Introduction: Ischemic stroke patients with mild deficits were largely excluded from pivotal trials of IV rt-PA. The balance of benefit versus risk of intravenous thrombolysis for this large, understudied patient cohort is uncertain. The PRISMS trial is underway to test the benefit of IV rt-PA for treatment of mild stroke. Objective: To characterize baseline features of the first 100 patients enrolled in this prospective cohort of exclusively mild stroke. Methods: The PRISMS trial is a Phase 3b, double-blind, 75-center, 948-subject study evaluating IV rt-PA administered within three hours of mild stroke onset to improve 90-day functional outcome (modified Rankin Scale 0 or 1). Mild stroke is defined as NIHSS ≤5 and not “clearly disabling” (i.e., inability to return to work or perform basic activities of daily living based on current deficits). Patients are randomized 1:1 to IV rt-PA 0.9 mg/kg with aspirin placebo or IV rt-PA placebo with aspirin 325 mg. Here we describe baseline characteristics, including clinical presentations by NIHSS item, of the first 100 enrolled patients. The study team remains fully blinded to patient treatment assignment and outcomes. Results: The 100th subject was enrolled on June 15, 2015. Baseline characteristics are presented in the Table. Median NIHSS was 2 (IQR 1-3). Clinical presentations of each patient by abnormal NIHSS items are shown in the Figure. Dysarthria, facial palsy, and sensory loss were the most common deficits. Conclusions: This initial 100-patient PRISMS cohort is consistent with expectations. Upon completion, the PRISMS trial will determine the benefit of IV rt-PA for mild stroke.
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.
BACKGROUND Stroke is a worldwide cause of disability, 40% of stroke survivors sustain cognitive impairments, most of them follow inpatient rehabilitation at specialized clinical centers. Web-based cognitive rehabilitation tasks are already integrated into clinical settings. The impact of a task execution depends on the ratio between the skills of the treated patient and the challenges imposed by the task itself. Thus, treatments personalization requires a trade-off between patients’ skills and tasks difficulties, which is still an open issue. In this work we propose Elo ratings to support clinicians in representing patients’ skills and supporting tasks assignations to optimize rehabilitation outcomes. OBJECTIVE i) perform a stratification of patients with ischemic stroke at early stage of rehabilitation in three levels according to their Elo rating ii) show the relationships between the Elo rating levels, tasks difficulty levels and rehabilitation outcomes iii) determine if 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 Test Barcelona and the Rey Auditory Verbal Memory Test (RAVLT) was used to assess verbal memory. The 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 characteristics curve (AUC) for logistic regressions and adjusted R2 for linear regressions. RESULTS Three Elo levels (Low, Mid and High) with the same number of patients (n=96) in each Elo group, were obtained using the 50 initial tasks executions (from a total of 38,177) for n=288 adult patients consecutively admitted for inpatient rehabilitation in a clinical setting. The highest proportion of patients that improved in all 4 memory items were from Mid Elo level: 56.7% of them improved in DIGITS, 67.1% in RAVLT075, 58.8% in RAVLT015 and 53.7% in RAVLT015R (p < 0.001). The proportion of patients from the Mid Elo level that performed tasks at difficulty levels #1, #2 and #3 were: 32.1%, 31.0% and 36.9% (p < 0.001) respectively, showing the highest match between skills (represented by Elo level) and tasks difficulties, considering the set of 38,177 tasks executions. Elo ratings were significant predictors in 3 of the 4 models and quasi-significant in the other. When predicting RAVLT075 and DIGITS at discharge we obtained R2=0.54 and R2=0.43 respectively, meanwhile in RAVLT075 and DIGITS improvement predictions we obtained AUC= 0.73, 95% CI(0.64-0.82) and AUC= 0.81 95%CI(0.72-0.89). CONCLUSIONS Elo ratings can support clinicians at early rehabilitation stages in identifying cognitive profiles that can be used to assign tasks’ difficulty levels.
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