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

Machine Learning Web Application for Predicting Functional Outcomes in Patients With Traumatic Spinal Cord Injury Following Inpatient Rehabilitation

Accurately predicting functional outcomes in patients with spinal cord injury (SCI) helps clinicians set realistic functional recovery goals and improve the home environment after discharge. The present study aimed to develop and validate machine learning (ML) models to predict functional outcomes in patients with SCI and deploy the models within a web application. The study included data from the Japan Association of Rehabilitation Database from January 1, 1991, to December 31, 2015. Patients with SCI who were admitted to an SCI center or transferred to a participating post-acute rehabilitation hospital after receiving acute treatment were enrolled in this database. The primary outcome was functional ambulation at discharge from the rehabilitation hospital. The secondary outcome was the total motor Functional Independence Measure (FIM) score at discharge. We used binary classification models to predict whether functional ambulation was achieved, as well as regression models to predict total motor FIM scores at discharge. In the training dataset (70% random sample) using demographic characteristics and neurological and functional status as predictors, we built prediction performance matrices of multiple ML models and selected the best one for each outcome. We validated each model's predictive performance in the test dataset (the remaining 30%). Among the 4181 patients, 3827 were included in the prediction model for the total motor FIM score. The mean (standard deviation [SD]) age was 50.4 (18.7) years, and 3211 (83.9%) patients were male. There were 3122 patients included in the prediction model for functional ambulation. The CatBoost Classifier and regressor models showed the best performances in the training dataset. On the test dataset, the CatBoost Classifier had an area under the receiver operating characteristic curve of 0.8572 and an accuracy of 0.7769 for predicting functional ambulation. Likewise, the CatBoost Regressor performed well, with an R2 of 0.7859, a mean absolute error of 9.2957, and a root mean square error of 13.4846 for predicting the total motor FIM score. The final models were deployed in a web application to provide functional predictions. The application can be found at http://3.138.174.54:8501. In conclusion, our prediction models developed using ML successfully predicted functional outcomes in patients with SCI and were deployed in an open-access web application.

Guidelines for neuroprognostication in adults with traumatic spinal cord injury

BACKGROUND

Traumatic spinal cord injury (tSCI) impacts patients and their families acutely and often for the long term. The ability of clinicians to share prognostic information about mortality and functional outcomes allows patients and their surrogates to engage in decision-making and plan for the future. These guidelines provide recommendations on the reliability of acute-phase clinical predictors to inform neuroprognostication and guide clinicians in counseling adult patients with tSCI or their surrogates.

METHODS

A narrative systematic review was completed using Grading of Recommendations Assessment, Development, and Evaluation methodology. Candidate predictors, including clinical variables and prediction models, were selected based on clinical relevance and presence of an appropriate body of evidence. The Population/Intervention/Comparator/Outcome/Timing/Setting question was framed as "When counseling patients or surrogates of critically ill patients with traumatic spinal cord injury, should < predictor, with time of assessment if appropriate > be considered a reliable predictor of < outcome, with time frame of assessment >?" Additional full-text screening criteria were used to exclude small and lower quality studies. Following construction of an evidence profile and summary of findings, recommendations were based on four Grading of Recommendations Assessment, Development, and Evaluation criteria: quality of evidence, balance of desirable and undesirable consequences, values and preferences, and resource use. Good practice recommendations addressed essential principles of neuroprognostication that could not be framed in the Population/Intervention/Comparator/Outcome/Timing/Setting format. Throughout the guideline development process, an individual living with tSCI provided perspective on patient-centered priorities.

RESULTS

Six candidate clinical variables and one prediction model were selected. Out of 11,132 articles screened, 369 met inclusion criteria for full-text review and 35 articles met eligibility criteria to guide recommendations. We recommend pathologic findings on magnetic resonance imaging, neurological level of injury, and severity of injury as moderately reliable predictors of American Spinal Cord Injury Impairment Scale improvement and the Dutch Clinical Prediction Rule as a moderately reliable prediction model of independent ambulation at 1 year after injury. No other reliable or moderately reliable predictors of mortality or functional outcome were identified. Good practice recommendations include considering the complete clinical condition as opposed to a single variable and communicating the challenges of likely functional deficits as well as potential for improvement and for long-term quality of life with SCI-related deficits to patients and surrogates.

CONCLUSIONS

These guidelines provide recommendations about the reliability of acute-phase predictors of mortality, functional outcome, American Spinal Injury Association Impairment Scale grade conversion, and recovery of independent ambulation for consideration when counseling patients with tSCI or their surrogates and suggest broad principles of neuroprognostication in this context.

Identification of a reliable sacral-sparing examination to assess the ASIA impairment scale in patients with traumatic spinal cord injury

OBJECTIVES

We evaluated the time course of the American Spinal Cord Injury Association (ASIA) impairment scale (AIS) for up to three months in participants within 72 h after traumatic spinal cord injury (TSCI) with complete paralysis. We aimed to determine the most useful sacral-sparing examination (deep anal pressure [DAP], voluntary anal contraction [VAC], S4-5 light touch [LT], or pin prick [PP] sensation) in determining AIS grades.

DESIGN

Retrospective cohort study.

SETTING

Spinal Injuries Center, Fukuoka, Japan.

PARTICIPANTS

Among 668 TSCI participants registered in the Japan Single Center study for Spinal Cord Injury Database (JSSCI-DB) between January 2012 and May 2020, we extracted the data of 80 patients with AIS grade A within 72 h after injury and neurological level of injury (NLI) at T12 or higher.

INTERVENTIONS

None.

OUTCOME MEASURES

The sacral-sparing examination at the time of the change to incomplete paralysis was compared to the AIS determination using a standard algorithm and with each assessment including the VAC, DAP, S4-5LT, and S4-5PP examinations at the time of AIS functional change. Agreement among assessments was evaluated using weighted kappa coefficients. The relationship was evaluated using Spearman's rank correlation coefficients.

RESULTS

Fifteen participants (18.8%) improved to incomplete paralysis (AIS B to D) within three months after injury. The single assessment among the sacral-sparing examinations with the highest agreement and strongest correlation with AIS determination was the S4-5LT examination (k = 0.89, P < 0.01, r = 0.84, P < 0.01).

CONCLUSIONS

The S4-5LT examination is key in determining complete or incomplete paralysis due to its high discriminatory power.

Multivariable Prediction Models for Traumatic Spinal Cord Injury: A Systematic Review

Background

Traumatic spinal cord injuries (TSCI) greatly affect the lives of patients and their families. Prognostication may improve treatment strategies, health care resource allocation, and counseling. Multivariable clinical prediction models (CPMs) for prognosis are tools that can estimate an absolute risk or probability that an outcome will occur.

Objectives

We sought to systematically review the existing literature on CPMs for TSCI and critically examine the predictor selection methods used.

Methods

We searched MEDLINE, PubMed, Embase, Scopus, and IEEE for English peer-reviewed studies and relevant references that developed multivariable CPMs to prognosticate patient-centered outcomes in adults with TSCI. Using narrative synthesis, we summarized the characteristics of the included studies and their CPMs, focusing on the predictor selection process.

Results

We screened 663 titles and abstracts; of these, 21 full-text studies (2009-2020) consisting of 33 distinct CPMs were included. The data analysis domain was most commonly at a high risk of bias when assessed for methodological quality. Model presentation formats were inconsistently included with published CPMs; only two studies followed established guidelines for transparent reporting of multivariable prediction models. Authors frequently cited previous literature for their initial selection of predictors, and stepwise selection was the most frequent predictor selection method during modelling.

Conclusion

Prediction modelling studies for TSCI serve clinicians who counsel patients, researchers aiming to risk-stratify participants for clinical trials, and patients coping with their injury. Poor methodological rigor in data analysis, inconsistent transparent reporting, and a lack of model presentation formats are vital areas for improvement in TSCI CPM research.

