Predictors of social risk for post-ischemic stroke reintegration.

After stroke rehabilitation, patients need to reintegrate back into their daily life, workplace and society. Reintegration involves complex processes depending on age, sex, stroke severity, cognitive, physical, as well as socioeconomic factors that impact long-term outcomes post-stroke. Moreover, post-stroke quality of life can be impacted by social risks of inadequate family, social, economic, housing and other supports needed by the patients. Social risks and barriers to successful reintegration are poorly understood yet critical for informing clinical or social interventions. Therefore, the aim of this work is to predict social risk at rehabilitation discharge using sociodemographic and clinical variables at rehabilitation admission and identify factors that contribute to this risk. A Gradient Boosting modelling methodology based on decision trees was applied to a Catalan 217-patient cohort of mostly young (mean age 52.7), male (66.4%), ischemic stroke survivors. The modelling task was to predict an individual's social risk upon discharge from rehabilitation based on 16 different demographic, diagnostic and social risk variables (family support, social support, economic status, cohabitation and home accessibility at admission). To correct for imbalance in patient sample numbers with high and low-risk levels (prediction target), five different datasets were prepared by varying the data subsampling methodology. For each of the five datasets a prediction model was trained and the analysis involves a comparison across these models. The training and validation results indicated that the models corrected for prediction target imbalance have similarly good performance (AUC 0.831-0.843) and validation (AUC 0.881 - 0.909). Furthermore, predictor variable importance ranked social support and economic status as the most important variables with the greatest contribution to social risk prediction, however, sex and age had a lesser, but still important, contribution. Due to the complex and multifactorial nature of social risk, factors in combination, including social support and economic status, drive social risk for individuals.

Pressure ulcers acquired during inpatient rehabilitation after spinal cord injury, characterization and predictors: A 15-years' experience.

BACKGROUND: Most studies focus on the risk factors associated with the development of pressure ulcers (PUs) during acute phase or community care for individuals with spinal cord injury (SCI). OBJECTIVES: This study aimed to i) compare clinical and demographic characteristics of inpatients after SCI with PUs acquired during rehabilitation vs inpatients without PUs and ii) evaluate an existing PU risk assessment tool iii) identify first PU predictors. METHODS: Individuals (n = 1,135) admitted between 2008 and 2022 to a rehabilitation institution within 60 days after SCI were included. Admission Functional Independence Measure (FIM), American Spinal Injury Association Impairment Scale (AIS) and mEntal state, Mobility, Incontinence, Nutrition, Activity (EMINA) were assessed. Kaplan-Meier curves and Cox proportional hazards models were fitted. RESULTS: Overall incidence of PUs was 8.9%. Of these, 40.6% occurred in the first 30 days, 47.5% were sacral, 66.3% were Stage II. Patients with PUs were older, mostly with traumatic injuries (67.3%), AIS A (54.5%), lower FIM motor (mFIM) score and mechanical ventilation. We identified specific mFIM items to increase EMINA specificity. Adjusted Cox model yielded sex (male), age at injury, AIS grade, mFIM and diabetes as PUs predictors (C-Index = 0.749). CONCLUSION: Inpatients can benefit from combined assessments (EMINA + mFIM) and clinical features scarcely addressed in previous studies to prevent PUs.

Return to work within a year after first stroke: blue and white collar workers comparison, predictors and causal mediation assessed during inpatient rehabilitation.

BACKGROUND: Most research focuses around impairments in body function and structure, with relatively only a small number exploring their social impact. OBJECTIVES: 1) compare characteristics for individuals who before stroke were blue collar vs. white collar workers 2) identify clinical, functional, and job-related factors associated with return to work within 1 year after discharge 3) identify specific ADL individual items (assessed at rehabilitation discharge) as return to work predictors and 4) identify return to work causal mediators. METHODS: Retrospective observational cohort study, analyzing adult patients with stroke admitted to rehabilitation between 2007 and 2021, including baseline Barthel Index (BI) and return to work assessments between 2008 and 2022. Kaplan-Meier survival curves and Cox proportional hazards were applied. Causal mediation analyses using 1000-bootstrapped simulations were performed. RESULTS: A total of 802 individuals were included (14.6% returned to work), 53.6% blue-collar and 46.4% white-collar. Blue-collar workers showed significantly higher proportion of ischemic stroke, diabetes, dyslipidemia, and hypertension.Individuals not returning to work presented a higher proportion of blue collar, dominant side affected, aphasia, lower BI scores, and larger length of stay (LOS). Multivariable Cox proportional hazards identified age at injury, aphasia, hypertension, and total discharge BI score (C-Index = 0.74). Univariable Cox models identified three independent BI items at all levels of independence: bathing (C-Index = 0.58), grooming (C-Index = 0.56) and feeding (C-Index = 0.59). BI efficiency (gain/LOS) was a causal mediator. CONCLUSION: Blue collar workers showed higher proportion of risk factors and comorbidities. Novel factors, predictors, and a return to work mediator were identified.

