For phase III RCTs, sample heterogeneity is useful for both generalizability of findings and providing insight into treatment effects for specific subgroups. Prior studies in stroke rehabilitation have rarely explored differences in intervention effects between racial and ethnic subgroups across participating sites. We examined participant characteristics across centers, with the hypothesis that strategic use of a multi-center structure across 3 distinct urban geographical areas (Atlanta, GA, Los Angeles, CA and Washington, DC) would generate a sample diverse enough to explore differences in treatment effects by racial and ethnic subgroups Methods: The ICARE Stroke Initiative is a randomized multi-center clinical trial designed to compare the effectiveness of the Accelerated Skill Acquisition Program (ASAP) to an equivalent dose of usual and customary outpatient occupational therapy (DEUCC) and a monitoring only usual therapy group (UCC). Demographics, stroke characteristics and cognitive outcomes collected at baseline for randomized participants (N = 361) were compared across the 3 centers using ANOVA or χ2 tests for continuous and categorical outcomes, respectively. Results: We found significant differences in race and ethnicity (p<0.001); the highest proportion of African-Americans came from the Atlanta and DC centers, and the highest proportion of Hispanic/Latinos came from the Los Angeles center. Additional unanticipated differences between centers in baseline characteristics include: age, referral source, stroke location, stroke severity as measured by the NIH Stroke Scale, Short Blessed Memory Test, DKEF’s verbal fluency sub-score of category switching, and pre-randomization hours of outpatient occupational therapy (p<0.05). Conclusions: ICARE’s strategic center selection resulted in a diverse and robust dataset, allowing for post hoc exploration of treatment effect differences by subgroup and for the intention-to-treat analysis, determination of generalizability of treatment effects across a racially and ethnically diverse population.
Background Wrist-worn accelerometry provides objective monitoring of upper-extremity functional use, such as reaching tasks, but also detects nonfunctional movements, leading to ambiguity in monitoring results. Objective Compare machine learning algorithms with standard methods (counts ratio) to improve accuracy in detecting functional activity. Methods Healthy controls and individuals with stroke performed unstructured tasks in a simulated community environment (Test duration = 26 ± 8 minutes) while accelerometry and video were synchronously recorded. Human annotators scored each frame of the video as being functional or nonfunctional activity, providing ground truth. Several machine learning algorithms were developed to separate functional from nonfunctional activity in the accelerometer data. We also calculated the counts ratio, which uses a thresholding scheme to calculate the duration of activity in the paretic limb normalized by the less-affected limb. Results The counts ratio was not significantly correlated with ground truth and had large errors ( r = 0.48; P = .16; average error = 52.7%) because of high levels of nonfunctional movement in the paretic limb. Counts did not increase with increased functional movement. The best-performing intrasubject machine learning algorithm had an accuracy of 92.6% in the paretic limb of stroke patients, and the correlation with ground truth was r = 0.99 ( P < .001; average error = 3.9%). The best intersubject model had an accuracy of 74.2% and a correlation of r =0.81 ( P = .005; average error = 5.2%) with ground truth. Conclusions In our sample, the counts ratio did not accurately reflect functional activity. Machine learning algorithms were more accurate, and future work should focus on the development of a clinical tool.
Introduction: The transtheoretical model describes how people modify a problem behavior or acquire positive behaviors. The central construct is the stages of change, where behavior change is a continuum describing readiness to change: precontemplation, contemplation, preparation, action, and maintenance. People progress through these stages at varying rates, often moving back and forth along the continuum before attaining maintenance. We investigated whether urban underserved persons newly hospitalized for stroke or TIA intend to change their stroke prevention behaviors, and their belief about their premorbid behaviors. Methods: Participants in the PROTECT DC Phase II trial of health navigation to improve adherence with secondary stroke prevention behaviors were evaluated. They met the following criteria: atherogenic ischemic stroke or TIA diagnosed within 30 days, resident of the District of Columbia, community dwelling, and able to provide informed consent. Participants were recruited at 4 hospitals, and were interviewed regarding their risk factor management intentions. Results: In 87 participants aged 60.7 ± 12 yrs, the median NIH Stroke Scale score was 2(0-16), 45% were male, 90% were African-American. Long-term (>6 mos) medication adherence was reported by 52%, 7% reported adherence <6mos, and 32% intended to adhere during the next 6 mos. Dietary adherence >6 mos was reported by 26%, and 62% intended to start adherence. Eighty percent intended to learn more about stroke, and 94% of active smokers (30 individuals) intended to quit smoking within 6 months. Discussion: In a sample of urban underserved hospitalized for acute stroke, a large proportion reported the intent to adhere to risk management behaviors or already believed themselves adherent. Our data suggest that this population is quite motivated to engage in the recommended behaviors. Many report adherence to medication, diet and exercise recommendations prior to stroke onset; it is unclear how these perceptions relate to current stroke prevention guidelines. Urban underserved populations are receptive to behavioral changes associated with risk reduction, acute hospitalization may provide an important opportunity to initiate and refine effective stroke prevention behaviors.
