Modeling Outcome in Patients With Acquired Brain Injuries

Официальное название

Modeling Trajectories of Functional Outcome in Patients With Severe Acquired Brain Injuries Using a Non-Linear Dynamic Evolution Approach.

Обзор

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.

Вмешательства

• Другое Data collection
  The study will involve at the time of entry into the rehabilitation setting, the collection of data related to demographic and clinical variables assessing: 1. The Level of responsiveness (Coma Recovery Scale -revised (CRS-r); 2. Cognitive functioning (Levels of Cognitive Functioning, LCF); 3. disability (Disability Rating Scale, DRS); 4. level of care needed (Early Rehabilition Barthel Index, ERBI) The Final outcome measure will be the Glasgow Outcome Scale- Extended (GOSE). It will also coll

Первичные конечные точки

• Glasgow Outcome Scale - Extended [Срок оценки: The test needs approximately 5 minutes to complete.]

Вторичные конечные точки (1)

• Early Rehabilition Barthel Index [Срок оценки: The test needs approximately 20 minutes to complete.]

Критерии участия

Критерии включения

• 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

Критерии исключения

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

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Италия · 1 центр

• Institute for Biomedical Research and Innovation (IRIB) - National Research Council (CNR) — Messina

Публикации

• Panunzi S, Lucca LF, De Tanti A, Cava F, Romoli A, Formisano R, Scarponi F, Estraneo A, Frattini D, Tonin P, Piergentilli I, Pioggia G, De Gaetano A, Cerasa A. Modeling outcome trajectories in patients with acquired brain injury using a non-linear dynamic evolution approach. Sci Rep. 2023 Apr 18;13(1):6295. doi: 10.1038/s41598-023-33560-x. PMID 37072538

Идентификаторы

NCT: NCT06162091 · CNR-IRIB-PRO-2023-007

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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