Effectiveness and efficiency of telerehabilitation on functionality after spinal cord injury: A matched case-control study.

BACKGROUND: Telerehabilitation in spinal cord injury (teleSCI) is a growing field that can improve access to care and health outcomes in patients with spinal cord injury (SCI). The clinical effectiveness of teleSCI is not known. OBJECTIVES: To compare independence in activities of daily living and mobility capacity in patients following teleSCI and matched controls undergoing traditional rehabilitation. DESIGN: Matched case-control study. SETTING: TeleSCI occurring in home setting (cases) versus traditional rehabilitation on inpatient unit (controls). PARTICIPANTS: Forty-two consecutive patients with SCI followed with teleSCI were compared to 42 historical rehabilitation inpatients (controls) matched for age, time since injury to rehabilitation admission, level of injury (paraplegia/tetraplegia), complete or incomplete injury, and etiology (traumatic/nontraumatic). The teleSCI group (n = 42) was also compared to the complete cohort of historical controls (n = 613). INTERVENTIONS: The teleSCI group followed home-based telerehabilitation (3.5 h/day, 5 days/week, 67 days average duration) and historical controls followed in-person rehabilitation. MAIN OUTCOME MEASURE(S): The Functional Independence Measure (FIM), the Spinal Cord Independence Measure (SCIM) and the Walking Index for Spinal Cord Injury (WISCI). We formally compared gains, efficiency and effectiveness. International Standards for Neurological Classification of Spinal Cord Injury and the American Spinal Injury Association Impairment Scale (AIS) were used. RESULTS: The teleSCI group (57.1% nontraumatic, 71.4% paraplegia, 73.8% incomplete, 52.4% AIS grade D) showed no significant differences compared with historical controls in AIS grades, neurological levels, duration, gains, efficiency and effectiveness in FIM, SCIM, or WISCI, although the teleSCI cohort had significantly higher admission FIM scores compared with the complete cohort of historical controls. CONCLUSIONS: TeleSCI may provide similar improvements in mobility and functional outcomes as traditional rehabilitation in medically stable patients (predominantly with paraplegia and motor incomplete SCI) when provided with appropriate support and equipment.

Tele-rehabilitation on independence in activities of daily living after stroke: A Matched Case-Control Study.

OBJECTIVES: To compare independence in activities of daily living (ADLs) in post-acute patients with stroke following tele-rehabilitation and matched in-person controls. MATERIALS AND METHODS: Matched case-control study. A total of 35 consecutive patients with stroke who followed tele-rehabilitation were compared to 35 historical in-person patients (controls) matched for age, functional independence at admission and time since injury to rehabilitation admission (<60 days). The tele-rehabilitation group was also compared to the complete cohort of historical controls (n=990). Independence in ADLs was assessed using the Functional Independence Measure (FIM) and the Barthel Index (BI). We formally compared FIM and BI gains calculated as discharge score - admission scores, efficiency measured as gains / length of stay and effectiveness defined as (discharge score-admission score)/ (maximum score-admission score). We analyzed the minimal clinically important difference (MCID) for FIM and BI. RESULTS: The groups showed no significant differences in type of stroke (ischemic or hemorrhagic), location, severity, age at injury, length of stay, body mass index, diabetes, dyslipidemia, hypertension, aphasia, neglect, affected side of the body, dominance or educational level. The groups showed no significant differences in gains, efficiency nor effectiveness either using FIM or Barthel Index. We identified significant differences in two specific BI items (feeding and transfer) in favor of the in-person group. No differences were observed in the proportion of patients who achieved MCID. CONCLUSIONS: No significant differences were seen between total ADL scores for tele-rehabilitation and in-person rehabilitation. Future research studies should analyze a combined rehabilitation approach that utilizes both models.

