The impact of COVID-19 on home, social, and productivity integration of people with chronic traumatic brain injury or stroke living in the community

Compare community integration of people with stroke or traumatic brain injury (TBI) living in the community before and during the coronavirus severe acute respiratory syndrome coronavirus 2 disease (COVID-19) when stratifying by injury: participants with stroke (G1) and with TBI (G2); by functional independence in activities of daily living: independent (G3) and dependent (G4); by age: participants younger than 54 (G5) and older than 54 (G6); and by gender: female (G7) and male (G8) participants. Prospective observational cohort study In-person follow-up visits (before COVID-19 outbreak) to a rehabilitation hospital in Spain and on-line during COVID-19. Community dwelling adults (≥18 years) with chronic stroke or TBI. Community integration questionnaire (CIQ) the total-CIQ as well as the subscale domains (ie, home-CIQ, social-CIQ, productivity CIQ) were compared before and during COVID-19 using the Wilcoxon ranked test or paired t test when appropriate reporting Cohen effect sizes (d). The functional independence measure was used to assess functional independence in activities of daily living. Two hundred four participants, 51.4% with stroke and 48.6% with TBI assessed on-line between June 2020 and April 2021 were compared to their own in-person assessments performed before COVID-19. When analyzing total-CIQ, G1 (d = −0.231), G2 (d = −0.240), G3 (d = −0.285), G5 (d = −0.276), G6 (d = −0.199), G7 (d = −0.245), and G8 (d = −0.210) significantly decreased their scores during COVID-19, meanwhile G4 was the only group with no significant differences before and during COVID-19. In productivity-CIQ, G1 (d = −0.197), G4 (d = −0.215), G6 (d = −0.300), and G8 (d = −0.210) significantly increased their scores, meanwhile no significant differences were observed in G2, G3, G5, and G7. In social-CIQ, all groups significantly decreased their scores: G1 (d = −0.348), G2 (d = −0.372), G3 (d = −0.437), G4 (d = −0.253), G5 (d = −0.394), G6 (d = −0.319), G7 (d = −0.355), and G8 (d = −0.365). In home-CIQ only G6 (d = −0.229) significantly decreased, no significant differences were observed in any of the other groups. The largest effect sizes were observed in total-CIQ for G3, in productivity-CIQ for G6, in social-CIQ for G3 and in home-CIQ for G6 (medium effect sizes). Stratifying participants by injury, functionality, age or gender allowed identifying specific CIQ subtotals where remote support may be provided addressing them

Informe preliminar sobre la prospección de la Vall del Barxell -Polop (Alcoi-Alcant)

Dins del projecte d'estudi del procés de neolitització a les comarques centromeridionals del País Valencià. es presenten els resultats preliminars obringuts en la prospecció sistemàtica deI la capçalera del riu Serpis, la Vall de Barxell-Polop (Alcoi-Alacant).Within the survey project of neolithization in the central and southern regions of the Valencian Country, we present herein the preliminary results achieved so far in the systematic prospecting at the source of the Serpis River, located in the Barxell-Polop Valley, within the municipal boundary of Alcoi, in the Alicante area.Dentro del proyecto de estudio del proceso de Neolitización en las comarcas centromeridionales del País Valenciano. se presentan los resultados preliminares obtenidos en la prospección sistemática de la cabecera del río Serpis, valle del Barxell-Polop (Alcoi. Alacant)

Modelado de Procesos de Neurorrehabilitación

La Neurorrehabilitación es un proceso clínico que se centra en el abordaje de la alteración del sistema nervioso. Existe una enorme variabilidad tanto en la tipología como en el grado de las lesiones neurológicas, lo que la convierte en un proceso extremadamente complejo de analizar y comprender. El presente trabajo se centra en el modelado de las principales actividades que se llevan a cabo en el contexto de la Neurorrehabilitación actual con el objetivo de detectar aquellos puntos en que puedan ser mejoradas, tanto a nivel organizativo como a nivel de ejecución. Por otra parte, se trata de comprenderlas en profundidad para tratar de transformarlas posteriormente en nuevas actividades automatizadas y monitorizadas que se ajusten al nuevo paradigma de rehabilitación ubicua, personalizada y basada en la evidencia

