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

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

Factors Associated with Recovery in Motor Strength, Walking Ability, and Bowel and Bladder Function after Traumatic Cauda Equina Injury.

Traumatic cauda equina injury (TCEI) is usually caused by spine injury at or below L1 and can result in motor and/or sensory impairments and/or neurogenic bowel and bladder. We examined factors associated with recovery in motor strength, walking ability, and bowel and bladder function to aid in prognosis and establishing rehabilitation goals. The analysis cohort was comprised of persons with acute TCEI enrolled in the Rick Hansen Spinal Cord Injury Registry. Multi-variable regression analysis was used to determine predictors for lower-extremity motor score (LEMS) at discharge, walking ability at discharge as assessed by the walking subscores of either the Functional Independence Measure (FIM) or Spinal Cord Independence Measure (SCIM), and improvement in bowel and bladder function as assessed by FIM-relevant subscores. Age, sex, neurological level and severity of injury, time from injury to surgery, rehabilitation onset, and length of stay were examined as potential confounders. The cohort included 214 participants. Median improvement in LEMS was 4 points. Fifty-two percent of participants were able to walk, and >20% recovered bowel and bladder function by rehabilitation discharge. Multi-variable analyses revealed that shorter time from injury to rehabilitation admission (onset) was a significant predictor for both improvement in walking ability and bowel function. Longer rehabilitation stay and being an older female were associated with improved bladder function. Our results suggest that persons with TCEI have a reasonable chance of recovery in walking ability and bowel and bladder function. This study provides important information for rehabilitation goals setting and communication with patients and their families regarding prognosis.

Community acquired pressure injuries in a work-related spinal cord injury population: Problem characterization and assessment of a working solution.

BACKGROUND: To characterize the problem of community-acquired pressure injuries (CAPIs) in a work-related spinal cord injury (SCI) population in Canada and assess the benefits of a person-centered solution. Characterization of the problem and a solution, albeit in an insured Worker's Compensation Board of British Columbia (WorkSafeBC) cohort, may inform the supply of solutions in the larger SCI population with disparate access to healthcare. METHODS: For this observational study, data on 244 WorkSafeBC clients, who received an intervention featuring pressure injury (PI) assessment between 2011 and 2015, were used to characterize the problem. Data on observed injuries, risk, referrals, and outcomes were linked to healthcare service claims. Employing an activity-based costing methodology, total expenditures on attributed services were calculated for clients with 1 or more PIs. Intervention cost and benefits from the insurer's perspective are considered. RESULTS: 84 of 244 clients had 1 or more PIs at assessment, with attributed mean cost of $56,092 in 2015 Canadian dollars (CAD). Mean cost by PI severity range from $9580 to $238,736. At an intervention cost of $820,618, detection of less severe injuries provided an opportunity to prevent progression and achieve $3 million in cost avoidance. Follow-up data suggest reasonable returns. Reductions in the incidence, number, and risk of pressure injuries were also observed. CONCLUSIONS: The analysis establishes the cost of CAPIs in a Canadian-based work-related SCI population and suggests preventative and early intervention is not only feasible but also practical. Results are relevant to decisions regarding the use of proactive prevention-based treatment models as opposed to reactive, solutions in the larger SCI population.

In-Hospital Mortality for the Elderly with Acute Traumatic Spinal Cord Injury.

As the incidence of traumatic spinal cord injury (tSCI) in the elderly rises, clinicians are increasingly faced with difficult discussions regarding aggressiveness of management, likelihood of recovery, and survival. Our objective was to outline risk factors associated with in-hospital mortality in elderly surgical and non-surgical patients following tSCI and to determine those unlikely to have a favorable outcome. Data from elderly patients (≥ 65 years of age) in the Canadian Rick Hansen SCI Registry from 2004 to 2017 were analyzed using descriptive analysis. Survival and mortality groups in each of the surgical and non-surgical group were compared to explore factors associated with in-hospital mortality and their impact, using logistical regression. Of 1340 elderly patients, 1018 had surgical data with 826 having had surgery. In the surgical group, the median time to death post-injury was 30 days with 75% dying within 50 days compared with 7 days and 20 days, respectively, in the non-surgical group. Significant predictors for in-hospital mortality following surgery are age, comorbidities, neurological injury severity (American Spinal Injury Association [ASIA] Impairment Scale [AIS]), and ventilation status. The odds of dying 50 days post-surgery are six times higher for patients ≥77 years of age versus those 65-76 years of age, five times higher for those with AIS A versus those with AIS B/C/D, and seven times higher for those who are ventilator dependent. An expected probability of dying within 50 days post-surgery was determined using these results. In-hospital mortality in the elderly after tSCI is high. The trend with age and time to death and the significant predictors of mortality identified in this study can be used to inform clinical decision making and discussions with patients and their families.

Correction: The influence of neurological examination timing within hours after acute traumatic spinal cord injuries: an observational study.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

Effect of Frailty on Outcome after Traumatic Spinal Cord Injury.