Inpatient Rehabilitation Falls: Comparing Patients With Traumatic Brain Injury Versus Patients With Stroke.

BACKGROUND: Cognitively impaired neurological rehabilitation inpatients are at an increased risk for falls; yet, little is known regarding fall risk of different groups, such as stroke versus traumatic brain injury. OBJECTIVES: To determine if rehabilitation patients' fall characteristics differ for patients with stroke versus patients with traumatic brain injury. METHODS: This retrospective observational cohort study evaluates inpatients with stroke or traumatic brain injury admitted to a rehabilitation center in Barcelona, Spain, between 2005 and 2021. We assessed independence in daily activities with the Functional Independence Measure. We compared fallen versus nonfallen patients' features and examined the association between time to first fall and risk using Cox proportional hazards models. RESULTS: A total of 1,269 fall events were experienced by 898 different patients with traumatic brain injury ( n = 313; 34.9%) and stroke ( n = 585; 65.1%). A higher proportion of falls for patients with stroke occurred while performing rehabilitation activities (20.2%-9.8%), whereas falls were significantly higher for patients with traumatic brain injury during the night shift. Fall timing revealed completely different behaviors (stroke vs. traumatic brain injury), for example, an absolute peak at 6 a.m. due to young male traumatic patients. Nonfallen patients ( n = 1,363; 78.2%) were younger, with higher independence in daily activities scores, and having a larger time since injury to admission; all three were significant fall predictors. CONCLUSIONS: Patients with traumatic brain injury and stroke showed different fall behaviors. Knowledge of fall patterns and characteristics in the inpatient rehabilitation setting can help design management protocols to mitigate their risk.

Predicting models for arm impairment: External validation of the Scandinavian models and identification of new predictors in post-acute stroke settings.

BACKGROUND: Post-stroke arm impairment at rehabilitation admission as predictor of discharge arm impairment was consistently reported as extremely useful. Several models for acute prediction exist (e.g. the Scandinavian), though lacking external validation and larger time-window admission assessments. OBJECTIVES: (1) use the 33 Fugl-Meyer Assessment-Upper Extremity (FMA-UE) individual items to predict total FMA-UE score at discharge of patients with ischemic stroke admitted to rehabilitation within 90 days post-injury, (2) use eight individual items (seven from the Scandinavian study plus the top predictor item from objective 1) to predict mild impairment (FMA-UE≥48) at discharge and (3) adjust the top three models from objective 2 with known confounders. METHODS: This was an observational study including 287 patients (from eight settings) admitted to rehabilitation (2009-2020). We applied regression models to candidate predictors, reporting adjusted R2, odds ratios and ROC-AUC using 10-fold cross-validation. RESULTS: We achieved good predictive power for the eight item-level models (AUC: 0.70-0.82) and for the three adjusted models (AUC: 0.85-0.88). We identified finger mass flexion as new item-level top predictor (AUC:0.88) and time to admission (OR = 0.9(0.9;1.0)) as only common significant confounder. CONCLUSION: Scandinavian item-level predictors are valid in a different context, finger mass flexion outperformed known predictors, days-to-admission predict discharge mild arm impairment.

Long-term trajectories of community integration: identification, characterization, and prediction using inpatient rehabilitation variables.

