Prediction of rehabilitation induced motor recovery after stroke using a multi-dimensional and multi-modal approach.

Background: Stroke is a debilitating disease affecting millions of people worldwide. Despite the survival rate has significantly increased over the years, many stroke survivors are left with severe impairments impacting their quality of life. Rehabilitation programs have proved to be successful in improving the recovery process. However, a reliable model of sensorimotor recovery and a clear identification of predictive markers of rehabilitation-induced recovery are still needed. This article introduces the cross-modality protocols designed to investigate the rehabilitation treatment's effect in a group of stroke survivors. Methods/design: A total of 75 stroke patients, admitted at the IRCCS San Camillo rehabilitation Hospital in Venice (Italy), will be included in this study. Here, we describe the rehabilitation programs, clinical, neuropsychological, and physiological/imaging [including electroencephalography (EEG), transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI) techniques] protocols set up for this study. Blood collection for the characterization of predictive biological biomarkers will also be taken. Measures derived from data acquired will be used as candidate predictors of motor recovery. Discussion/summary: The integration of cutting-edge physiological and imaging techniques, with clinical and cognitive assessment, dose of rehabilitation and biological variables will provide a unique opportunity to define a predictive model of recovery in stroke patients. Taken together, the data acquired in this project will help to define a model of rehabilitation induced sensorimotor recovery, with the final aim of developing personalized treatments promoting the greatest chance of recovery of the compromised functions.

Cortical Thickness of Brain Areas Beyond Stroke Lesions and Sensory-Motor Recovery: A Systematic Review.

Background: The clinical outcome of patients suffering from stroke is dependent on multiple factors. The features of the lesion itself play an important role but clinical recovery is remarkably influenced by the plasticity mechanisms triggered by the stroke and occurring at a distance from the lesion. The latter translate into functional and structural changes of which cortical thickness might be easy to quantify one of the main players. However, studies on the changes of cortical thickness in brain areas beyond stroke lesion and their relationship to sensory-motor recovery are sparse. Objectives: To evaluate the effects of cerebral stroke on cortical thickness (CT) beyond the stroke lesion and its association with sensory-motor recovery. Materials and Methods: Five electronic databases (PubMed, Embase, Web of Science, Scopus and the Cochrane Library) were searched. Methodological quality of the included studies was assessed with the Newcastle-Ottawa Scale for non-randomized controlled trials and the Risk of Bias Cochrane tool for randomized controlled trials. Results: The search strategy retrieved 821 records, 12 studies were included and risk of bias assessed. In most of the included studies, cortical thinning was seen at the ipsilesional motor area (M1). Cortical thinning can occur beyond the stroke lesion, typically in regions anatomically connected because of anterograde degeneration. Nonetheless, studies also reported cortical thickening of regions of the unaffected hemisphere, likely related to compensatory plasticity. Some studies revealed a significant correlation between changes in cortical thickness of M1 or somatosensory (S1) cortical areas and motor function recovery. Discussion and Conclusions: Following a stroke, changes in cortical thickness occur both in regions directly connected to the stroke lesion and in contralateral hemisphere areas as well as in the cerebellum. The underlying mechanisms leading to these changes in cortical thickness are still to be fully understood and further research in the field is needed. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020200539; PROSPERO 2020, identifier: CRD42020200539.

Rehabilitative management of pelvic fractures: a literature-based update.

A comprehensive rehabilitation program is required after Pelvic Fracture (PF). In a PF rehabilitation setting an effective treatment and a proper management of complications is supplied by an appropriate and reliable clinical assessment. In this literature-based update, we search on MEDLINE, EMBASE, and the Cochrane Database of Systematic reviews to find articles, scientific society guidelines and practioners experiences defining the rehabilitative management of clinically PF outcomes. Based on literature evidences and expert opinions, a set of key topics was collated to generate advices and recommendations to put into daily practice. Even if there are no high-quality evidence for rehabilitative interventions after PF in terms of duration and modality of therapy, rehabilitation setting, care pathways, and long-term functional outcomes, it is strongly recommended an early multidisciplinary intervention to improve recovery from PF.

Cortical gamma-synchrony measured with magnetoencephalography is a marker of clinical status and predicts clinical outcome in stroke survivors.