Identificación de Oportunidades de Mejora en Procesos de Neurorrehabilitación

El modelado de procesos es una técnica de gestión empresarial destinada a la mejora continua de los procesos de una organización, como base operativa y estructural de la misma. En el ámbito de la Neurorrehabilitación, crece el interés por los mapas de procesos como herramienta de comprensión, representación y análisis de los procesos clínicos. El presente trabajo se centra en la identificación de oportunidades de mejora de las actividades de rehabilitación, con el objetivo de definir nuevas estrategias de monitorización y automatización que permitan su evolución hacia el nuevo modelo de rehabilitación ubicua, personalizada y basada en la evidencia

Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury

The number and grade of injured neuroanatomic structures and the type of injury determine the degree of impairment after a brain injury event and the recovery options of the patient. However, the body of knowledge and clinical intervention guides are basically focused on functional disorder and they still do not take into account the location of injuries. The prognostic value of location information is not known in detail either. This paper proposes a feature-based detection algorithm, named Neuroanatomic-Based Detection Algorithm (NBDA), based on SURF (Speeded Up Robust Feature) to label anatomical brain structures on cortical and sub-cortical areas. Themain goal is to register injured neuroanatomic structures to generate a database containing patient?s structural impairment profile. This kind of information permits to establish a relation with functional disorders and the prognostic evolution during neurorehabilitation procedures

Toward Personalized Web-Based Cognitive Rehabilitation for Patients With Ischemic Stroke : Elo Rating Approach

Stroke is a worldwide cause of disability; 40% of stroke survivors sustain cognitive impairments, most of them following inpatient rehabilitation at specialized clinical centers. Web-based cognitive rehabilitation tasks are extensively used in clinical settings. The impact of task execution depends on the ratio between the skills of the treated patient and the challenges imposed by the task itself. Thus, treatment personalization requires a trade-off between patients' skills and task difficulties, which is still an open issue. In this study, we propose Elo ratings to support clinicians in tasks assignations and representing patients' skills to optimize rehabilitation outcomes. This study aims to stratify patients with ischemic stroke at an early stage of rehabilitation into three levels according to their Elo rating; to show the relationships between the Elo rating levels, task difficulty levels, and rehabilitation outcomes; and to determine if the Elo rating obtained at early stages of rehabilitation is a significant predictor of rehabilitation outcomes. The PlayerRatings R library was used to obtain the Elo rating for each patient. Working memory was assessed using the DIGITS subtest of the Barcelona test, and the Rey Auditory Verbal Memory Test (RAVLT) was used to assess verbal memory. Three subtests of RAVLT were used: RAVLT learning (RAVLT075), free-recall memory (RAVLT015), and recognition (RAVLT015R). Memory predictors were identified using forward stepwise selection to add covariates to the models, which were evaluated by assessing discrimination using the area under the receiver operating characteristic curve (AUC) for logistic regressions and adjusted R 2 for linear regressions. Three Elo levels (low, middle, and high) with the same number of patients (n=96) in each Elo group were obtained using the 50 initial task executions (from a total of 38,177) for N=288 adult patients consecutively admitted for inpatient rehabilitation in a clinical setting. The mid-Elo level showed the highest proportions of patients that improved in all four memory items: 56% (54/96) of them improved in DIGITS, 67% (64/96) in RAVLT075, 58% (56/96) in RAVLT015, and 53% (51/96) in RAVLT015R (P <.001). The proportions of patients from the mid-Elo level that performed tasks at difficulty levels 1, 2, and 3 were 32.1% (3997/12,449), 31.% (3997/12,449), and 36.9% (4595/12,449), respectively (P <.001), showing the highest match between skills (represented by Elo level) and task difficulties, considering the set of 38,177 task executions. Elo ratings were significant predictors in three of the four models and quasi-significant in the fourth. When predicting RAVLT075 and DIGITS at discharge, we obtained R 2 =0.54 and 0.43, respectively; meanwhile, we obtained AUC=0.73 (95% CI 0.64-0.82) and AUC=0.81 (95% CI 0.72-0.89) in RAVLT075 and DIGITS improvement predictions, respectively. Elo ratings can support clinicians in early rehabilitation stages in identifying cognitive profiles to be used for assigning task difficulty levels