BACKGROUND: Community integration (CI) is often regarded as the foundation of rehabilitation endeavors after stroke; nevertheless, few studies have investigated the relationship between inpatient rehabilitation (clinical and demographic) variables and long-term CI. OBJECTIVES: To identify novel classes of patients having similar temporal patterns in CI and relate them to baseline features. METHODS: Retrospective observational cohort study analyzing (n = 287) adult patients with stroke admitted to rehabilitation between 2003 and 2018, including baseline Functional Independence Measure (FIM) at discharge, follow-ups (m = 1264) of Community Integration Questionnaire (CIQ) between 2006 and 2022. Growth mixture models (GMMs) were fitted to identify CI trajectories, and baseline predictors were identified using multivariate logistic regression (reporting AUC) with 10-fold cross validation. RESULTS: Each patient was assessed at 2.7 (2.2-3.7), 4.4 (3.7-5.6), and 6.2 (5.4-7.4) years after injury, 66% had a fourth assessment at 7.9 (6.8-8.9) years. GMM identified three classes of trajectories.Lowest CI (n=105, 36.6%): The lowest mean total CIQ; highest proportion of dysphagia (47.6%) and aphasia (46.7%), oldest at injury, largest length of stay (LOS), largest time to admission, and lowest FIM.Highest CI (n=63, 21.9%): The highest mean total CIQ, youngest, shortest LOS, highest education (27% university) highest FIM, and Intermediate CI (n=119, 41.5%): Intermediate mean total CIQ and FIM scores. Age at injury OR: 0.89 (0.85-0.93), FIM OR: 1.04 (1.02-1.07), hypertension OR: 2.86 (1.25-6.87), LOS OR: 0.98 (0.97-0.99), and high education OR: 3.05 (1.22-7.65) predicted highest CI, and AUC was 0.84 (0.76-0.93). CONCLUSION: Novel clinical (e.g. hypertension) and demographic (e.g. education) variables characterized and predicted long-term CI trajectories.

Long-term prediction of functional independence using adjusted and unadjusted single items of the functional independence measure (FIM) at discharge from rehabilitation.

CONTEXT: Being able to survive in the long-term independently is of concern to patients with spinal cord injury (SCI), their relatives, and to those providing or planning health care, especially at rehabilitation discharge. Most previous studies have attempted to predict functional dependency in activities of daily living within one year after injury. OBJECTIVES: (1) build 18 different predictive models, each model using one FIM (Functional Independence Measure) item, assessed at discharge, as independent predictor of total FIM score at chronic phase (3-6 years post-injury) (2) build three different predictive models, using in each model an item from a different FIM domain with the highest predictive power obtained in objective (1) to predict "good" functional independence at chronic phase and (3) adjust the 3 models from objective (2) with known confounding factors. METHODS: This observational study included 461 patients admitted to rehabilitation between 2009 and 2019. We applied regression models to predict total FIM score and "good" functional independence (FIM motor score ≥ 65) reporting adjusted R2, odds ratios, ROC-AUC (95% CI) tested using 10-fold cross-validation. RESULTS: The top three predictors, each from a different FIM domain, were Toilet (adjusted R2 = 0.53, Transfers domain), Toileting (adjusted R2 = 0.46, Self-care domain), and Bowel (adjusted R2 = 0.35, Sphincter control domain). These three items were also predictors of "good" functional independence (AUC: 0.84-0.87) and their predictive power increased (AUC: 0.88-0.93) when adjusted by age, paraplegia, time since injury, and length of stay. CONCLUSIONS: Discharge FIM items accurately predict long-term functional independence.

Falls During Inpatient Rehabilitation After Spinal Cord Injury: Characterization, Clock-Hour Visualization, and Time to Event Predictors.

OBJECTIVES: To (1) determine fall characteristics (eg, cause, location, witnesses) of inpatients with spinal cord injury (SCI) and whether they were different for ambulatory persons vs wheelchair users; (2) visualize the total number of daily falls per clock-hour for different inpatients' features (eg, cause of injury, age); (3) compare clinical and demographic characteristics of inpatients who experienced a first fall event vs inpatients who did not experience such event; and (4) identify first fall event predictors. DESIGN: Retrospective observational cohort study. SETTING: Institution for inpatient neurologic rehabilitation. PARTICIPANTS: Persons with SCI (N=1294) admitted to a rehabilitation facility between 2005 and 2022. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Functional independence measure (FIM), Hospital Anxiety and Depression Scale (HADS), American Spinal Injury Association Impairment Scale (AIS), and Spinal Cord Independence Measure (SCIM) at admission. Kaplan-Meier survival curves and Cox proportional hazards models were used. RESULTS: A total of 502 fall events were experienced by 369 ambulatory inpatients (19.8%) and wheelchair users (80.2%) in 63.9% of cases being alone, with cause, situation, and location significantly different in both groups. Clock-hour visualizations revealed an absolute peak at 12 AM (complete or incomplete injuries, with paraplegia or tetraplegia) but a relative peak at 9 AM mainly including incomplete patients with paraplegia. Of the (n=1294) included patients, 16.8% experienced at least 1 fall. Fallen patients reported higher levels of HADS depression, lower total SCIM, and longer time since injury to admission, with no differences in age, sex, educational level, FIM (quasi-significant), and AIS grade. Multivariable Cox proportional hazards identified time since injury to admission and AIS grade D as significant predictors of first fall event. CONCLUSIONS: Falls identification, characterization, and clock-hour visualization can support decisions for mitigation strategies specifically addressed to inpatients with SCI. Fall predictors were identified as a first step for future research.

