Using Rasch motor FIM individual growth curves to inform clinical decisions for persons with paraplegia

Defining Trajectories of Linguistic, Cognitive-Communicative, and Quality of Life Outcomes in Aphasia: Longitudinal Observational Study Protocol

Objective

To describe the trajectories of linguistic, cognitive-communicative, and health-related quality of life (HRQOL) outcomes after stroke in persons with aphasia.

Design

Longitudinal observational study from inpatient rehabilitation to 18 months after stroke.

Setting

Four US mid-west inpatient rehabilitation facilities (IRFs).

Participants

We plan to recruit 400 adult (older than 21 years) English speakers who meet the following inclusion criteria: (1) Diagnosis of aphasia after a left-hemisphere infarct confirmed by CT scan or magnetic resonance imaging (MRI); (2) first admission for inpatient rehabilitation due to a neurologic event; and (3) sufficient cognitive capacity to provide informed consent and participate in testing. Exclusion criteria include any neurologic condition other than stroke that could affect language, cognition or speech, such as Parkinson's disease, Alzheimer's disease, traumatic brain injury, or the presence of right-hemisphere lesions.

Interventions

Not applicable.

Main Outcome Measures

Subjects are administered a test battery of linguistic, cognitive-communicative, and HRQOL measures. Linguistic measures include the Western Aphasia Battery-Revised and the Apraxia of Speech Rating Scale. Cognitive-communicative measures include the Communication Participation Item Bank, Connor's Continuous Performance Test-3, the Communication Confidence Rating Scale for Aphasia, the Communication Effectiveness Index, the Neurological Quality of Life measurement system (Neuro-QoL) Communication short form, and the Neuro-QoL Cognitive Function short form. HRQOL measures include the 39-item Stroke & Aphasia Quality of Life Scale, Neuro-QoL Fatigue, Sleep Disturbance, Depression, Ability to Participate in Social Roles & Activities, and Satisfaction with Social Roles & Activities tests, and the Patient-Reported Outcome Measurement and Information System 10-item Global Health short form. The test battery is administered initially during inpatient rehabilitation, and at 3-, 6-, 12-, and 18-months post-IRF discharge. Biomarker samples are collected via saliva samples at admission and a subgroup of participants also undergo resting state fMRI scans.

Results

Not applicable.

Conclusions

This longitudinal observational study will develop trajectory models for recovery of clinically relevant linguistic, cognitive-communicative, and quality of life outcomes over 18 months after inpatient rehabilitation. Models will identify individual differences in the patterns of recovery based on variations in personal, genetic, imaging, and therapy characteristics. The resulting models will provide an unparalleled representation of recovery from aphasia resulting from stroke. This improved understanding of recovery will enable clinicians to better tailor and plan rehabilitation therapies to individual patient's needs.

The Role of Upper Extremity Motor Function in the Choice of Bladder Management in Those Unable to Volitionally Void due to Neurologic Dysfunction

It is estimated that 425,000 individuals with neurologic bladder dysfunction (spinal cordinjury, spina bifida and multiple sclerosis) are unable to volitionally void and must rely oncatheter drainage. Upper extremity (UE) motor function is one of the most important factors indetermining the type of bladder management chosen in individuals who cannot volitionally void. Novel bladder management solutions for those with impaired UE motor function and concurrent impairments involitional voiding continue to be an area of need. Those with poor UE motor function more often choose an indwelling catheter, whereas those with normal UE motor function more often choose clean intermittent catheterization.

Spinal Cord Injury-Functional Index/Capacity: Responsiveness to Change Over Time

OBJECTIVE

To establish responsiveness of 3 Spinal Cord Injury-Functional Index/Capacity (SCI-FI/C) item banks in the first year after spinal cord injury (SCI).

DESIGN

Longitudinal patient-reported outcomes assessment replicated through secondary analysis of an independent data set.

SETTING

A total of 8 SCI Model Systems rehabilitation hospitals in the United States.

PARTICIPANTS

Study 1 participants included 184 adults with recent (≤4 months) traumatic SCI and 221 community-dwelling adults (>1 year post injury) (N=405). Study 2 participants were 418 individuals with recent SCI (≤4 months) (N=418).