Are Clinical Prediction Rules Used in Spinal Cord Injury Care? A Survey of Practice

Background

Accurate outcome prediction is desirable post spinal cord injury (SCI), reducing uncertainty for patients and supporting personalized treatments. Numerous attempts have been made to create clinical prediction rules that identify patients who are likely to recover function. It is unknown to what extent these rules are routinely used in clinical practice.

Objectives

To better understand knowledge of, and attitudes toward, clinical prediction rules amongst SCI clinicians in the United Kingdom.

Methods

An online survey was distributed via mailing lists of clinical special interest groups and relevant National Health Service Trusts. Respondents answered questions about their knowledge of existing clinical prediction rules and their general attitudes to using them. They also provided information about their level of experience with SCI patients.

Results

One hundred SCI clinicians completed the survey. The majority (71%) were unaware of clinical prediction rules for SCI; only 8% reported using them in clinical practice. Less experienced clinicians were less likely to be aware. Lack of familiarity with prediction rules was reported as being a barrier to their use. The importance of clinical expertise when making prognostic decisions was emphasized. All respondents reported interest in using clinical prediction rules in the future.

Conclusion

The results show widespread lack of awareness of clinical prediction rules amongst SCI clinicians in the United Kingdom. However, clinicians were positive about the potential for clinical prediction rules to support decision-making. More focus should be directed toward refining current rules and improving dissemination within the SCI community.

A Single Dermatome Clinical Prediction Rule for Independent Walking 1 Year After Spinal Cord Injury

OBJECTIVE

To derive and validate a simple, accurate CPR to predict future independent walking ability after SCI at the bedside that does not rely on motor scores and is predictive for those initially classified in the middle of the SCI severity spectrum.

DESIGN

Retrospective cohort study. Binary variables were derived, indicating degrees of sensation to evaluate predictive value of pinprick and light touch variables across dermatomes. The optimal single sensory modality and dermatome was used to derive our CPR, which was validated on an independent dataset.

SETTING

Analysis of SCI Model Systems dataset.

PARTICIPANTS

Individuals with traumatic SCI. The data of 3679 participants (N=3679) were included with 623 participants comprising the derivation dataset and 3056 comprising the validation dataset.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Self-reported ability to walk both indoors and outdoors.

RESULTS

Pinprick testing at S1 over lateral heels, within 31 days of SCI, accurately identified future independent walkers 1 year after SCI. Normal pinprick in both lateral heels provided good prognosis, any pinprick sensation in either lateral heel provided fair prognosis, and no sensation provided poor prognosis. This CPR performed satisfactorily in the middle SCI severity subgroup.

CONCLUSIONS

In this large multi-site study, we derived and validated a simple, accurate CPR using only pinprick sensory testing at lateral heels that predicts future independent walking after SCI.

Enabling knowledge translation: implementation of a web-based tool for independent walking prediction after traumatic spinal cord injury

Introduction

Several clinical prediction rules (CPRs) have been published, but few are easily accessible or convenient for clinicians to use in practice. We aimed to develop, implement, and describe the process of building a web-based CPR for predicting independent walking 1-year after a traumatic spinal cord injury (TSCI).

Methods

Using the published and validated CPR, a front-end web application called "Ambulation" was built using HyperText Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. A survey was created using QualtricsXM Software to gather insights on the application's usability and user experience. Website activity was monitored using Google Analytics. Ambulation was developed with a core team of seven clinicians and researchers. To refine the app's content, website design, and utility, 20 professionals from different disciplines, including persons with lived experience, were consulted.

Results

After 11 revisions, Ambulation was uploaded onto a unique web domain and launched (www.ambulation.ca) as a pilot with 30 clinicians (surgeons, physiatrists, and physiotherapists). The website consists of five web pages: Home, Calculation, Team, Contact, and Privacy Policy. Responses from the user survey (n = 6) were positive and provided insight into the usability of the tool and its clinical utility (e.g., helpful in discharge planning and rehabilitation), and the overall face validity of the CPR. Since its public release on February 7, 2022, to February 28, 2023, Ambulation had 594 total users, 565 (95.1%) new users, 26 (4.4%) returning users, 363 (61.1%) engaged sessions (i.e., the number of sessions that lasted 10 seconds/longer, had one/more conversion events e.g., performing the calculation, or two/more page or screen views), and the majority of the users originating from the United States (39.9%) and Canada (38.2%).

Discussion

Ambulation is a CPR for predicting independent walking 1-year after TSCI and it can assist frontline clinicians with clinical decision-making (e.g., time to surgery or rehabilitation plan), patient education and goal setting soon after injury. This tool is an example of adapting a validated CPR for independent walking into an easily accessible and usable web-based tool for use in clinical practice. This study may help inform how other CPRs can be adopted into clinical practice.

The Impact of COVID-19 on Epidemiological Features of Spinal Cord Injury in Wuhan, China: A Comparative Study in Different Time Periods

Background and Objectives: Spinal cord injury (SCI) is a severe affliction that can have a profound impact on a person's ability to move and feel, affecting a significant number of individuals. However, rehabilitation after SCI treatment remains a critical method to improve motor-sensory functions, which improves the patient's quality of life. This study aims to describe the epidemiological profile of SCI during the COVID-19 pandemic ("COVID-19 period") and before and after the COVID-19 pandemic ("non-COVID-19 period") in Wuhan City, Hubei Province, China. Materials and Methods: Medical records of 93 patients diagnosed with SCI admitted to the rehabilitation department of Wuhan Tongji Hospital from January 2019 to May 2023 were retrospectively reviewed. Basic demographics and clinical characteristics such as level of injury, American Spinal Injury Association (ASIA) Impairment Scale, treatment method, and concomitant injuries were analyzed. Results: Forty patients with SCI from the non-COVID-19 period and fifty-three patients from the COVID-19 period were identified. The mean ages were 38.80 ± 17.71 and 44.53 ± 13.27 years, respectively, with a consistent male-to-female ratio of 2:1 across both periods. Notably, falls accounted for the most prevalent mechanism of injury, constituting 50% of cases during the non-COVID-19 period and 37.74% during the COVID-19 period. The most common initial ASIA grade was B in the non-COVID-19 period and grade C in the COVID-19 period. In addition, the final ASIA grade after treatment was grade C in the non-COVID-19 period and grade D in the COVID-19 period. Conclusions: A greater proportion of males suffer from SCI, and the primary causes are falls and traffic accidents. Workers are the most vulnerable group to SCI among all patients. Prevention strategies should be customized based on the unique characteristics of SCI patients. This study highlights the importance of SCI rehabilitation.

Importance of Prospective Registries and Clinical Research Networks in the Evolution of Spinal Cord Injury Care

Only 100 years ago, traumatic spinal cord injury (SCI) was commonly lethal. Today, most people who sustain SCI survive with continual efforts to improve their quality of life and neurological outcomes. SCI epidemiology is changing as preventative interventions reduce injuries in younger individuals, and there is an increased incidence of incomplete injuries in aging populations. Early treatment has become more intensive with decompressive surgery and proactive interventions to improve spinal cord perfusion. Accurate data, including specialized outcome measures, are crucial to understanding the impact of epidemiological and treatment trends. Dedicated SCI clinical research and data networks and registries have been established in the United States, Canada, Europe, and several other countries. We review four registry networks: the North American Clinical Trials Network (NACTN) SCI Registry, the National Spinal Cord Injury Model Systems (SCIMS) Database, the Rick Hansen SCI Registry (RHSCIR), and the European Multi-Center Study about Spinal Cord Injury (EMSCI). We compare the registries' focuses, data platforms, advanced analytics use, and impacts. We also describe how registries' data can be combined with electronic health records (EHRs) or shared using federated analysis to protect registrants' identities. These registries have identified changes in epidemiology, recovery patterns, complication incidence, and the impact of practice changes such as early decompression. They've also revealed latent disease-modifying factors, helped develop clinical trial stratification models, and served as matched control groups in clinical trials. Advancing SCI clinical science for personalized medicine requires advanced analytical techniques, including machine learning, counterfactual analysis, and the creation of digital twins. Registries and other data sources help drive innovation in SCI clinical science.