Frailty negatively affects outcome in elective spine surgery populations. This study sought to determine the effect of frailty on patient outcome after traumatic spinal cord injury (tSCI). Patients with tSCI were identified from our prospectively collected database from 2004 to 2016. We examined effect of patient age, admission Total Motor Score (TMS), and Modified Frailty Index (mFI) on adverse events (AEs), acute length of stay (LOS), in-hospital mortality, and discharge destination (home vs. other). Subgroup analysis (for three age groups: <60, 61-75, and 76+ years), and multi-variable analysis was performed to investigate the impact of age, TMS, and mFI on outcome. For the 634 patients, the mean age was 50.3 years, 77% were male, and falls were the main cause of injury (46.5%). On bivariate analysis, mFI, age at injury, and TMS were predictors of AEs, acute LOS, and in-hospital mortality. After statistical adjustment, mFI was a predictor of LOS (p = 0.0375), but not of AEs (p = 0.1428) or in-hospital mortality (p = 0.1245). In patients <60 years of age, mFI predicted number of AEs, acute LOS, and in-hospital mortality. In those aged 61-75, TMS predicted AEs, LOS, and mortality. In those 76+ years of age, mFI no longer predicted outcome. Age, mFI, and TMS on admission are important determinants of outcome in patients with tSCI. mFI predicts outcomes in those <75 years of age only. The inter-relationship of advanced age and decreased physiological reserve is complex in acute tSCI, warranting further study. Identifying frailty in younger patients with tSCI may be useful for peri-operative optimization, risk stratification, and patient counseling.

The influence of neurological examination timing within hours after acute traumatic spinal cord injuries: an observational study.

STUDY DESIGN: Cohort study. OBJECTIVES: It is widely accepted that the prediction of long-term neurologic outcome after traumatic spinal cord injury (SCI) can be done more accurately with neurological examinations conducted days to weeks post injury. However, modern clinical trials of neuroprotective interventions often require patients be examined and enrolled within hours. Our objective was to determine whether variability in timing of neurological examinations within 48 h after SCI is associated with differences in observations of follow-up neurologic recovery. SETTING: Level I trauma hospital. METHODS: An observational analysis testing for differences in AIS conversion rates and changes in total motor scores by neurological examination timing, controlling for potential confounders with multivariate stepwise regression. RESULTS: We included 85 patients, whose mean times from injury to baseline and follow-up examinations were 11.8 h (SD 9.8) and 208.2 days (SD 75.2), respectively. AIS conversion by 1+ grade was significantly more likely in patients examined at ≤4 h in comparison with later examination (78% versus 47%, RR = 1.66, p = 0.04), even after controlling for timing of surgery, age, and sex (OR 5.0, 95% CI 1.1-10, p = 0.04). We failed to identify any statistically significant associations for total motor score recovery in unadjusted or adjusted analyses. CONCLUSIONS: AIS grade conversion was significantly more likely in those examined ≤4 h of injury; the effect of timing on motor scores remains uncertain. Variability in neurological examination timing within hours after acute traumatic SCI may influence observations of long-term neurological recovery, which could introduce bias or lead to errors in interpretation of studies of therapeutic interventions.

Exploring the relationship between self-reported urinary tract infections to quality of life and associated conditions: insights from the spinal cord injury Community Survey.

STUDY DESIGN: Descriptive study OBJECTIVES: Urinary tract infections (UTIs) are one of the most frequent types of infections following spinal cord injury (SCI). Here we assess the relationship between frequency of UTIs and activity level/overall quality of life (QOL) measures, determine the frequency of temporally associated conditions associated with UTI and identify factors associated with frequent UTIs. SETTING: Canada METHODS: The Spinal Cord Injury Community Survey was developed to assess major dimensions of community living and health outcomes in persons with chronic SCI in Canada. Participants were stratified by self-reported UTI frequency. The relationship between UTI frequency and QOL, health resource utilization, and temporally associated conditions were assessed. Results were analysed with cross tabulations, χ2 tests, and ordinal logistic regression. RESULTS: Overall 73.5% of participants experienced at least one self-reported UTI since the time of injury (mean 18.5 years). Overall QOL was worse with increasing frequency of these events. Those with frequent self-reported UTIs had twice as many hospitalizations and doctors' visits and were limited in financial, vocational and leisure situations, physical health and ability to manage self-care as compared with those with no UTIs. Self-reported UTIs were associated with higher incidence of temporally associated conditions including bowel incontinence, constipation, spasticity, and autonomic dysreflexia. Individuals who were younger and female were more likely to have frequent UTIs and those with constipation and autonomic dysreflexia had worse QOL. CONCLUSIONS: Higher frequency self-reported UTIs is related to poor QOL of individuals with long-term SCI. These findings will be incorporated into SCI UTI surveillance and management guidelines.

Decision tree analysis to better control treatment effects in spinal cord injury clinical research.