INTERVENTIONS

In study 1, SCI-FI/C computer adaptive tests were presented in a standardized interview format either in person or by phone call at baseline and 6-month follow-up. Responsiveness was examined by comparing 6-month changes in SCI-FI scores within and across samples (recently injured vs community-dwelling) because only the recent injury sample was expected to exhibit change over time. Effect sizes were also computed. In study 2, the study 1 results were cross-validated in a second sample with recent SCI 1 year after baseline measurement. Study 2 also compared the SCI-FI/C measures' responsiveness to that of the Self-reported Functional Measure (SRFM) and stratified results by injury diagnosis and completeness.

MAIN OUTCOME MEASURES

The SCI-FI Basic Mobility/C, Self-care/C and Fine Motor/C item banks (study 1 and study 2); Self-reported Functional Measure SRFM (study 2 only).

RESULTS

In study 1, changes in SCI-FI/C scores between baseline and 6-month follow-up were statistically significant (P<.01) for recently injured individuals. SCI-FI Basic Mobility/C, Self-care/C, and Fine Motor/C item banks demonstrated small to medium effect sizes in the recently injured sample. In the community-dwelling sample, all SCI-FI/C effects were negligible (ie, effect size<0.08). Study 2 results were similar to study 1. As expected, SCI-FI Basic Mobility/C and Self-care/C were responsive to change for all individuals in study 2, whereas the SCI-FI Fine Motor/C was responsive only for individuals with tetraplegia and incomplete paraplegia. The SRFM demonstrated a medium effect size for responsiveness (effect size=0.65).

CONCLUSIONS

The SCI-FI Basic Mobility/C and Self-care/C banks demonstrate adequate sensitivity to change at 6 months and 1 year for all individuals with SCI, while the SCI-FI/C Fine Motor item bank is sensitive to change in individuals with tetraplegia or incomplete paraplegia. All SCI-FI/C banks demonstrate stability in a sample not expected to change. Results provide support for the use of these measures for research or clinical use.

Physical Function Recovery Trajectories following Spinal Cord Injury

OBJECTIVE

Explore trajectories of functional recovery that occur during the first two years after spinal cord injury (SCI).

DESIGN

Observational cohort study.

SETTING

Eight SCI Model System sites.

PARTICIPANTS

479 adults with SCI completed four Spinal Cord Injury-Functional Index (SCI-FI) item banks within 4 months of injury and again at 2 weeks, 3, 6, 12, and 24 months following baseline assessment.

INTERVENTION

None.

MAIN OUTCOME MEASURES

SCI-FI Basic Mobility/Capacity (C), Fine Motor Function/C, Self-Care/C, and Wheelchair Mobility/Assistive Technology (AT) item banks.

RESULTS

Growth mixture modeling was used to identify groups with similar trajectory patterns. For the Basic Mobility/C and Wheelchair Mobility/AT domains, models specifying 2 trajectory groups were selected. For both domains, a majority class exhibited average functional levels and gradual improvement, primarily in the first six months. A smaller group of individuals made gradual improvements but had greater initial functional limitations. The Self Care/C domain exhibited a similar pattern; however, a third, small class emerged that exhibited substantial improvement in the first six months. Finally, for individuals with tetraplegia, trajectories of Fine Motor Function/C scores followed two patterns, with individuals reporting generally low initial scores and then making either modest or large improvements. In individual growth curve models, injury/demographic factors predicted initial functional levels but less so with regard to rates of recovery.

CONCLUSIONS

Trajectories of functional recovery followed a small number of change patterns, though variation around these patterns emerged. During the first two years after initial hospitalization, SCI-FI scores showed modest improvements; however, substantial improvements were noted for a small number of individuals with severe limitations in fine motor and self-care function. Future studies should further explore the personal, medical, and environmental characteristics that influence functional trajectories during these first two years and beyond.

The potential of prediction models of functioning remains to be fully exploited: A scoping review in the field of spinal cord injury rehabilitation

OBJECTIVE

The study aimed to explore existing prediction models of functioning in spinal cord injury (SCI).

STUDY DESIGN AND SETTING

The databases PubMed, EBSCOhost CINAHL Complete, and IEEE Xplore were searched for relevant literature. The search strategy included published search filters for prediction model and impact studies, index terms and keywords for SCI, and relevant outcome measures able to assess functioning as reflected in the International Classification of Functioning, Disability and Health (ICF). The search was completed in October 2020.