Spasticity Predicts Motor Recovery for Patients with Subacute Motor Complete Spinal Cord Injury

OBJECTIVE

A motor complete spinal cord injury (SCI) results in the loss of voluntary motor control below the point of injury. Some of these patients can regain partial motor function through inpatient rehabilitation; however, there is currently no biomarker to easily identify which patients have this potential. Evidence indicates that spasticity could be that marker. Patients with motor complete SCI who exhibit spasticity show preservation of descending motor pathways, the pathways necessary for motor signals to be carried from the brain to the target muscle. We hypothesized that the presence of spasticity predicts motor recovery after subacute motor complete SCI.

METHODS

Spasticity (Modified Ashworth Scale and pendulum test) and descending connectivity (motor evoked potentials) were tested in the rectus femoris muscle in patients with subacute motor complete (n = 36) and motor incomplete (n = 30) SCI. Motor recovery was assessed by using the International Standards for Neurological Classification of Spinal Cord Injury and the American Spinal Injury Association Impairment Scale (AIS). All measurements were taken at admission and discharge from inpatient rehabilitation.

RESULTS

We found that motor complete SCI patients with spasticity improved in motor scores and showed AIS conversion to either motor or sensory incomplete. Conversely, patients without spasticity showed no changes in motor scores and AIS conversion. In incomplete SCI patients, motor scores improved and AIS conversion occurred regardless of spasticity.

INTERPRETATION

These findings suggest that spasticity represents an easy-to-use clinical outcome that might help to predict motor recovery after severe SCI. This knowledge can improve inpatient rehabilitation effectiveness for motor complete SCI patients. ANN NEUROL 2023.

A dynamic nomogram for predicting the probability of irreversible neurological dysfunction after cervical spinal cord injury: research based on clinical features and MRI data

BACKGROUND

Irreversible neurological dysfunction (IND) is an adverse event after cervical spinal cord injury (CSCI). However, there is still a shortage of objective criteria for the early prediction of neurological function. We aimed to screen independent predictors of IND and use these findings to construct a nomogram that could predict the development of neurological function in CSCI patients.

METHODS

Patients with CSCI attending the Affiliated Hospital of Southwest Medical University between January 2014 and March 2021 were included in this study. We divided the patients into two groups: reversible neurological dysfunction (RND) and IND. The independent predictors of IND in CSCI patients were screened using the regularization technique to construct a nomogram, which was finally converted into an online calculator. Concordance index (C-index), calibration curves analysis and decision curve analysis (DCA) evaluated the model's discrimination, calibration, and clinical applicability. We tested the nomogram in an external validation cohort and performed internal validation using the bootstrap method.

RESULTS

We enrolled 193 individuals with CSCI in this study, including IND (n = 75) and RND (n = 118). Six features, including age, American spinal injury association Impairment Scale (AIS) grade, signal of spinal cord (SC), maximum canal compromise (MCC), intramedullary lesion length (IMLL), and specialized institution-based rehabilitation (SIBR), were included in the model. The C-index of 0.882 from the training set and its externally validated value of 0.827 demonstrated the model's prediction accuracy. Meanwhile, the model has satisfactory actual consistency and clinical applicability, verified in the calibration curve and DCA.

CONCLUSION

We constructed a prediction model based on six clinical and MRI features that can be used to assess the probability of developing IND in patients with CSCI.

Limb accelerations during sleep are related to measures of strength, sensation, and spasticity among individuals with spinal cord injury

BACKGROUND

To evaluate the relationship between measures of neuromuscular impairment and limb accelerations (LA) collected during sleep among individuals with chronic spinal cord injury (SCI) to provide evidence of construct and concurrent validity for LA as a clinically meaningful measure.

METHODS

The strength (lower extremity motor score), sensation (summed lower limb light touch scores), and spasticity (categorized lower limb Modified Ashworth Scale) were measured from 40 adults with chronic (≥ 1 year) SCI. Demographics, pain, sleep quality, and other covariate or confounding factors were measured using self-report questionnaires. Each participant then wore ActiGraph GT9X Link accelerometers on their ankles and wrist continuously for 1-5 days to measure LA from movements during sleep. Regression models with built-in feature selection were used to determine the most relevant LA features and the association to each measure of impairment.

RESULTS

LA features were related to measures of impairment with models explaining 69% and 73% of the variance (R²) in strength and sensation, respectively, and correctly classifying 81.6% (F1-score = 0.814) of the participants into spasticity categories. The most commonly selected LA features included measures of power and frequency (frequency domain), movement direction (correlation between axes), consistency between movements (relation to recent movements), and wavelet energy (signal characteristics). Rolling speed (change in angle of inclination) and movement smoothness (median crossings) were uniquely associated with strength. When LA features were included, an increase of 72% and 222% of the variance was explained for strength and sensation scores, respectively, and there was a 34% increase in spasticity classification accuracy compared to models containing only covariate features such as demographics, sleep quality, and pain.

CONCLUSION

LA features have shown evidence of having construct and concurrent validity, thus demonstrating that LA are a clinically-relevant measure related to lower limb strength, sensation, and spasticity after SCI. LA may be useful as a more detailed measure of impairment for applications such as clinical prediction models for ambulation.

Utility of transcranial magnetic stimulation in the assessment of spinal cord injury: Current status and future directions

Comprehensive assessment following traumatic spinal cord injury (SCI) is needed to improve prognostication, advance the understanding of the neurophysiology and better targeting of clinical interventions. The International Standards for Neurological Classification of Spinal Cord Injury is the most common clinical examination recommended for use after a SCI. In addition, there are over 30 clinical assessment tools spanning across different domains of the International Classification of Functioning, Disability, and Health that have been validated and recommended for use in SCI. Most of these tools are subjective in nature, have limited value in predicting neurologic recovery, and do not provide insights into neurophysiological mechanisms. Transcranial magnetic stimulation (TMS) is a non-invasive neurophysiology technique that can supplement the clinical assessment in the domain of body structure and function during acute and chronic stages of SCI. TMS offers a better insight into neurophysiology and help in better detection of residual corticomotor connectivity following SCI compared to clinical assessment alone. TMS-based motor evoked potential and silent period duration allow study of excitatory and inhibitory mechanisms following SCI. Changes in muscle representations in form of displacement of TMS-based motor map center of gravity or changes in the map area can capture neuroplastic changes resulting from SCI or following rehabilitation. Paired-pulse TMS measures help understand the compensatory reorganization of the cortical circuits following SCI. In combination with peripheral stimulation, TMS can be used to study central motor conduction time and modulation of spinal reflexes, which can be used for advanced diagnostic and treatment purposes. To strengthen the utility of TMS in SCI assessment, future studies will need to standardize the assessment protocols, address population-specific concerns, and establish the psychometric properties of TMS-based measurements in the SCI population.

Inclusive Trial Designs in Acute Spinal Cord Injuries: Prediction-Based Stratification of Clinical Walking Outcome and Projected Enrolment Frequencies

Background

New therapeutic approaches in neurological disorders are progressing into clinical development. Past failures in translational research have underlined the critical importance of selecting appropriate inclusion criteria and primary outcomes. Narrow inclusion criteria provide sensitivity, but increase trial duration and cost to the point of infeasibility, while broader requirements amplify confounding, increasing the risk of trial failure. This dilemma is perhaps most pronounced in spinal cord injury (SCI), but applies to all neurological disorders with low frequency and/or heterogeneous clinical manifestations.

