Assessing the reach, effectiveness, adoption, implementation, and maintenance of the ProACTIVE SCI physical activity counseling intervention among physiotherapists and SCI peer coaches during the transition from rehabilitation to community.

Introduction: Physical Activity (PA) levels for individuals with spinal cord injury (SCI) peak during rehabilitation and sharply decline post-discharge. The ProACTIVE SCI intervention has previously demonstrated very large-sized effects on PA; however, it has not been adapted for use at this critically understudied timepoint. The objective is to evaluate the reach, effectiveness, adoption, implementation, and maintenance of the ProACTIVE SCI intervention delivered by physiotherapists and SCI peer coaches during the transition from rehabilitation to community. Methods: A single-group, within-subjects, repeated measures design was employed. The implementation intervention consisted of PA counseling training, champion support, prompts and cues, and follow-up training/community of practice sessions. Physiotherapists conducted counseling sessions in hospital, then referred patients to SCI peer coaches to continue counseling for 1-year post-discharge in the community. The RE-AIM Framework was used to guide intervention evaluation. Results: Reach: 82.3% of patients at the rehabilitation hospital were reached by the intervention. Effectiveness: Interventionists (physiotherapists and SCI peer coaches) perceived that PA counseling was beneficial for patients. Adoption: 100% of eligible interventionists attended at least one training session. Implementation: Interventionists demonstrated high fidelity to the intervention. Intervention strategy highlights included a feasible physiotherapist to SCI peer coach referral process, flexibility in timepoint for intervening, and time efficiency. Maintenance: Ongoing training, PA counseling tracking forms, and the ability to refer to SCI peer coaches at discharge are core components needed to sustain this intervention. Discussion: The ProACTIVE SCI intervention was successfully adapted for use by physiotherapists and SCI peer coaches during the transition from rehabilitation to community. Findings are important for informing intervention sustainability and scale-up.

Implementation of the spinal cord injury exercise guidelines in the hospital and community settings: Protocol for a type II hybrid trial.

STUDY DESIGN: Type II hybrid effectiveness-implementation trial protocol. OBJECTIVES: To (1) evaluate the implementation of coordinated physical activity (PA) coaching delivered by physiotherapists and spinal cord injury (SCI) peers during the transition from in-hospital care to living in a community (implementation objective) and (2) assess the effect of coaching on PA behaviour and psychosocial predictors among people with SCI (effectiveness objective). SETTING: Rehabilitation hospital and home/community settings in British Columbia, Canada. METHODS: Implementation objective: PA coaches (physiotherapists and SCI peers) receive an implementation intervention including training, monitoring, feedback, and champion support. A Theoretical Domains Framework-based questionnaire is collected at baseline, post-training, 2, and 6 months follow-up and semi-structured interviews conducted at 6 months. Effectiveness objective: Using a quasi-experimental design, 55 adults with SCI are allocated to intervention (PA coaching, n = 30) or control (usual care, n = 25) groups. Participants in the intervention group are referred by physiotherapists to receive 11 SCI peer-delivered PA coaching sessions in the community. Control participants received usual care. Questionnaires assessing PA behaviour and psychosocial predictors are administered at baseline, 2-months, 6-months, and 1-year. Semi-structured interviews are conducted to assess intervention satisfaction at 6 months. Analyses include one-way (implementation objective) and two-way (effectiveness objective) repeated measures ANCOVAs for questionnaire-reported outcomes and thematic content analysis for interview data. Data are summarised using the reach effectiveness adoption implementation maintenance (RE-AIM) framework. ETHICS AND DISSEMINATION: The University of British Columbia Clinical Research Ethics Board approved the protocol (#H19-02694), clinicaltrials.gov registration NCT04493606. Documentation of the adoption process will inform implementation in future sites.

Development of a machine learning algorithm for predicting in-hospital and 1-year mortality after traumatic spinal cord injury.

BACKGROUND CONTEXT: Current prognostic tools such as the Injury Severity Score (ISS) that predict mortality following trauma do not adequately consider the unique characteristics of traumatic spinal cord injury (tSCI). PURPOSE: Our aim was to develop and validate a prognostic tool that can predict mortality following tSCI. STUDY DESIGN: Retrospective review of a prospective cohort study. PATIENT SAMPLE: Data was collected from 1245 persons with acute tSCI who were enrolled in the Rick Hansen Spinal Cord Injury Registry between 2004 and 2016. OUTCOME MEASURES: In-hospital and 1-year mortality following tSCI. METHODS: Machine learning techniques were used on patient-level data (n=849) to develop the Spinal Cord Injury Risk Score (SCIRS) that can predict mortality based on age, neurological level and completeness of injury, AOSpine classification of spinal column injury morphology, and Abbreviated Injury Scale scores. Validation of the SCIRS was performed by testing its accuracy in an independent validation cohort (n=396) and comparing its performance to the ISS, a measure which is used to predict mortality following general trauma. RESULTS: For 1-year mortality prediction, the values for the Area Under the Receiver Operating Characteristic Curve (AUC) for the development cohort were 0.84 (standard deviation=0.029) for the SCIRS and 0.55 (0.041) for the ISS. For the validation cohort, AUC values were 0.86 (0.051) for the SCIRS and 0.71 (0.074) for the ISS. For in-hospital mortality, AUC values for the development cohort were 0.87 (0.028) and 0.60 (0.050) for the SCIRS and ISS, respectively. For the validation cohort, AUC values were 0.85 (0.054) for the SCIRS and 0.70 (0.079) for the ISS. CONCLUSIONS: The SCIRS can predict in-hospital and 1-year mortality following tSCI more accurately than the ISS. The SCIRS can be used in research to reduce bias in estimating parameters and can help adjust for coefficients during model development. Further validation using larger sample sizes and independent datasets is needed to assess its reliability and to evaluate using it as an assessment tool to guide clinical decision-making and discussions with patients and families.