Understanding and Predicting Cognitive Improvement of Young Adults in Ischemic Stroke Rehabilitation Therapy.

Accurate early predictions of a patient's likely cognitive improvement as a result of a stroke rehabilitation programme can assist clinicians in assembling more effective therapeutic programs. In addition, sufficient levels of explainability, which can justify these predictions, are a crucial requirement, as reported by clinicians. This article presents a machine learning (ML) prediction model targeting cognitive improvement after therapy for stroke surviving patients. The prediction model relies on electronic health records from 201 ischemic stroke surviving patients containing demographic information, cognitive assessments at admission from 24 different standardized neuropsychology tests (e.g., TMT, WAIS-III, Stroop, RAVLT, etc.), and therapy information collected during rehabilitation (72,002 entries collected between March 2007 and September 2019). The study population covered young-adult patients with a mean age of 49.51 years and only 4.47% above 65 years of age at the stroke event (no age filter applied). Twenty different classification algorithms (from Python's Scikit-learn library) are trained and evaluated, varying their hyper-parameters and the number of features received as input. Best-performing models reported Recall scores around 0.7 and F1 scores of 0.6, showing the model's ability to identify patients with poor cognitive improvement. The study includes a detailed feature importance report that helps interpret the model's inner decision workings and exposes the most influential factors in the cognitive improvement prediction. The study showed that certain therapy variables (e.g., the proportion of memory and orientation executed tasks) had an important influence on the final prediction of the cognitive improvement of patients at individual and population levels. This type of evidence can serve clinicians in adjusting the therapeutic settings (e.g., type and load of therapy activities) and selecting the one that maximizes cognitive improvement.

Clinical Prediction Rule Validation for Ambulation Outcome After Traumatic Spinal Cord Injury in a Spanish Population.

BACKGROUND: Predicting the ability to walk after traumatic spinal cord injury is of utmost importance in the clinical setting. Nevertheless, only a small fraction of predictive models are evaluated on their performance by other authors using external data. The Dutch Clinical Prediction Rule for long-term walking ability was developed and validated using neurological assessments performed within 15 days postinjury. However, in reality, this assessment is most often performed between 11 and 55 days. When considering a longer time from injury to neurological assessments, the Dutch Clinical Prediction Rule has only been externally validated for patients after non-traumatic spinal cord injury. OBJECTIVE: We aimed to validate the Dutch Clinical Prediction Rule with neurological assessment performed within 3-90 days after traumatic spinal cord injury, using (a) the Dutch Clinical Prediction Rule logistic regression coefficients (Equation 1); (b) the Dutch Clinical Prediction Rule weighted coefficients (Equation 2); and (c) the reestimated (using a Spanish population) weighted coefficients (Equation 3). METHODS: We conducted a retrospective (STROBE-compliant) study involving 298 adults with traumatic spinal cord injury admitted to a hospital between 2010 and 2019 in Spain. The Spinal Cord Independence Measure item-12 was used for walking assessment. RESULTS: Using Equation 1, the model yielded 86.2% overall classification accuracy, 94.5% sensitivity, and 83.4% specificity (area under the curve [AUC] = 0.939, 95% confidence interval [CI]: 0.915-0.965; p < .001).Using Equation 2 yielded 86.2% overall classification accuracy, 93.2% sensitivity, and 83.9% specificity (AUC = 0.9392, 95% CI: 0.914-0.964; p < .001).Using Equation 3 yielded 86.9% overall classification accuracy, 68.9% sensitivity, and 92.8% specificity (AUC = 0.939, 95% CI: 0.914-0.964; p < .001). CONCLUSIONS: This study validates the Dutch Clinical Prediction Rule in a Spanish traumatic spinal cord injury population with assessments performed up to 90 days postinjury with similar performance, using the original coefficients and including a reestimation of the coefficients.