Objective

Stratification of homogeneous patient cohorts to enable the design of clinical trials with broad inclusion criteria.

Methods

Prospectively–gathered data from patients with acute cervical SCI were analysed using an unbiased recursive partitioning conditional inference tree (URP–CTREE) approach. Performance in the 6-minute walk test at 6 months after injury was classified based on standardized neurological assessments within the first 15 days of injury. Functional and neurological outcomes were tracked throughout rehabilitation up to 6 months after injury.

Results

URP–CTREE identified homogeneous outcome cohorts in a study group of 309 SCI patients. These cohorts were validated by an internal, yet independent, validation group of 172 patients. The study group cohorts identified demonstrated distinct recovery profiles throughout rehabilitation. The baseline characteristics of the analysed groups were compared to a reference group of 477 patients.

Conclusion

URP–CTREE enables inclusive trial design by revealing the distribution of outcome cohorts, discerning distinct recovery profiles and projecting potential patient enrolment by providing estimates of the relative frequencies of cohorts to improve the design of clinical trials in SCI and beyond.

Spinal Cord Tissue Bridges Validation Study: Predictive Relationships With Sensory Scores Following Cervical Spinal Cord Injury

Background

Using magnetic resonance imaging (MRI), widths of ventral tissue bridges demonstrated significant predictive relationships with future pinprick sensory scores, and widths of dorsal tissue bridges demonstrated significant predictive relationships with future light touch sensory scores, following spinal cord injury (SCI). These studies involved smaller participant numbers, and external validation of their findings is warranted.

Objectives

The purpose of this study was to validate these previous findings using a larger independent data set.

Methods

Widths of ventral and dorsal tissue bridges were quantified using MRI in persons post cervical level SCI (average 3.7 weeks post injury), and pinprick and light touch sensory scores were acquired at discharge from inpatient rehabilitation (average 14.3 weeks post injury). Pearson product-moments were calculated and linear regression models were created from these data.

Results

Wider ventral tissue bridges were significantly correlated with pinprick scores (r = 0.31, p < 0.001, N = 136) and wider dorsal tissue bridges were significantly correlated with light touch scores (r = 0.31, p < 0.001, N = 136) at discharge from inpatient rehabilitation.

Conclusion

This retrospective study's results provide external validation of previous findings, using a larger sample size. Following SCI, ventral tissue bridges hold significant predictive relationships with future pinprick sensory scores and dorsal tissue bridges hold significant predictive relationships with future light touch sensory scores.

MRI metrics at the epicenter of spinal cord injury are correlated with the stepping process in rhesus monkeys

Clinical evaluations of long-term outcomes in the early-stage spinal cord injury (SCI) focus on macroscopic motor performance and are limited in their prognostic precision. This study was designed to investigate the sensitivity of the magnetic resonance imaging (MRI) indexes to the data-driven gait process after SCI. Ten adult female rhesus monkeys were subjected to thoracic SCI. Kinematics-based gait examinations were performed at 1 (early stage) and 12 (chronic stage) months post-SCI. The proportion of stepping (PS) and gait stability (GS) were calculated as the outcome measures. MRI metrics, which were derived from structural imaging (spinal cord cross-sectional area, SCA) and diffusion tensor imaging (fractional anisotropy, FA; axial diffusivity, λ_//), were acquired in the early stage and compared with functional outcomes by using correlation analysis and stepwise multivariable linear regression. Residual tissue SCA at the injury epicenter and residual tissue FA/remote normal-like tissue FA were correlated with the early-stage PS and GS. The extent of lesion site λ_///residual tissue λ_// in the early stage after SCI was correlated with the chronic-stage GS. The ratios of lesion site λ_// to residual tissue λ_// and early-stage GS were predictive of the improvement in the PS at follow-up. Similarly, the ratios of lesion site λ_// to residual tissue λ_// and early-stage PS best predicted chronic GS recovery. Our findings demonstrate the predictive power of MRI combined with the early data-driven gait indexes for long-term outcomes. Such an approach may help clinicians to predict functional recovery accurately.

Early Clinical Prediction of Independent Outdoor Functional Walking Capacity in a Prospective Cohort of Traumatic Spinal Cord Injury Patients

OBJECTIVE

The first objective was to identify a method for early prediction of independent outdoor functional walking 1 yr after a traumatic spinal cord injury using the motor and sensory function derived from the International Standards for Neurological Classification of Spinal Cord Injury assessment during acute care. Then, the second objective was to develop a clinically relevant prediction rule that would be accurate, easy to use, and quickly calculated in clinical setting.

DESIGN

A prospective cohort of 159 traumatic spinal cord injury patients was analyzed. Bivariate correlations were used to determine the assessment method of motor strength and sensory function as well as the specific dermatomes and myotomes best associated with independent outdoor functional walking 1 yr after injury. An easy-to-use clinical prediction rule was produced using a multivariable linear regression model.

RESULTS

The highest motor strength for a given myotome (L3 and L5) and preserved light touch sensation (dermatome S1) were the best predictors of the outcome. The proposed prediction rule displayed a sensitivity of 84.21%, a specificity of 85.54%, and a global accuracy of 84.91% for classification.

CONCLUSIONS

After an acute traumatic spinal cord injury, accurately predicting the ability to walk is challenging. The proposed clinical prediction rule aims to enhance previous work by identifying traumatic spinal cord injury patients who will reach a mobility level that fosters social participation and quality of life in the chronic period after the injury.

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) Revise the different motor and sensory function assessment methods used for prognostication of walking after an acute traumatic spinal cord injury; (2) Identify clinical factors that are significantly associated with functional walking 1 yr after a traumatic spinal cord injury; and (3) Accurately estimate the likelihood of reaching independent outdoor functional walking in the chronic phase after an acute traumatic spinal cord injury.

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.

Early Trauma Predictors of Mobility in People with Spinal Cord Injury

STUDY DESIGN

A retrospective cohort study.

OBJECTIVE

This study aims to assess the potential value of very early trauma variables such as Abbreviated Injury Scale (AIS) and the Injury Severity Score for predicting independent ambulation following a traumatic spinal cord injury (TSCI).

SUMMARY OF BACKGROUND DATA

Several models for prediction of ambulation early after TSCI have been published and validated. The vast majority rely on the initial examination of American Spinal Injury Association (ASIA) impairment scale and level of injury; however, in many locations and clinical situations this examination is not feasible early after the injury.

METHODS

Patient characteristics, trauma data, and ASIA scores on admission to rehabilitation were collected for each of the 144 individuals in the study. Outcome measure was the indoor mobility item of the Spinal Cord Independence Measure taken upon discharge from rehabilitation. Univariate and multivariable models were created for each predictor, Odds ratios (ORs) were obtained by a multivariable logistic regression analysis, and area under the receiver operator curve was calculated for each model.

RESULTS

We observed a significant correlation between the trauma variables and independent ambulation upon discharge from rehabilitation. Of the early variables, the AIS for the spine region showed the strongest correlation.

CONCLUSION

These findings support using preliminary trauma variables for early prognostication of ambulation following a TSCI, allowing for tailored individual interventions.Level of Evidence: 3.

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.

Improving Diagnostic Workup Following Traumatic Spinal Cord Injury: Advances in Biomarkers

PURPOSE OF REVIEW

Traumatic spinal cord injury (SCI) is a life-changing event with drastic implications for patients due to sensorimotor impairment and autonomous dysfunction. Current clinical evaluations focus on the assessment of injury level and severity using standardized neurological examinations. However, they fail to predict individual trajectories of recovery, which highlights the need for the development of advanced diagnostics. This narrative review identifies recent advances in the search of clinically relevant biomarkers in the field of SCI.