Highlighting discrepancies in walking prediction accuracy for patients with traumatic spinal cord injury: an evaluation of validated prediction models using a Canadian Multicenter Spinal Cord Injury Registry.

BACKGROUND CONTEXT: Models for predicting recovery in traumatic spinal cord injury (tSCI) patients have been developed to optimize care. Several models predicting tSCI recovery have been previously validated, yet recent findings question their accuracy, particularly in patients whose prognoses are the least predictable. PURPOSE: To compare independent ambulatory outcomes in AIS (ASIA [American Spinal Injury Association] Impairment Scale) A, B, C, and D patients, as well as in AIS B+C and AIS A+D patients by applying two existing logistic regression prediction models. STUDY DESIGN: A prospective cohort study. PARTICIPANT SAMPLE: Individuals with tSCI enrolled in the pan-Canadian Rick Hansen SCI Registry (RHSCIR) between 2004 and 2016 with complete neurologic examination and Functional Independence Measure (FIM) outcome data. OUTCOME MEASURES: The FIM locomotor score was used to assess independent walking ability at 1-year follow-up. METHODS: Two validated prediction models were evaluated for their ability to predict walking 1-year postinjury. Relative prognostic performance was compared with the area under the receiver operating curve (AUC). RESULTS: In total, 675 tSCI patients were identified for analysis. In model 1, predictive accuracies for 675 AIS A, B, C, and D patients as measured by AUC were 0.730 (95% confidence interval [CI] 0.622-0.838), 0.691 (0.533-0.849), 0.850 (0.771-0.928), and 0.516 (0.320-0.711), respectively. In 160 AIS B+C patients, model 1 generated an AUC of 0.833 (95% CI 0.771-0.895), whereas model 2 generated an AUC of 0.821 (95% CI 0.754-0.887). The AUC for 515 AIS A+D patients was 0.954 (95% CI 0.933-0.975) with model 1 and 0.950 (0.928-0.971) with model 2. The difference in prediction accuracy between the AIS B+C cohort and the AIS A+D cohort was statistically significant using both models (p=.00034; p=.00038). The models were not statistically different in individual or subgroup analyses. CONCLUSIONS: Previously tested prediction models demonstrated a lower predictive accuracy for AIS B+C than AIS A+D patients. These models were unable to effectively prognosticate AIS A+D patients separately; a failure that was masked when amalgamating the two patient populations. This suggests that former prediction models achieved strong prognostic accuracy by combining AIS classifications coupled with a disproportionately high proportion of AIS A+D patients.

A simplified clinical prediction rule for prognosticating independent walking after spinal cord injury: a prospective study from a Canadian multicenter spinal cord injury registry.

