AUTHOR=Hakiki Bahia , Donnini Ida , Romoli Anna Maria , Draghi Francesca , Maccanti Daniela , Grippo Antonello , Scarpino Maenia , Maiorelli Antonio , Sterpu Raisa , Atzori Tiziana , Mannini Andrea , Campagnini Silvia , Bagnoli Silvia , Ingannato Assunta , Nacmias Benedetta , De Bellis Francesco , Estraneo Anna , Carli Valentina , Pasqualone Eugenia , Comanducci Angela , Navarro Jorghe , Carrozza Maria Chiara , Macchi Claudio , Cecchi Francesca TITLE=Clinical, Neurophysiological, and Genetic Predictors of Recovery in Patients With Severe Acquired Brain Injuries (PRABI): A Study Protocol for a Longitudinal Observational Study JOURNAL=Frontiers in Neurology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2022.711312 DOI=10.3389/fneur.2022.711312 ISSN=1664-2295 ABSTRACT=Background

Due to continuous advances in intensive care technology and neurosurgical procedures, the number of survivors from severe acquired brain injuries (sABIs) has increased considerably, raising several delicate ethical issues. The heterogeneity and complex nature of the neurological damage of sABIs make the detection of predictive factors of a better outcome very challenging. Identifying the profile of those patients with better prospects of recovery will facilitate clinical and family choices and allow to personalize rehabilitation. This paper describes a multicenter prospective study protocol, to investigate outcomes and baseline predictors or biomarkers of functional recovery, on a large Italian cohort of sABI survivors undergoing postacute rehabilitation.

Methods

All patients with a diagnosis of sABI admitted to four intensive rehabilitation units (IRUs) within 4 months from the acute event, aged above 18, and providing informed consent, will be enrolled. No additional exclusion criteria will be considered. Measures will be taken at admission (T0), at three (T1) and 6 months (T2) from T0, and follow-up at 12 and 24 months from onset, including clinical and functional data, neurophysiological results, and analysis of neurogenetic biomarkers.

Statistics

Advanced machine learning algorithms will be cross validated to achieve data-driven prediction models. To assess the clinical applicability of the solutions obtained, the prediction of recovery milestones will be compared to the evaluation of a multiprofessional, interdisciplinary rehabilitation team, performed within 2 weeks from admission.

Discussion

Identifying the profiles of patients with a favorable prognosis would allow customization of rehabilitation strategies, to provide accurate information to the caregivers and, possibly, to optimize rehabilitation outcomes.

Conclusions

The application and validation of machine learning algorithms on a comprehensive pool of clinical, genetic, and neurophysiological data can pave the way toward the implementation of tools in support of the clinical prognosis for the rehabilitation pathways of patients after sABI.