Background: Constraint-induced movement therapy (CIMT) is among the most developed training approaches for motor restoration of the upper extremity (UE). Methods: Very Early Constraint-Induced Movement during Stroke Rehabilitation (VECTORS) was a single-blind phase II trial of CIMT during acute inpatient rehabilitation comparing traditional UE therapy with dose-matched and high-intensity CIMT protocols. Participants were adaptively randomized on rehabilitation admission, and received 2 weeks of study-related treatments. The primary endpoint was the total Action Research Arm Test (ARAT) score on the more affected side at 90 days after stroke onset. A mixed model analysis was performed. Results: A total of 52 participants (mean age 63.9 ± 14 years) were randomized 9.65 ± 4.5 days after onset. Mean NIHSS was 5.3 ± 1.8; mean total ARAT score was 22.5 ± 15.6; 77% had ischemic stroke. Groups were equivalent at baseline on all randomization variables. As expected, all groups improved with time on the total ARAT score. There was a significant time x group interaction ( F = 3.1, p Conclusion: Constraint-induced movement therapy (CIMT) was equally as effective but not superior to an equal dose of traditional therapy during inpatient stroke rehabilitation. Higher intensity CIMT resulted in less motor improvement at 90 days, indicating an inverse dose-response relationship. Motor intervention trials should control for dose, and higher doses of motor training cannot be assumed to be more beneficial, particularly early after stroke.
Previously, we presented an Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (ICARE) imaging informatics system that supports a large-scale phase III stroke rehabilitation trial. The ePR system is capable of displaying anonymized patient imaging studies and reports, and the system is accessible to multiple clinical trial sites and users across the United States via the web. However, the prior multicenter stroke rehabilitation trials lack any significant neuroimaging analysis infrastructure. In stroke related clinical trials, identification of the stroke lesion characteristics can be meaningful as recent research shows that lesion characteristics are related to stroke scale and functional recovery after stroke. To facilitate the stroke clinical trials, we hope to gain insight into specific lesion characteristics, such as vascular territory, for patients enrolled into large stroke rehabilitation trials. To enhance the system's capability for data analysis and data reporting, we have integrated new features with the system: a digital brain template display, a lesion quantification tool and a digital case report form. The digital brain templates are compiled from published vascular territory templates at each of 5 angles of incidence. These templates were updated to include territories in the brainstem using a vascular territory atlas and the Medical Image Processing, Analysis and Visualization (MIPAV) tool. The digital templates are displayed for side-by-side comparisons and transparent template overlay onto patients' images in the image viewer. The lesion quantification tool quantifies planimetric lesion area from user-defined contour. The digital case report form stores user input into a database, then displays contents in the interface to allow for reviewing, editing, and new inputs. In sum, the newly integrated system features provide the user with readily-accessible web-based tools to identify the vascular territory involved, estimate lesion area, and store these results in a web-based digital format.
Restoration of human brain function after injury is a signal challenge for translational neuroscience. Rodent stroke recovery studies identify an optimal or sensitive period for intensive motor training after stroke: near-full recovery is attained if task-specific motor training occurs during this sensitive window. We extended these findings to adult humans with stroke in a randomized controlled trial applying the essential elements of rodent motor training paradigms to humans. Stroke patients were adaptively randomized to begin 20 extra hours of self-selected, task-specific motor therapy at ≤30 d (acute), 2 to 3 mo (subacute), or ≥6 mo (chronic) after stroke, compared with controls receiving standard motor rehabilitation. Upper extremity (UE) impairment assessed by the Action Research Arm Test (ARAT) was measured at up to five time points. The primary outcome measure was ARAT recovery over 1 y after stroke. By 1 y we found significantly increased UE motor function in the subacute group compared with controls (ARAT difference = +6.87 ± 2.63, P = 0.009). The acute group compared with controls showed smaller but significant improvement (ARAT difference = +5.25 ± 2.59 points, P = 0.043). The chronic group showed no significant improvement compared with controls (ARAT = +2.41 ± 2.25, P = 0.29). Thus task-specific motor intervention was most effective within the first 2 to 3 mo after stroke. The similarity to rodent model treatment outcomes suggests that other rodent findings may be translatable to human brain recovery. These results provide empirical evidence of a sensitive period for motor recovery in humans.