BACKGROUND CONTEXT: Traumatic spinal cord injury (SCI) is a debilitating condition with limited treatment options for neurologic or functional recovery. The ability to predict the prognosis of walking post injury with emerging prediction models could aid in rehabilitation strategies and reintegration into the community. PURPOSE: To revalidate an existing clinical prediction model for independent ambulation (van Middendorp et al., 2011) using acute and long-term post-injury follow-up data, and to investigatethe accuracy of a simplified model using prospectively collected data from a Canadian multicenter SCI database, the Rick Hansen Spinal Cord Injury Registry (RHSCIR). STUDY DESIGN: Prospective cohort study. PARTICIPANT SAMPLE: The analysis cohort consisted of 278 adult individuals with traumatic SCI enrolled in the RHSCIR for whom complete neurologic examination data and Functional Independence Measure (FIM) outcome data were available. OUTCOME MEASURES: The FIM locomotor score was used to assess independent walking ability (defined as modified or complete independence in walk or combined walk and wheelchair modality) at 1-year follow-up for each participant. METHODS: A logistic regression (LR) model based on age and four neurologic variables was applied to our cohort of 278 RHSCIR participants. Additionally, a simplified LR model was created. The Hosmer-Lemeshow goodness of fit test was used to check if the predictive model is applicable to our data set. The performance of the model was verified by calculating the area under the receiver operating characteristic curve (AUC). The accuracy of the model was tested using a cross-validation technique. This study was supported by a grant from The Ottawa Hospital Academic Medical Organization ($50,000 over 2 years). The RHSCIR is sponsored by the Rick Hansen Institute and is supported by funding from Health Canada, Western Economic Diversification Canada, and the provincial governments of Alberta, British Columbia, Manitoba, and Ontario. ET and JP report receiving grants from the Rick Hansen Institute (approximately $60,000 and $30,000 per year, respectively). DMR reports receiving remuneration for consulting services provided to Palladian Health, LLC and Pacira Pharmaceuticals, Inc ($20,000-$30,000 annually), although neither relationship presents a potential conflict of interest with the submitted work. KEH received a grant for involvement in the present study from the Government of Canada as part of the Canada Summer Jobs Program ($3,000). JP reports receiving an educational grant from Medtronic Canada outside of the submitted work ($75,000 annually). TM reports receiving educational fellowship support from AO Spine, AO Trauma, and Medtronic; however, none of these relationships are financial in nature. All remaining authors have no conflicts of interest to disclose. RESULTS: The fitted prediction model generated 85% overall classification accuracy, 79% sensitivity, and 90% specificity. The prediction model was able to accurately classify independent walking ability (AUC 0.889, 95% confidence interval [CI] 0.846-0.933, p<.001) compared with the existing prediction model, despite the use of a different outcome measure (FIM vs. Spinal Cord Independence Measure) to qualify walking ability. A simplified, three-variable LR model based on age and two neurologic variables had an overall classification accuracy of 84%, with 76% sensitivity and 90% specificity, demonstrating comparable accuracy with its five-variable prediction model counterpart. The AUC was 0.866 (95% CI 0.816-0.916, p<.01), only marginally less than that of the existing prediction model. CONCLUSIONS: A simplified predictive model with similar accuracy to a more complex model for predicting independent walking was created, which improves utility in a clinical setting. Such models will allow clinicians to better predict the prognosis of ambulation in individuals who have sustained a traumatic SCI.

Does Specialized Inpatient Rehabilitation Affect Whether or Not People with Traumatic Spinal Cord Injury Return Home?

Return to living at home is an important patient-reported outcome following traumatic spinal cord injury (tSCI). Specialized inpatient rehabilitation assists such patients in maximizing function and independence. Our project aim was to describe those patients receiving specialized rehabilitation after tSCI in Canada, and to determine if such rehabilitation improved the likelihood of returning home. This cohort study utilized data from the Rick Hansen Spinal Cord Injury Registry (RHSCIR) to identify patients with tSCI discharged from 1 of 18 participating acute specialized spine facilities between 2011 and 2015 to either 1 of 13 participating specialized rehabilitation facilities, or to another discharge destination. To determine if specialized rehabilitation affected likelihood of returning home, multiple logistic regressions and propensity score matchings were performed to account for age at injury, gender, neurological severity and level, acute length of stay (LOS), and region of residence. The χ2 test was used to compare rate of return home between matched groups. Of the 1599 patients included, 71% received specialized rehabilitation. Receiving specialized rehabilitation was a significant and strong predictor of return to home after controlling for covariates (adjusted odds ratio = 3.1; 95% confidence interval [CI], 1.6-5.9). The rate of return to home was significantly higher in the matched rehabilitation group than the no rehabilitation group (98% vs. 87%, p = 0.0004). For the matched patients, an extra 11 patients returned home for every 100 patients receiving specialized rehabilitation. However, effect of age on returning home requires further investigation. Improving access to specialized rehabilitation could potentially reduce discharges to nursing homes or other non-home destinations.

Effect of submaximal repetitive exercise on knee coactivation in young and middle-aged women.

Coactivation of the knee extensors and flexors increases knee joint contact forces, which may lead to degradation of the articular surfaces. This study investigated the effect of neuromuscular fatigue induced by submaximal, repetitive, dynamic contractions on coactivation of knee musculature in young and middle-aged women. Data from 10 young women (24.6±1.8 years) and 8 middle-aged women (55.4±4.2 years) were analyzed. Measures included peak knee extension and flexion torques and the average amplitude of surface electromyography of rectus femoris and biceps femoris. Coactivation ratios were calculated from these activations. To induce fatigue, participants completed up to ten sets of 50 concentric knee extension and flexion contractions at 60°/s. A two-factor analysis of variance was used to determine the effect of age and fatigue. The young group showed higher peak torque compared with the middle-aged group (P<.001). During flexion, biceps femoris activity increased after fatigue when both groups were considered together (P=.018). During extension, biceps femoris activity was higher in the middle-aged than young group (P=.043). Middle-aged women exhibited a trend for greater coactivation during knee extension compared with young women (P=.066). This coactivation likely contributed to extension torque decrements in middle-aged women.