RECENT FINDINGS

Advanced neuroimaging and molecular biomarkers sensitive to the disease processes initiated by the SCI have been identified. These biomarkers range from advanced neuroimaging techniques, neurophysiological readouts, and molecular biomarkers identifying the concentrations of several proteins in blood and CSF samples. Some of these biomarkers improve current prediction models based on clinical readouts. Validation with larger patient cohorts is warranted. Several biomarkers have been identified-ranging from imaging to molecular markers-that could serve as advanced diagnostic and hence supplement current clinical assessments.

Using a national surgical database to predict complications following posterior lumbar surgery and comparing the area under the curve and F1-score for the assessment of prognostic capability

BACKGROUND

With spinal surgery rates increasing in North America, models that are able to accurately predict which patients are at greater risk of developing complications are highly warranted. However, the previously published methods which have used large, multi-centre databases to develop their prediction models have relied on the receiver operator characteristics curve with the associated area under the curve (AUC) to assess their model's performance. Recently, it has been found that a precision-recall curve with the associated F1-score could provide a more realistic analysis for these models.

PURPOSE

To develop a logistic regression (LR) model for the prediction of complications following posterior lumbar spine surgery and to then assess for any difference in performance of the model when using the AUC versus the F1-score.

STUDY DESIGN

Retrospective review of a prospective cohort.

PATIENT SAMPLE

The American College of Surgeons National Surgical Quality Improvement Program (NSQIP) registry was used. All patients that underwent posterior lumbar spine surgery between 2005 to 2016 with appropriate data were included.

OUTCOME MEASURES

Both the AUC and F1-score were utilized to assess the prognostic performance of the prediction model.

METHODS

In order to develop the LR model used to predict a complication during or following spine surgery, 19 variables were selected by three orthopedic spine surgeons from the NSQIP registry. Two datasets were developed for this analysis: (1) an imbalanced dataset, which was taken directly from the NSQIP registry, and (2) a down-sampled set. The purpose of the down-sampled set was to balance the data in order to evaluate whether balancing the data had an effect on model performance. The AUC and F1-score were applied to both of these datasets.

RESULTS

Within the NSQIP database, 52,787 spine surgery cases were identified of which only 10% of these cases had complications during surgery. Applying the LR model showed a large difference between the AUC (0.69) and the F1 score (0.075) on the imbalanced dataset. However, no major differences existed between the AUC and F1-score when the data was balanced and the LR model was reapplied (0.69 and 0.62, AUC and F1-score, respectively).

CONCLUSIONS

The F1-score detected a drastically lower performance for the prediction of complications when using the imbalanced data, but detected a performance similar to the AUC level when balancing techniques were utilized for the dataset. This difference is due to a low precision score when many false positive classifications are present, which is not identified when using the AUC value. This lowers the utility of the AUC score, as many of the datasets used in medicine are imbalanced. Therefore, we recommend using the F1-score on large, prospective databases when the data is imbalanced with a large amount of true negative classifications.

Clinical judgment is a cornerstone for validating and using clinical prediction rules: a head-to-head study on ambulation outcomes for spinal cord injured patients

STUDY DESIGN

Retrospective comparative study.

OBJECTIVE

Clinical prediction rules (CPRs) are an effervescent topic in the medical literature. Recovering ambulation after a traumatic spinal cord injury (tSCI) is a priority for patients and multiple CPRs have been proposed for predicting ambulation outcomes. Our objective is to confront clinical judgment to an established CPR developed for patients with tSCI.

SETTINGS

Level one trauma center specialized in tSCI and its affiliated rehabilitation center.

METHOD

In this retrospective comparative study, six physicians had to predict the ambulation outcome of 68 patients after a tSCI based on information from the acute hospitalization. Ambulation was also predicted according to the CPR of van Middendorp (CPR-vM). The success rate of the CPR-vM and clinicians to predict ambulation was compared using criteria of 5% for defining clinical significance, and a level of statistical significance of 0.05 for bilateral McNemar tests.

RESULTS

There was no statistical difference between the overall performance of physicians (success rate of 79%) and of the CPR-vM (81%) for predicting ambulation. The differences between the CPR-vM and physicians varied clinically and significantly with the level of experience, clinical setting, and field of expertise.

CONCLUSION

Confronting CPRs with the judgment of a group of clinicians should be an integral part of the design and validation of CPRs. Head-to-head comparison of CPRs with clinicians is also a cornerstone for defining the optimal strategy for translation into the clinical practice, and for defining which clinician and specific clinical context would benefit from using the CPR.

Characterizing Natural Recovery after Traumatic Spinal Cord Injury

The predominant tool used to predict outcomes after traumatic spinal cord injury (SCI) is the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), in association with the American Spinal Injury Association (ASIA) Impairment Scale (AIS). These measures have evolved based on analyses of large amounts of longitudinal neurological recovery data published in numerous separate studies. This article reviews and synthesizes published data on neurological recovery from multiple sources, only utilizing data in which the sacral sparing definition was applied for determination of completeness. Conversion from a complete to incomplete injury is more common in tetraplegia than paraplegia. The majority of AIS conversion and motor recovery occurs within the first 6-9 months, with the most rapid rate of motor recovery occurring in the first three months after injury. Motor score changes, as well as recovery of motor levels, are described with the initial strength of muscles as well as the levels of the motor zone of partial preservation influencing the prognosis. Total motor recovery is greater for patients with initial AIS B than AIS A, and greater after initial AIS C than with motor complete injuries. Older age has a negative impact on neurological and functional recovery after SCI; however, the specific age (whether >50 or >65 years) and underlying reasons for this impact are unclear. Penetrating injury is more likely to lead to a classification of a neurological complete injury compared with blunt trauma and reduces the likelihood of AIS conversion at one year. There are insufficient data to support gender having a major effect on neurological recovery after SCI.

An arrow that missed the mark: a pediatric case report of remarkable neurologic improvement following penetrating spinal cord injury

Penetrating spinal cord injuries are rare in children but result in devastating impacts on long-term morbidity and mortality-with little known about the recovery capacity in this age group. We present the case of an eight-year-old child who sustained a penetrating injury through the right anterior thorax. Thoracic CT showed the arrow tip extending through the spinal canal at T6. Neurologic examination revealed no motor or sensory function below T6. The arrow was surgically removed without complications through an anterior-only approach. MRI on post-operative day (POD) 4 showed focal T2 hyperintensity at the T6 spinal cord. Patient was discharged on POD33 with an American Spinal Injury Association (ASIA)-D score and trace voluntary control over bowel and bladder function. Remarkably, four months later, he had near normal bowel and bladder function, with near-intact lower extremity strength and self-sustained ambulation. Follow-up imaging revealed hemicord formation at the level of injury. We review our case of penetrating spinal cord injury in a child and similar reports in the literature. Penetrating thoracic spinal cord trauma portends poor clinical outcomes, particularly when employing available adult prognostic spinal cord injury scoring metrics. Incomplete spinal cord injury, and often-associated spinal shock, can mimic a complete injury-as in our patient, which improved to near-complete motor and sensory restoration of function and resulted in the formation of a split hemicord. This case represents a unique penetrating spinal cord injury with remarkable neurologic recovery, which would advocate against definitive early prognostication in the pediatric population.

Toward Improving the Prediction of Functional Ambulation After Spinal Cord Injury Though the Inclusion of Limb Accelerations During Sleep and Personal Factors

OBJECTIVE

To determine if functional measures of ambulation can be accurately classified using clinical measures; demographics; personal, psychosocial, and environmental factors; and limb accelerations (LAs) obtained during sleep among individuals with chronic, motor incomplete spinal cord injury (SCI) in an effort to guide future, longitudinal predictions models.

