@article{ref1,
title="Predicting outcome of acquired brain injury by the evolution of paroxysmal sympathetic hyperactivity signs",
journal="Journal of neurotrauma",
year="2020",
author="Lucca, Lucia Francesca and De Tanti, Antonio and Cava, Francesca and Romoli, Anna Maria and Formisano, Rita and Scarponi, Federico and Estraneo, Anna and Frattini, Diana and Tonin, Paolo and Bertolino, Chiara and Salucci, Pamela and Hakiki, Bahia and D'Ippolito, Mariagrazia and Zampolini, Mauro and Masotta, Orsola and Premoselli, Silvia and Interlenghi, Matteo and Salvatore, Chrstian and Polidori, Annalisa and Cerasa, Antonio",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="In this multicenter study, we provide a systematic evaluation of the clinical variability associated with paroxysmal sympathetic hyperactivity (PSH) in patients  with acquired brain injury (ABI) to determine how these signs can impact outcomes. A  total of 156 ABI patients with a disorder of consciousness (DoOC) were admitted to  neurorehabilitation subacute units (IRU) and evaluated at baseline (T0), after 4  months from event (T1) and at discharge (T2). The outcome measure was the Glasgow  outcome scale-extended, while age, sex, etiology, Coma Recovery Scale-revised  (CRS-r), Rancho Los Amigos Scale (RLAS), early rehabilitation Barthel index (ERBI),  PSH-assessment measure (PSH-AM) scores and other clinical features were considered  as predictive factors. A machine learning (ML) approach was used to identify the  best predictive model of clinical outcomes. The etiology was predominantly vascular  (50.8%), followed by traumatic (36.2%). At admission, the prevalence of PSH was  31.3%, which decreased to 16.6% and 4.4% at T1 and T2, respectively. At T2, 2.8%  were dead, 61.1% had a full recovery of consciousness, whereas 36.1% remained in VS  or MCS. A Support Vector Machine (SVM) SVM-based ML approach provides the best model  with 82% accuracy in predicting outcomes. Analysis of variable importance shows that  the most important clinical factors influencing the outcome are the PSH-AM scores  measured at T0 and T1, together with neurological diagnosis, CRS-r and RLAS scores  measured at T0. This joint multicenter effort provides a comprehensive picture of  the clinical impact of the PSH signs in ABI patients, demonstrating its predictive  value in comparison with other well-known clinical measurements.<p /> <p>Language: en</p>",
language="en",
issn="0897-7151",
doi="10.1089/neu.2020.7302",
url="http://dx.doi.org/10.1089/neu.2020.7302"
}