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

ABSTRACT: 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 studyIn-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.

Long-term trajectories of motor functional independence after ischemic stroke in young adults: Identification and characterization using inpatient baseline assessments.

BACKGROUND: Stroke is a major worldwide cause of serious long-term disability. Most previous studies addressing functional independence included only inpatients with limited follow-up. OBJECTIVE: To identify novel classes of patients having similar temporal patterns in motor functional independence and relate them to baseline clinical features. METHODS: Retrospective observational cohort study, data were obtained for n = 428 adult patients with ischemic stroke admitted to rehabilitation (March 2005-March 2020), including baseline clinical features and follow-ups of motor Functional Independence Measure (mFIM) categorized as poor, fair or good. Growth mixture models (GMMs) were fitted to identify classes of patients with similar mFIM trajectories. RESULTS: GMM identified three classes of trajectories (1,664 mFIM assessments):C1 (11.2 %), 97.9% having poor admission mFIM, at 4.93 years 61.1% still poor, with the largest percentage of hypertension, neglect, dysphagia, diabetes and dyslipidemia of all three classes.C2 (23.1%), 99% had poor admission mFIM, 25% poor discharge mFIM, the largest percentage of aphasia and greatest mFIM gain, at 4.93 years only 6.2% still poor.C3 (65.7%) the youngest, lowest NIHSS, 37.7% poor admission mFIM, 73% good discharge mFIM, only 4.6% poor discharge mFIM, 90% good at 4.93 years. CONCLUSIONS: GMM identified novel motor functional classes characterized by baseline features.

The impact of COVID-19 on community integration, quality of life, depression and anxiety in people with chronic spinal cord injury.

CONTEXT/OBJECTIVE: Compare community integration, quality of life, anxiety and depression of people with chronic spinal cord injury (SCI) living in the community before the outbreak of coronavirus SARS-CoV-2 disease (COVID-19) and during it. DESIGN: Prospective observational cohort study. SETTING: In-person follow-up visits (before COVID-19 outbreak) to a rehabilitation hospital in Spain and on-line during COVID-19. PARTICIPANTS: Community dwelling adults (≥ 18 years) with chronic SCI. OUTCOME MEASURES: Hospital Anxiety and Depression Scale (HADS), Community Integration Questionnaire (CIQ) and World Health Organization Quality of Life (WHOQOL-BREF) were compared using the Wilcoxon ranked test or paired t-test when appropriate. RESULTS: One hundred and seventy five people with SCI assessed on-line between June 2020 and November 2020 were compared to their own assessments before COVID-19. Participants reported significantly decreased Social Integration during COVID-19 compared to pre-pandemic scores (P = 0.037), with a small effect size (d = -0.15). Depression (measured using HADS) was significantly higher than before COVID-19 (P < 0.001) with a moderate effect size (d = -0.29). No significant differences were found in any of the 4 WHOQOL-BREF dimensions (Physical, Psychological, Social and Environmental).Nevertheless, when all participants were stratified in two groups according to their age at on-line assessment, the younger group (19-54 years, N = 85) scored lower during COVID-19 than before, in WHOQOL-BREF Physical (P = 0.004), (d = -0.30) and Psychological dimensions (P = 0.007) (d = -0.29). The older group (55-88 years, N = 0) reported no significant differences in any dimension. CONCLUSIONS: COVID-19 impacted HADS' depression and CIQ's social integration. Participants younger than 55 years were impacted in WHOQOL-BREF's physical and psychological dimensions, meanwhile participants older than 55, were not.

The impact of coronavirus disease 2019 on emotional and behavioral stress of informal family caregivers of individuals with stroke or traumatic brain injury at chronic phase living in a Mediterranean setting.