DESIGN

Cross-sectional, 1-5 days of data collection.

SETTING

Community-based data collection.

PARTICIPANTS

Adults with chronic (>1 year), motor incomplete SCI (N=27).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Ambulatory ability based on the 10-m walk test (10MWT) or 6-minute walk test (6MWT) categorized as nonambulatory, household ambulator (0.01-0.44 m/s, 1-204 m), or community ambulator (>0.44 m/s, >204 m). A random forest model classified ambulatory ability using input features including clinical measures of strength, sensation, and spasticity; demographics; personal, psychosocial, and environmental factors including pain, environmental factors, health, social support, self-efficacy, resilience, and sleep quality; and LAs measured during sleep. Machine learning methods were used explicitly to avoid overfitting and minimize the possibility of biased results.

RESULTS

The combination of LA, clinical, and demographic features resulted in the highest classification accuracies for both functional ambulation outcomes (10MWT=70.4%, 6MWT=81.5%). Adding LAs, personal, psychosocial, and environmental factors, or both increased the accuracy of classification compared with the clinical/demographic features alone. Clinical measures of strength and sensation (especially knee flexion strength), LA measures of movement smoothness, and presence of pain and comorbidities were among the most important features selected for the models.

CONCLUSIONS

The addition of LA and personal, psychosocial, and environmental features increased functional ambulation classification accuracy in a population with incomplete SCI for whom improved prognosis for mobility outcomes is needed. These findings provide support for future longitudinal studies that use LA; personal, psychosocial, and environmental factors; and advanced analyses to improve clinical prediction rules for functional mobility outcomes.

The influence of conventional T2 MRI indices in predicting who will walk outside one year after spinal cord injury

CONTEXT/OBJECTIVE

Magnetic resonance imaging (MRI) indices of spinal cord damage are predictive of future motor function after spinal cord injury (SCI): hyperintensity length, midsagittal tissue bridges, and Brain and Spinal Injury Center (BASIC) scores. Whether these indices are predictive of outdoor walking after SCI is unknown. The primary purpose was to see if these MRI indices predict the ability to walk outdoors one-year after SCI. The secondary purpose was to determine if MRI indices provide additional predictive value if initial lower extremity motor scores are available.

DESIGN

Retrospective. Clinical T₂-weighted MRIs were used to quantify spinal cord damage. Three MRI indices were calculated: midsagittal ventral tissue bridges, hyperintensity length, BASIC scores.

SETTING

Academic hospital.

PARTICIPANTS

129 participants with cervical SCI.

INTERVENTIONS

Inpatient rehabilitation.

OUTCOMES MEASURES

One year after SCI, participants self-reported their outdoor walking ability.

RESULTS

Midsagittal ventral tissue bridges, hyperintensity length, and BASIC scores significantly correlated with outdoor walking ability (R = 0.34, P < 0.001; R = -0.25, P < 0.01; Rs = -0.35, P < 001, respectively). Using midsagittal ventral tissue bridges and hyperintensity length, the final adjusted R² for model 1 = 0.19. For model 2, the adjusted R² using motor scores alone = 0.81 and MRI variables were non-significant. All five participants with observable intramedullary hemorrhage reported they were unable to walk one block outdoors.

CONCLUSIONS

The MRI indices were significant predictors of outdoor walking ability, but when motor scores were available, this was the strongest predictor and neither midsagittal tissue bridges nor hyperintensity length contributed additional value. MRI indices may be a quick and convenient supplement to physical examination when motor testing is unavailable.

Clinical utility during inpatient rehabilitation of a clinical prediction rule for ambulation prognosis following spinal cord injury

OBJECTIVE

Mobility prognosis is a key focus during rehabilitation following spinal cord injury (SCI). The goal of this study was to prospectively evaluate the clinical utility of the van Middendorp clinical prediction rule (CPR).

DESIGN

Observational study.

SETTING

Inpatient rehabilitation unit.

PARTICIPANTS

Physical therapists and their patients with acute SCI and SCI disorders (SCI/D) for whom long-term ambulation prognosis was judged difficult to determine.

INTERVENTIONS

N/A.

OUTCOME MEASURES

CPR-determined probability of ambulation, therapist reported clinical utility (yes/no), shared with the patient (yes/no), useful for motivation/setting realistic expectations, and Functional Independence Measure (FIM) Locomotion walk score.

RESULTS

Five therapists and 52 patients (8 non-traumatic SCI/D) participated. 91% had lesions classified as AIS C or D. The median [IQR] for CPR probability of ambulation was 96.0 [86.5,99.0] for traumatic SCI and 80.0 [64.5, 94.5] for non-traumatic SCI/D. Clinical utility was reported for 45% of those with SCI and 88% with non-traumatic SCI/D. Therapists with less experience were more likely to report clinical utility and share with their patients. Ambulation probability was higher for patients who did not meet their FIM goal. CPR probability was correlated with discharge FIM only for non-traumatic SCI/D.

CONCLUSION

The CPR was not predictive of inpatient rehabilitation outcomes, in fact outcomes varied widely for individuals with similar probabilities emphasizing the importance of clinical judgement and continued need to identify individual factors that affect ambulation. However, greater utility in establishing prognosis and goal setting was noted for clinicians with less experience and for individuals with non-traumatic SCI/D.

Axial MRI biomarkers of spinal cord damage to predict future walking and motor function: a retrospective study

Study design

Retrospective.

Objectives

Primary: to assess if axial damage ratios are predictors of future walking after spinal cord injury (SCI), and if they add any predictive value if initial neurological impairment grades are available. Secondary: to determine if lateral spinal cord regions are predictors of future lower extremity motor scores (LEMS).

Setting

University/hospital.

Methods

Axial T₂-weighted MRIs were used. Axial damage ratios and non-damaged lateral cord volumes were calculated. Each participant answered at 1 year after SCI, “Are you able to walk for 150 feet? (45.72 meters)” For the secondary aim, right and left LEMS were used.

Results

In total, 145 participants were selected. Individuals that could walk had smaller ratios than those that were unable. Walking and axial damage ratios were negatively correlated. A 0.374 ratio cut-off showed optimal sensitivity/specificity. When initial neurological grades were used, axial damage ratios did not add predictive value. Forty-two participants had LEMS available and were included for the secondary aim. Right cord regions and right LEMS were positively correlated and left regions and left LEMS, but these variables were also correlated with each other.

Conclusions

Axial damage ratios were significant predictors of walking ability 1 year after SCI. However, this measure did not add predictive value over initial neurological grades. Lateral cord regions correlated with same-side LEMS, but the opposite was also found, calling this biomarker’s specificity into question. Axial damage ratios may be useful in predicting walking after SCI if initial neurological grades are unavailable.

Sponsorship

This research was funded by a National Institutes of Health award, National Institute of Child Health and Development—NIH R03HD094577.

The effect of age and injury severity on clinical prediction rules for ambulation among individuals with spinal cord injury

BACKGROUND CONTEXT

While several models for predicting independent ambulation early after traumatic spinal cord injury (SCI) based upon age and specific motor and sensory level findings have been published and validated, their accuracy, especially in individual American Spinal Injury Association [ASIA] Impairment Scale (AIS) classifications, has been questioned. Further, although age is widely used in prediction rules, its role and possible modifications have not been adequately evaluated until now.

PURPOSE

To evaluate the predictive accuracy of existing clinical prediction rules for independent ambulation among individuals at spinal cord injury model systems (SCIMS) Centers as well as the effect of modifying the age parameter from a cutoff of 65 years to 50 years.

STUDY DESIGN

Retrospective analysis of a longitudinal database.