RESULTS

We identified seven prediction model studies reporting twelve prediction models of functioning. The identified prediction models were mainly envisioned to be used for rehabilitation planning, however, also other possible applications were stated. The method predominantly used was regression analysis and the investigated predictors covered mainly the ICF-components of body functions and activities and participation, next to characteristics of the health condition and health interventions.

CONCLUSION

Findings suggest that the development of prediction models of functioning for use in clinical practice remains to be fully exploited. By providing a comprehensive overview of what has been done, this review informs future research on prediction models of functioning in SCI and contributes to an efficient use of research evidence.

Identification of Classes of Functioning Trajectories and Their Predictors in Individuals With Spinal Cord Injury Attending Initial Rehabilitation in Switzerland

Objectives

To identify classes of functioning trajectories in individuals with spinal cord injury (SCI) undergoing initial rehabilitation after injury and to examine potential predictors of class membership to inform clinical planning of the rehabilitation process.

Design

Longitudinal analysis of the individual's rehabilitation stay using data from the Inception Cohort of the Swiss Spinal Cord Injury Cohort Study (SwiSCI).

Setting

Initial rehabilitation in specialized centers in Switzerland.

Participants

Individuals with newly acquired SCI (N=748; mean age, 54.66±18.38y) who completed initial rehabilitation between May 2013 and September 2019. The cohort was primarily composed of men (67.51%), persons with paraplegia (56.15%), incomplete injuries (67.51%), and traumatic etiologies (55.48%).

Interventions

Not applicable.

Main Outcome Measures

Functioning was operationalized with the interval-based sum score of the Spinal Cord Independence Measure version III (SCIM III). For each individual, the SCIM III sum score was assessed at up to 4 time points during rehabilitation stay. The corresponding time of assessment was recorded by the difference in days between the SCIM III assessment and admission to the rehabilitation program.

Results

Latent process mixed model analysis revealed 4 classes of functioning trajectories within the present sample. Class-specific predicted mean functioning trajectories describe stable high functioning (n=307; 41.04%), early functioning improvement (n=39; 5.21%), moderate functioning improvement (n=287; 38.37%), and slow functioning improvement (n=115; 15.37%), respectively. Out of 12 tested factors, multinomial logistic regression showed that age, injury level, injury severity, and ventilator assistance were robust predictors that could distinguish between identified classes of functioning trajectories in the present sample.

Conclusions

The current study establishes a foundation for future research on the course of functioning of individuals with SCI in initial rehabilitation by identifying classes of functioning trajectories. This supports the development of specifically tailored rehabilitation programs and prediction models, which can be integrated into clinical rehabilitation planning.

Development of an unsupervised machine learning algorithm for the prognostication of walking ability in spinal cord injury patients

BACKGROUND CONTEXT

Traumatic spinal cord injury can have a dramatic effect on a patient's life. The degree of neurologic recovery greatly influences a patient's treatment and expected quality of life. This has resulted in the development of machine learning algorithms (MLA) that use acute demographic and neurologic information to prognosticate recovery. The van Middendorp et al. (2011) (vM) logistic regression (LR) model has been established as a reference model for the prediction of walking recovery following spinal cord injury as it has been validated within many different countries. However, an examination of the way in which these prediction models are evaluated is warranted. The area under the receiver operators curve (AUROC) has been consistently used when evaluating model performance, but it has been shown that AUROC overemphasizes the most common event resulting in an inaccurate assessment when the data are imbalanced. Furthermore, there is evidence that the use of more advanced MLA, such as an unsupervised k-means model, may show superior performance compared to LR as they can handle a larger number of features.

PURPOSE

The first objective of the study was to assess the performance of both an unsupervised MLA and LR model with complete admission neurologic information against the vM and Hicks models. Second, a comparison between the accuracy of the AUROC and the F1-score will be made to determine which method is superior for the assessment of diagnostic performance of prediction models on large-scale datasets.

STUDY DESIGN

Retrospective review of a prospective cohort study.

PATIENT SAMPLE

The Rick Hansen Spinal Cord Injury Registry (RHSCIR) was used in this study. All patients enrolled between 2004 and 2017 with complete neurologic examination and Functional Independence Measure outcome data at ≥1 year follow-up or who could walk at discharge were included. The prognostic variables included age (dichotomized at ≥65 years old); American Spinal Injury Association Impairment Scale (AIS) grade; and individual motor, light touch, and pinprick score from L2 to S1.