BACKGROUND: The outcome of stroke survivors is difficult to anticipate. While the extent of the anatomical brain lesion is only poorly correlated with the prognosis, functional measures of cortical synchrony, brain networks and cortical plasticity seem to be good predictors of clinical recovery. In this field, gamma (>30 Hz) cortical synchrony is an ideal marker of brain function, as it plays a crucial role for the integration of information, it is an indirect marker of Glutamate/GABA balance and it directly estimates the reserve of parvalbulin-positive neurons, key players in synaptic plasticity. In this study we measured gamma synchronization driven by external auditory stimulation with magnetoencephalography and tested whether it was predictive of the clinical outcome in stroke survivors undergoing intensive rehabilitation in a tertiary rehabilitation center. MATERIAL AND METHODS: Eleven stroke survivors undergoing intensive rehabilitation were prospectively recruited. Gamma synchrony was measured non-invasively within one month from stroke onset with magnetoencephalography, both at rest and during entrainment with external 40 Hz amplitude modulated binaural sounds. Lesion location and volume were quantitatively assessed through a high-resolution anatomical MRI. Barthel index (BI) and Functional Independence Measure (FIM) scales were measured at the beginning and at the end of the admission to the rehabilitation unit. RESULTS: The spatial distribution of cortical gamma synchrony was altered, and the physiological right hemispheric dominance observed in healthy controls was attenuated or lost. Entrained gamma synchronization (but not resting state gamma synchrony) showed a very high correlation with the clinical status at both admission and discharge (both BI and FIM). Neither clinical status nor gamma synchrony showed a correlation with lesion volume. CONCLUSIONS: Cortical gamma synchrony related to auditory entrainment can be reliably measured in stroke patients. Gamma synchrony is strongly associated with the clinical outcome of stroke survivors undergoing rehabilitation.

Predicting Motor and Cognitive Improvement Through Machine Learning Algorithm in Human Subject that Underwent a Rehabilitation Treatment in the Early Stage of Stroke.

BACKGROUND: The objective of this study was to investigate, in subject with stroke, the exact role as prognostic factor of common inflammatory biomarkers and other markers in predicting motor and/or cognitive improvement after rehabilitation treatment from early stage of stroke. METHODS: In this longitudinal cohort study on stroke patients undergoing inpatient rehabilitation, data from 55 participants were analyzed. Functional and clinical data were collected after admission to the rehabilitation unit. Biochemical and hematological parameters were obtained from peripheral venous blood samples on all individuals who participated in the study within 24hours from the admission at the rehabilitative treatment. Data regarding the health status were collected at the end of rehabilitative treatment. First, a feature selection has been performed to estimate the mutual dependence between input and output variables. More specifically, the so called Mutual Information criterion has been exploited. In the second stage of the analysis, the Support Vector Machines (SVMs), a non-probabilistic binary machine learning algorithm widely used for classification and regression, has been used to predict the output of the rehabilitation process. Performances of the linear SVM regression algorithm have been evaluated considering a different number of input features (ranging from 4 to 14). The performance evaluation of the model proposed has been investigated in terms of correlation, Root Mean Square Error (RMSE) and Mean Absolute Deviation Percentage (MADP). RESULTS: Results on the test samples show a good correlation between all the predicted and measured outputs (i.e. T1 Barthel Index (BI), T1 Motor Functional Independence Measure (FIM), T1 Cognitive FIM and T1 Total FIM) ranging from 0.75 to 0.81. While the MADP is high (i.e., 83.96%) for T1 BI, the other predicted responses (i.e., T1 Motor FIM, T1 Cognitive FIM, T1 Total FIM) disclose a smaller MADP of 30%. Accordingly, the RMSE ranges from 4.28 for T1 Cognitive FIM to 22.6 for T1 BI. CONCLUSIONS: In conclusion, the authors developed a new predictive model using SVM regression starting from common inflammatory biomarkers and other ratio markers. The main efforts of our model have been accomplished in regard to the evidence that the type of stroke has not shown itself to be a critical input variable to predict the discharge data, furthermore, among the four selected indicators, Barthel at T1 is the less predictable (MADP > 80%), while it is possible to predict T1 Cognitive FIM with an MADP less than 18%.

Idarucizumab: What Should We Know?

BACKGROUND: Idarucizumab, a humanized monoclonal antibody fragment acting as a specific antidote for dabigatran, is approved for reversing the dabigatran-associated possible bleeding from critical sites or bleeding persisting despite local post-procedure haemostasis. Moreover, it can also be applied to reverse the dabigatran anticoagulant activity in emergency surgery or in other invasive procedure at high risk of bleeding. OBJECTIVE: In this study, we discuss idarucizumab in light of the available literature data by conducting extensive research in the PubMed, EMBASE and Cochrane Library on the topic, using idarucizumab, dabigatran and their combinations as Mesh terms, and focusing on high impact investigations. RESULTS: Several studies have demonstrated the capacity of idarucizumab to reverse laboratory measures of dabigatran-associated coagulopathy, however its efficacy and safety in real world patients are still not very clear because of the scarcity of available data which should be assessed with an extensive post market surveillance. CONCLUSION: The introduction of idarucizumab as dabigatran antidote in clinical practice represents a useful tool for clinicians. The possibility to rapidly restore the anticoagulation activity of dabigatran makes its use simpler and more manageable.