PATIENT SAMPLE

Adult individuals with traumatic SCI.

OUTCOME MEASURES

The FIM locomotor score was used to assess independent walking ability at the 1-year follow-up.

METHODS

In all, 639 patients were enrolled in the SCIMS database between 2011 and 2015, with complete neurological examination data within 15 days following the injury and a follow-up assessment with functional independence measure (FIM) at 1-year post injury. Two previously validated logistic regression models were evaluated for their ability to predict independent walking at 1-year post injury with participants in the SCIMS database. Area under the receiver operating curve (AUC) was calculated for the individual AIS categories and for different age groups. Prediction accuracy was also calculated for a new modified LR model (with cut-off age of 50).

RESULTS

Overall AUC for each of the previous prediction models was found to be consistent with previous reports (0.919 and 0.904). AUCs for grouped AIS levels (A+D, B+C) were consistent with prior reports, moreover, prediction for individual AIS grades continued to reveal lower values. AUCs by different age categories showed a decline in prognostication accuracy with an increase in age, with statistically significant improvement of AUC when age-cut off was reduced to 50.

CONCLUSIONS

We confirmed previous results that former prediction models achieve strong prognostic accuracy by combining AIS subgroups, yet prognostication of the separate AIS groups is less accurate. Further, prognostication of persons with AIS B+C, for whom a clinical prediction model has arguably greater clinical utility, is less accurate than those with AIS A+D. Our findings emphasize that age is an important factor in prognosticating ambulation following SCI. Prediction accuracy declines for older individuals compared with younger ones. To improve prediction of independent ambulation, the age of 50 years may be a better cutoff instead of age of 65.

Gap Analysis Regarding Prognostication in Neurocritical Care: A Joint Statement from the German Neurocritical Care Society and the Neurocritical Care Society

Background/Objective

Prognostication is a routine part of the delivery of neurocritical care for most patients with acute neurocritical illnesses. Numerous prognostic models exist for many different conditions. However, there are concerns about significant gaps in knowledge regarding optimal methods of prognostication.

Methods

As part of the Arbeitstagung NeuroIntensivMedizin meeting in February 2018 in Würzburg, Germany, a joint session on prognostication was held between the German NeuroIntensive Care Society and the Neurocritical Care Society. The purpose of this session was to provide presentations and open discussion regarding existing prognostic models for eight common neurocritical care conditions (aneurysmal subarachnoid hemorrhage, intracerebral hemorrhage, acute ischemic stroke, traumatic brain injury, traumatic spinal cord injury, status epilepticus, Guillain–Barré Syndrome, and global cerebral ischemia from cardiac arrest). The goal was to develop a qualitative gap analysis regarding prognostication that could help inform a future framework for clinical studies and guidelines.

Results

Prognostic models exist for all of the conditions presented. However, there are significant gaps in prognostication in each condition. Furthermore, several themes emerged that crossed across several or all diseases presented. Specifically, the self-fulfilling prophecy, lack of accounting for medical comorbidities, and absence of integration of in-hospital care parameters were identified as major gaps in most prognostic models.

Conclusions

Prognostication in neurocritical care is important, and current prognostic models are limited. This gap analysis provides a summary assessment of issues that could be addressed in future studies and evidence-based guidelines in order to improve the process of prognostication.

Task-Specific Versus Impairment-Based Training on Locomotor Performance in Individuals With Chronic Spinal Cord Injury: A Randomized Crossover Study

Background. Many research studies attempting to improve locomotor function following motor incomplete spinal cord injury (iSCI) focus on providing stepping practice. However, observational studies of physical therapy strategies suggest the amount of stepping practice during clinical rehabilitation is limited; rather, many interventions focus on mitigating impairments underlying walking dysfunction. Objective. The purpose of this blinded-assessor randomized trial was to evaluate the effects of task-specific versus impairment-based interventions on walking outcomes in individuals with iSCI. Methods. Using a crossover design, ambulatory participants with iSCI >1-year duration performed either task-specific (upright stepping) or impairment-based training for up to 20 sessions over ≤6 weeks, with interventions alternated after >4 weeks delay. Both strategies focused on achieving higher cardiovascular intensities, with training specificity manipulated by practicing only stepping practice in variable contexts or practicing tasks targeting impairments underlying locomotor dysfunction (strengthening, balance tasks, and recumbent stepping). Results. Significantly greater increases in fastest overground and treadmill walking speeds were observed following task-specific versus impairment-based training, with moderate associations between differences in amount of practice and outcomes. Gains in balance confidence were also observed following task-specific vs impairment-based training, although incidence of falls was also increased with the former protocol. Limited gains were observed with impairment-based training except for peak power during recumbent stepping tests. Conclusion. The present study reinforces work from other patient populations that the specificity of task practice is a critical determinant of locomotor outcomes and suggest impairment-based exercises may not translate to improvements in functional tasks. Clinical Trial Registration URL. https://clinicaltrials.gov/ ; Unique Identifier: NCT02115685.

Task-Specific Versus Impairment-Based Training on Locomotor Performance in Individuals With Chronic Spinal Cord Injury: A Randomized Crossover Study

Background. Many research studies attempting to improve locomotor function following motor incomplete spinal cord injury (iSCI) focus on providing stepping practice. However, observational studies of physical therapy strategies suggest the amount of stepping practice during clinical rehabilitation is limited; rather, many interventions focus on mitigating impairments underlying walking dysfunction. Objective. The purpose of this blinded-assessor randomized trial was to evaluate the effects of task-specific versus impairment-based interventions on walking outcomes in individuals with iSCI. Methods. Using a crossover design, ambulatory participants with iSCI >1-year duration performed either task-specific (upright stepping) or impairment-based training for up to 20 sessions over ≤6 weeks, with interventions alternated after >4 weeks delay. Both strategies focused on achieving higher cardiovascular intensities, with training specificity manipulated by practicing only stepping practice in variable contexts or practicing tasks targeting impairments underlying locomotor dysfunction (strengthening, balance tasks, and recumbent stepping). Results. Significantly greater increases in fastest overground and treadmill walking speeds were observed following task-specific versus impairment-based training, with moderate associations between differences in amount of practice and outcomes. Gains in balance confidence were also observed following task-specific vs impairment-based training, although incidence of falls was also increased with the former protocol. Limited gains were observed with impairment-based training except for peak power during recumbent stepping tests. Conclusion. The present study reinforces work from other patient populations that the specificity of task practice is a critical determinant of locomotor outcomes and suggest impairment-based exercises may not translate to improvements in functional tasks. Clinical Trial Registration URL. https://clinicaltrials.gov/ ; Unique Identifier: NCT02115685.

Plasma Erythropoietin, IL-17A, and IFNγ as Potential Biomarkers of Motor Function Recovery in a Canine Model of Spinal Cord Injury

Traumatic spinal cord injury (SCI) is a devastating neurological disease for which an accurate, cost-effective prediction of motor function recovery is in pressing need. A plethora of neurochemical changes involved in the pathophysiological process of SCI may serve as a new source of biomarkers for patient outcomes. Five dogs were included in this study. We characterized the plasma cytokine profiles in acute phase (0, 1, and 3 days after SCI) and subacute phase (7, 14, and 21 days after SCI) with microarray analysis. The motor function recovery following SCI was monitored by Olby scores. The expression level of differentially expressed proteins (DEPs) was measured with enzyme-linked immunosorbent assay (ELISA). Then, correlations with the Olby scores and receiver operating characteristic curve (ROC) analysis were performed. We identified 12 DEPs including 10 pro-inflammatory and 2 anti-inflammatory cytokines during the 21-day study period. Among those, the expression levels of erythropoietin (EPO), IL-17A, and IFNγ significantly correlated with the Olby scores with R² values of 0.870, 0.740, and 0.616, respectively. The results of the ROC analysis suggested that plasma EPO, IL-17A, and IFNγ exhibited a significant predictive power with an area under the curve (AUC) of 0.656, 0.848, and 0.800 for EPO, IL-17A, and IFNγ, respectively. Our results provide a longitudinal description of the changes in plasma cytokine expression in the acute and subacute stages of canine SCI. These data reveal novel panels of inflammation-related cytokines which have the potential to be evaluated as biomarkers for predicting motor function prognosis after SCI.