OUTCOME MEASURES

The Functional Independence Measure locomotor score was used to assess independent walking ability at discharge or 1-year follow-up.

METHODS

An unsupervised MLA with k=2 was chosen in order to identify a "walk" cluster and a "not walk" cluster. Model performance was assessed through the development of a receiver operating characteristic curve with associated AUROC and a precision-recall curve with associated F1-score. The study and the RHSCIR are supported by funding from Health Canada, Western Economic Diversification Canada, and the Governments of Alberta, British Columbia, Manitoba, and Ontario. These funders had no role in the study or study reporting and the authors have no conflicts of interest to report.

RESULTS

No clinically relevant differences were found between with the use of an unsupervised MLA with a greater amount of initial neurologic information compared to the established standards for any AIS classification. Although demonstrated for all separate AIS classifications, most notably, the AUROC for the vM (0.78) and Hicks models (0.76) were found to be superior to that of the new LR model (0.72); however, the vM and Hicks models had more than double the amount of false negative classifications compared to the LR. The F1-scores between these three models were also found to be different but with the vM and Hicks models being lower than the LR (0.85, 0.81, and 0.89, respectively).

CONCLUSIONS

No clinically relevant differences were found between the use of an unsupervised MLA with complete admission neurologic information compared to the previously validated standards; however, when comparing the performance of the AUROC and F1-score, the AUROC showed inaccurate prognostic performance when there was an imbalance toward a greater amount of false negatives. Importantly, the F1-score did not succumb to this imbalance. As AUROC has been used as the standard when evaluating performance of prediction models, consideration as to whether this is the most appropriate method is warranted. Future work should focus on comparing AUROC and F1-scores with other previously validated models.

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.

Pre- and Postintervention Factor Structure of Functional Independence Measure in Patients with Spinal Cord Injury

Objective

To evaluate the factor structure of Functional Independence Measure (FIM®) scale amongst people with spinal cord injury (SCI).

Methods

This was a retrospective, register-based cohort study on 155 rehabilitants with SCI. FIM was assessed at the beginning and at the end of multidisciplinary inpatient rehabilitation. The internal consistency of the FIM was assessed with Cronbach's alpha and exploratory factor analysis was employed to approximate the construct structure of FIM.

Results

The internal consistency demonstrated high Cronbach's alpha of 0.95 to 0.96. For both pre- and postintervention assessments, the exploratory factor analysis resulted in 3-factor structures. Except for two items (“walking or using a wheelchair” and “expression”), the structures of the identified three factors remained the same from the beginning to the end of rehabilitation. The loadings of all items were sufficient, exceeding 0.3. Both pre- and postintervention chi-square tests showed significant p values < 0.0001. The “motor” domain was divided into two factors with this 2-factor structure enduring through the intervention period.

Conclusions

Amongst rehabilitants with SCI, FIM failed to demonstrate unidimensionality. Instead, it showed a 3-factor structure that fluctuated only little depending on the timing of measurement. Additionally, when measured separately, also motor score was 2-dimensional, not 1-dimensional. Using a total or subscale FIM, scores seem to be unjustified in the studied population.

Neurological and functional recovery in tuberculosis patients with spinal cord injury in The Netherlands

BACKGROUND

Spinal tuberculosis (TB) accounts for approximately 1% to 3% of all TB cases and it can cause a wide range of neurological symptoms, from none to a complete spinal cord injury (SCI), resulting in complete paraplegia or tetraplegia.

OBJECTIVES

To describe the functional and neurological outcome of SCI caused by TB.

METHODS

Retrospective data on the admission period was combined with prospectively collected data on long-term follow-up. Primary outcome was neurological outcome in terms of motor function. Secondary outcome measures were functional outcome in terms of level of independence and community participation. Results were compared to the outcome in patients with SCI due to trauma.

RESULTS

Six TB patients with complete motor SCI (American Spinal Injury Association Impairment Scale (AIS) A or B) were compared to eighteen patients with traumatic SCI. Most TB patients regained almost full neurological function (median motor score improved from 50 to 100), and reached high levels of independence, whereas trauma patients did not improve neurologically (median motor score remained 50) and reached a plateau in level of independence.

CONCLUSIONS

SCI due to tuberculosis in the Netherlands shows remarkable improvement in both neurological and functional outcome, especially compared with traumatic SCI.

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.