INTRODUCTION: Even in nonpandemic times, persons with disabilities experience emotional and behavioral disturbances which are distressing for them and for their close persons. We aimed at comparing the levels of stress in emotional and behavioral aspects, before and during coronavirus disease 2019 (COVID-19), as reported by informal family caregivers of individuals with chronic traumatic brain injury (TBI) or stroke living in the community, considering two different stratifications of the recipients of care (cause and injury severity). METHODS: We conducted a STROBE-compliant prospective observational study analyzing informal caregivers of individuals with stroke (IC-STROKE) or traumatic brain injury (IC-TBI). IC-STROKE and IC-TBI were assessed in-person before and during COVID-19 online, using the Head Injury Behavior Scale (HIBS). The HIBS comprises behavioral and emotional subtotals (10 items each) and a total-HIBS. Comparisons were performed using the McNemar's test, Wilcoxon signed-rank test or t-test. Recipients of care were stratified according to their injury severity using the National Institutes of Health Stroke Scale (NIHSS) and the Glasgow Coma Scale (GCS). RESULTS: One hundred twenty-two informal caregivers (62.3% IC-STROKE and 37.7% IC-TBI) were assessed online between June 2020 and April 2021 and compared to their own assessments performed in-person 1.74 ± 0.88 years before the COVID-19 lockdown. IC-STROKE significantly increased their level of stress during COVID-19 in five emotional items (impatience, frequent complaining, often disputes topics, mood change and overly sensitive) and in one behavioral item (overly dependent). IC-TBI stress level only increased in one behavioral item (impulsivity). By injury severity, (i) mild (14.7%) showed no significant differences in emotional and behavioral either total-HIBS (ii) moderate (28.7%) showed significant emotional differences in two items (frequent complaining and mood change) and (iii) severe (56.6%) showed significant differences in emotional (often disputes topics) and behavioral (impulsivity) items. CONCLUSIONS: Our results suggest specific items in which informal caregivers could be supported considering cause or severity of the recipients of care.

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

BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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 R2 for linear regressions. RESULTS: 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 R2=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. CONCLUSIONS: Elo ratings can support clinicians in early rehabilitation stages in identifying cognitive profiles to be used for assigning task difficulty levels.

Predictive models for independence after stroke rehabilitation: Maugeri external validation and development of a new model.

BACKGROUND: Many efforts have been devoted to identify predictors of functional outcomes after stroke rehabilitation. Though extensively recommended, there are very few external validation studies. OBJECTIVE: To externally validate two predictive models (Maugeri model 1 and model 2) and to develop a new model (model 3) that estimate the probability of achieving improvement in physical functioning (primary outcome) and a level of independence requiring no more than supervision (secondary outcome) after stroke rehabilitation. METHODS: We used multivariable logistic regression analysis for validation and development. Main outcome measures were: Functional Independence Measure (FIM) (primary outcome), Functional Independence Staging (FIS) (secondary outcome) and Minimal Clinically Important Difference (MCID). RESULTS: Patients with stroke admitted to a rehabilitation center from 2006 to 2019 were retrospectively studied (N = 710). Validation of Maugeri models confirmed very good discrimination: for model 1 AUC = 0.873 (0.833-0.915) and model 2 AUC = 0.803 (0.749-0.857). The Hosmer-Lemeshow χ2 was 6.07(p = 0.63) and 8.91(p = 0.34) respectively. Model 3 yielded an AUC = 0.894 (0.857-0.929) (primary outcome) and an AUC = 0.769 (0.714-0.825) (MCID). CONCLUSIONS: Discriminative power of both Maugeri models was externally confirmed (in a 20 years younger population) and a new model (incorporating aphasia) was developed outperforming Maugeri models in primary outcome and MCID.

Neuropsychological Assessments of Patients With Acquired Brain Injury: A Cluster Analysis Approach to Address Heterogeneity in Web-Based Cognitive Rehabilitation.