Therapeutic Interventions to Improve Mobility with Spinal Cord Injury Related Upper Motor Neuron Syndromes

Mobility is essential for quality of life and social participation. Some individuals with spinal cord injury have sufficient residual lower extremity motor control to walk. Improving walking function incorporates practice and training, and assistive devices or stimulation to augment function and balance. Overground robotic exoskeletons may have the potential to transform upright mobility in the future. Most individuals with spinal cord injury use a wheelchair for at least some of their mobility needs. Wheelchair skills training can open up new possibilities for participation. Regardless of the means of mobility, developing habits that protect joint health are essential for optimal lifelong mobility.

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.

Advances in the Rehabilitation of the Spinal Cord-Injured Patient: The Orthopaedic Surgeons' Perspective

Acute traumatic spinal cord injury is a devastating condition affecting 17,700 new patients per year in the United States alone. Typically, orthopaedic surgeons focus on managing the acute surgical aspects of care (eg, surgical spinal decompression and stabilization). However, in the care of these patients, being familiar with how to prognosticate neurologic recovery and manage secondary complications is extremely important. In addition, as an integral part of the multidisciplinary care team, the surgeon should have an awareness of contemporary rehabilitation approaches to maximize function and facilitate reintegration into the community. The purpose of this review article is to provide a surgeon's perspective on these aspects of spinal cord injury care.

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.

The acute phase serum zinc concentration is a reliable biomarker for predicting the functional outcome after spinal cord injury

Background

Spinal cord injury (SCI) is a devastating disorder for which the accurate prediction of the functional prognosis is urgently needed. Due to the lack of reliable prediction methods, the acute evaluation of SCI severity and therapeutic intervention efficacy is extremely difficult, presenting major obstacles to the development of acute SCI treatment. We herein report a novel method for accurately predicting the functional prognosis using the acute-phase serum zinc concentration after SCI.

Methods

We produced experimental animal SCI models with different prognoses and examined the relationship among the SCI severity, functional outcome, and acute-phase serum zinc concentration. We also examined whether we could predict the functional prognosis by evaluating the serum zinc concentration within 72 h after SCI in a human prospective study.

Findings

In a mouse model, the acute serum zinc concentrations decreased in proportion to SCI severity and the serum zinc concentrations at 12 h after SCI accurately predicted the functional prognosis. We clarified the mechanism underlying this serum zinc proportional decrease, showing that activated monocytes took up zinc from blood-serum and then infiltrated the lesion area in a severity-dependent manner. A non-linear regression analysis of 38 SCI patients showed that the serum zinc concentrations in the acute-phase accurately predicted the long-term functional outcome (R² = 0·84) more accurately than any other previously reported acute-phase biomarkers.

Interpretation

The acute-phase serum zinc concentration could be a useful biomarker for predicting the functional prognosis. This simple method will allow for more objective clinical trials and the development of patient-tailored treatment for SCI.

Systematic scoping review protocol for clinical prediction rules (CPRs) in the management of patients with spinal cord injuries

INTRODUCTION

The upsurge in the use of clinical prediction models in general medical practice is a result of evidence-based practice. However, the total number of clinical prediction rules (CPRs) currently being used or undergoing impact analysis in the management of patients who have sustained spinal cord injuries (SCIs) is unknown. This scoping review protocol will describe the current CPRs being used and highlight their possible strengths and weaknesses in SCI management.

METHODS AND ANALYSIS

Arksey and O'Malley's scoping review framework will be used. The following databases will be searched to identify relevant literature relating to the use of CPRs in the management of patients who have sustained an SCI: PubMed, Cumulative Index of Nursing and Allied Health Literature (CINAHL), ScienceDirect, EBSCOhost, Medline, OvidMedline and Google Scholar. Grey literature as well as reference lists of included studies will be searched. All studies relating to the use of CPRs in the management of patients with SCIs will be included. Literature searches and data extraction will be performed independently by two groups of reviewers.

ETHICS AND DISSEMINATION

Ethical clearance is not required for this scoping review study since only secondary data sources will be used. The findings of this review will be disseminated by means of peer-reviewed publication and conference proceedings. The final paper will be submitted for publication. Results of this review will also be presented at relevant conferences and disseminated to important stakeholders such as practicing physicians within specialised spinal care facilities within South Africa.

Dichotomous Locomotor Recoveries Are Predicted by Acute Changes in Segmental Blood Flow after Thoracic Spinal Contusion Injuries in Pigs

Neuroimaging facilitates the translation of animal pre-clinical research to human application. The large porcine spinal cord is useful for testing invasive interventions. Ideally, the safety and efficacy of a delayed intervention is tested in pigs that have recovered sufficiently after spinal cord injury (SCI) to allow either deterioration or improvement of function to be detected. We set out to create moderate severity T9 injuries in Yucatan minipigs by conducting a bridging study adapting methods previously developed in infant piglets. The injury severity was varied according to two pneumatic impactor parameters: the piston compression depth into tissue or the velocity. To stratify locomotor recovery, a 10-point scale used in prior piglet studies was redefined through longitudinal observations of spontaneous recovery. Using hindlimb body weight support to discriminate injury severity, we found that end-point recovery was strongly bimodal to either non-weight-bearing plegia with reciprocating leg movements (<5/10) or recovery of weight bearing that improved toward a ceiling effect (≥ 8/10). No intermediate recovery animals were observed at 2 months post-injury. The ability of intra-operative ultrasound and acute magnetic resonance imaging (MRI) to provide immediate predictive feedback regarding tissue and vascular changes following SCI was assessed. There was an inverse association between locomotor outcome and early gray matter hemorrhage on MRI and ultrasound. Epicenter blood flow following contusion predicted recovery or non-recovery of weight-bearing. The depth of the dorsal cerebrospinal fluid space, which varied between animals, influenced injury severity and confounded the results in this fixed-stroke paradigm.

Lower extremity outcome measures: considerations for clinical trials in spinal cord injury

STUDY DESIGN

This is a focused review article.

OBJECTIVES

To identify important concepts in lower extremity (LE) assessment with a focus on locomotor outcomes and provide guidance on how existing outcome measurement tools may be best used to assess experimental therapies in spinal cord injury (SCI). The emphasis lies on LE outcomes in individuals with complete and incomplete SCI in Phase II-III trials.

METHODS

This review includes a summary of topics discussed during a workshop focusing on LE function in SCI, conceptual discussion of corresponding outcome measures and additional focused literature review.

RESULTS

There are a number of sensitive, accurate, and responsive outcome tools measuring both quantitative and qualitative aspects of LE function. However, in trials with individuals with very acute injuries, a baseline assessment of the primary (or secondary) LE outcome measure is often not feasible.

CONCLUSION

There is no single outcome measure to assess all individuals with SCI that can be used to monitor changes in LE function regardless of severity and level of injury. Surrogate markers have to be used to assess LE function in individuals with severe SCI. However, it is generally agreed that a direct measurement of the performance for an appropriate functional activity supersedes any surrogate marker. LE assessments have to be refined so they can be used across all time points after SCI, regardless of the level or severity of spinal injury.

SPONSORS

Craig H. Neilsen Foundation, Spinal Cord Outcomes Partnership Endeavor.