCS Centro Neurolesi Bonino Pulejo; Centro Cardinal Ferrari, Fontanellato, Parma; Fondazione Istituto G. Giglio, Cefalù (PA); Habilita Istituto di Neuroriabilitazione, Zingonia (BG); Casa Sollievo della Sofferenza IRCCS; IRCCS Istituto delle Scienze Neurologiche di Bologna; IRCCS Sacro Cuore Don Calabria di Negrar; Fondazione Salvatore Maugeri; Istituti Clinici Zucchi; Istituto Clinico Humanitas; Istituto Medicina Fisica E Riabilitazione Gervasutta, Udine; Montecatone Rehabilitation Institute S.p.A.; Ospedale Di Riabilitazione Fondazione Santa Lucia, Roma; Ospedale San Giovanni Battista, Foligno (PG); Ospedale Ss. Trinità Di Fossano, Cuneo; Fondazione Don Carlo Gnocchi Onlus
Conditions: Brain Injuries
Interventions: Data collection
Locations: Institute for Biomedical Research and Innovation (IRIB) - National Research Council (CNR)
Countries: Italy
Enrollment: 190
Age range: 18 Years - None
Sex: ALL

Summary:
Acquired brain injury (ABI) is the leading cause of death and disability worldwide. The degree of severity varies according to a combination of numerous demographics, etiological, clinical, cognitive, behavioral, psychosocial and environmental factors, which can interfere with the effectiveness of rehabilitation interventions and, therefore, with the final outcome.

The most important goal of the modern clinic is to predict in time the progression of possible recovery after the brain injury event in order to provide more effective treatment, but the high heterogeneity and clinical variability and the unpredictability of the onset of comorbidities makes this a hard target to reach.

In recent years, artificial intelligence algorithms have been applied to more precisely define the role of critical variables that can help clinical practice to predict the final outcome. The classical approach of these algorithms provides only probabilistic values on the final outcome, without considering the typology of clinical interventions and overall complications that may appear throughout the hospitalization period.

The objective of this multicentric study is to define a new statistical approach that can describe the dynamics of individual clinical changes occuring during the inpatient intensive rehabilitation care period. The proposed approach combines a principal component analysis (PCA) for dimension reduction (capturing the maximum amount of information and reducing the dimensionality problem) and a nonlinear mathematical modeling for describing the evolution of the clinical course in terms of the resulting new PCA dimensions. By using this approach, we may determine the individual patient's temporal trajectories while examining particular clinical factors. The secondary objective of this study is to validate a new version of the Early Rehabilitation Barthel Index (ERBI), a well-known clinical scale used to measure functional changes in patients with severe acquired brain injury.

Eligibility criteria:
Inclusion Criteria:

* patients with clinical diagnosis of severe acquired brain injury of different etiology (traumatic, hemorrhagic vascular,ischemic vascular, anoxic, infectious, other etiology
* interval since the acute occurrence that led to the clinical condition of ≤3 months duration
* age of 18 years or older
* informed consent signed by family member/caregiver/supporting caregiver

Exclusion Criteria:

* Positive remote medical history of pre-existing disabling neurological or orthopedic conditions and psychiatric disorders

Outcomes:
Glasgow Outcome Scale - Extended