We aimed to (1) apply cluster analysis techniques to mixed-type data (numerical and categorical) from baseline neuropsychological standard and widely used assessments of patients with acquired brain injury (ABI) (2) apply state-of-the-art cluster validity indexes (CVI) to assess their internal validity (3) study their external validity considering relevant aspects of ABI rehabilitation such as functional independence measure (FIM) in activities of daily life assessment (4) characterize the identified profiles by using demographic and clinically relevant variables and (5) extend the external validation of the obtained clusters to all cognitive rehabilitation tasks executed by the participants in a web-based cognitive rehabilitation platform (GNPT). We analyzed 1,107 patients with ABI, 58.1% traumatic brain injury (TBI), 21.8% stroke and 20.1% other ABIs (e.g., brain tumors, anoxia, infections) that have undergone inpatient GNPT cognitive rehabilitation from September 2008 to January 2021. We applied the k-prototypes algorithm from the clustMixType R package. We optimized seven CVIs and applied bootstrap resampling to assess clusters stability (fpc R package). Clusters' post hoc comparisons were performed using the Wilcoxon ranked test, paired t-test or Chi-square test when appropriate. We identified a three-clusters optimal solution, with strong stability (>0.85) and structure (e.g., Silhouette > 0.60, Gamma > 0.83), characterized by distinctive level of performance in all neuropsychological tests, demographics, FIM, response to GNPT tasks and tests normative data (e.g., the 3 min cut-off in Trail Making Test-B). Cluster 1 was characterized by severe cognitive impairment (N = 254, 22.9%) the mean age was 47 years, 68.5% patients with TBI and 22% with stroke. Cluster 2 was characterized by mild cognitive impairment (N = 376, 33.9%) mean age 54 years, 53.5% patients with stroke and 27% other ABI. Cluster 3, moderate cognitive impairment (N = 477, 43.2%) mean age 33 years, 83% patients with TBI and 14% other ABI. Post hoc analysis on cognitive FIM supported a significant higher performance of Cluster 2 vs. Cluster 3 (p < 0.001), Cluster 2 vs. Cluster 1 (p < 0.001) and Cluster 3 vs. Cluster 1 (p < 0.001). All patients executed 286,798 GNPT tasks, with performance significantly higher in Cluster 2 and 3 vs. Cluster 1 (p < 0.001).

Relationships Between Functionality, Depression, and Anxiety With Community Integration and Quality of Life in Chronic Traumatic Spinal Cord Injury.

OBJECTIVES: The aims of the study were (1) to identify relationships between functional and psychological aspects with community integration and quality of life assessments in people with chronic traumatic spinal cord injury and (2) to analyze clinical and demographic predictors of quality of life dimensions. DESIGN: This is an observational cohort study, and correlation coefficients were calculated between the Functional Independence Measure, the Hospital Anxiety and Depression Scale, the Community Integration Questionnaire, and the World Health Organization Quality of Life-BREF dimensions (physical [D1], psychological [D2], social [D3], and environmental [D4]). Quality of life predictors were identified using multiple linear regression analyses. RESULTS: Nine hundred seventy-five people with traumatic spinal cord injury assessed since 2007-2020 were included. The Community Integration Questionnaire home integration correlated strongly with the Functional Independence Measure self-care (r = 0.74) and transfers (r = 0.62) for participants with tetraplegia. The specific Hospital Anxiety and Depression Scale items (known as the anhedonia subscale) correlated strongly with D1 (r = -0.65), D2 (r = -0.69), D3 (r = -0.53), and D4 (r = -0.51) for participants with paraplegia and D1 (r = -0.53), D2 (r = -0.61), D3 (r = -0.47), and D4 (r = -0.53) for participants with tetraplegia. The Hospital Anxiety and Depression Scale-depression was the most relevant predictor of D1 (ß = -0.61) and D2 (ß = -0.76). CONCLUSIONS: The Functional Independence Measure transfers and self-care were strongly associated with the Community Integration Questionnaire home integration (in participants with tetraplegia). Anhedonia was strongly related to all four World Health Organization Quality of Life-BREF Scale dimensions, being the Hospital Anxiety and Depression Scale-depression the most relevant predictor of D1 and D2. TO CLAIM CME CREDITS: Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME. CME OBJECTIVES: Upon completion of this article, the reader should be able to (1) Determine the associations between functional and psychological measures with community integration domains and quality of life from a multidimensional perspective (physical, psychological, social, and environmental) in persons with chronic traumatic paraplegia or tetraplegia living in the community; (2) Identify long-term clinical and demographic predictors of specific quality of life dimensions (e.g., physical and psychological) in persons with paraplegia or tetraplegia living in the community; and (3) Illustrate the strength of the identified associations and the impact of the quality of life predictors to suggest possible specific aspects to be addressed by professionals in clinical practice. LEVEL: Advanced. ACCREDITATION: The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.