OBJECTIVE: The aim of this study was to use decision tree modeling to identify optimal stratification groups considering both the neurological impairment and spinal column injury and to investigate the change in motor score as an example of a practical application. Inherent heterogeneity in spinal cord injury (SCI) introduces variation in natural recovery, compromising the ability to identify true treatment effects in clinical research. Optimized stratification factors to create homogeneous groups of participants would improve accurate identification of true treatment effects. METHODS: The analysis cohort consisted of patients with acute traumatic SCI registered in the Vancouver Rick Hansen Spinal Cord Injury Registry (RHSCIR) between 2004 and 2014. Severity of neurological injury (American Spinal Injury Association Impairment Scale [AIS grades A-D]), level of injury (cervical, thoracic), and total motor score (TMS) were assessed using the International Standards for Neurological Classification of Spinal Cord Injury examination; morphological injury to the spinal column assessed using the AOSpine classification (AOSC types A-C, C most severe) and age were also included. Decision trees were used to determine the most homogeneous groupings of participants based on TMS at admission and discharge from in-hospital care. RESULTS: The analysis cohort included 806 participants; 79.3% were male, and the mean age was 46.7 ± 19.9 years. Distribution of severity of neurological injury at admission was AIS grade A in 40.0% of patients, grade B in 11.3%, grade C in 18.9%, and grade D in 29.9%. The level of injury was cervical in 68.7% of patients and thoracolumbar in 31.3%. An AOSC type A injury was found in 33.1% of patients, type B in 25.6%, and type C in 37.8%. Decision tree analysis identified 6 optimal stratification groups for assessing TMS: 1) AOSC type A or B, cervical injury, and age ≤ 32 years; 2) AOSC type A or B, cervical injury, and age > 32-53 years; 3) AOSC type A or B, cervical injury, and age > 53 years; 4) AOSC type A or B and thoracic injury; 5) AOSC type C and cervical injury; and 6) AOSC type C and thoracic injury. CONCLUSIONS: Appropriate stratification factors are fundamental to accurately identify treatment effects. Inclusion of AOSC type improves stratification, and use of the 6 stratification groups could minimize confounding effects of variable neurological recovery so that effective treatments can be identified.

Unbiased Recursive Partitioning to Stratify Patients with Acute Traumatic Spinal Cord Injuries: External Validity in an Observational Cohort Study.

Clinical trials of novel therapies for acute spinal cord injury (SCI) are challenging because variability in spontaneous neurologic recovery can make discerning actual treatment effects difficult. Unbiased Recursive Partitioning regression with Conditional Inference Trees (URP-CTREE) is a novel approach developed through analyses of a large European SCI database (European Multicenter Study about Spinal Cord Injury). URP-CTREE uses early neurologic impairment to predict achieved motor recovery, with potential to optimize clinical trial design by optimizing patient stratification and decreasing sample sizes. We performed external validation to determine how well a previously reported URP-CTREE model stratified patients into distinct homogeneous subgroups and predicted subsequent neurologic recovery in an independent cohort. We included patients with acute cervical SCI level C4-C6 from a prospective registry at a quaternary care center from 2004-2018 (n = 101) and applied the URP-CTREE model and evaluated Upper Extremity Motor Score (UEMS) recovery, considered correctly predicted when final UEMS scores were within a pre-specified threshold of 9 points from median; sensitivity analyses evaluated the effect of timing of baseline neurological examination. We included 101 patients, whose mean times from injury baseline and follow-up examinations were 6.1 days (standard deviation [SD] 17) and 235.0 days (SD 71), respectively. Median UEMS recovery was 7 points (interquartile range 2-12). One of the predictor variables was not statistically significant in our sample; one group did not fit progressively improving UEMS scores, and three of five groups had medians that were not significantly different from adjacent groups. Overall accuracy was 75%, but varied from 82% among participants whose examinations occurred at <12 h, to 64% at 12-24 h, and 58% at >24 h. A previous URP-CTREE model had limited ability to stratify an independent into homogeneous subgroups. Overall accuracy was promising, but may be sensitive to timing of baseline neurological examinations. Further evaluation of external validity in incomplete injuries, influence of timing of baseline examinations, and investigation of additional stratification strategies is warranted.

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.

Quality of Life and Adaptation in People With Spinal Cord Injury: Response Shift Effects From 1 to 5 Years Postinjury.

OBJECTIVE: To investigate response shift effects in spinal cord injury (SCI) over 5 years postinjury. DESIGN: Prospective cohort study observed at 1, 2, and 5 years post-SCI. SETTING: Specialized SCI centers. PARTICIPANTS: Sample included 1125, 760, and 219 participants at 1, 2, and 5 years post-SCI (N = 2104). The study sample was 79% men; 39% were motor/sensory complete (mean age, 44.6±18.3y). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Patient-reported outcomes included the Medical Outcomes Study 36-Item Short-Form Health Survey version 2 and the Life Satisfaction-11 Questionnaire. Participant latent variable scores were adjusted for (1) potential attrition bias and (2) propensity scores reflecting risk of worse outcomes. The Oort structural equation modeling approach for detecting and accounting for response shift effects was used to test the hypothesis that people with SCI would undergo response shifts over follow-up. RESULTS: The study data comprised the time after FIM scores, an objective measure of motor and cognitive function, had improved and stabilized. Three latent variables (Physical, Mental, and Symptoms) were modeled over time. The response shift model indicated uniform recalibration and reconceptualization response shift effects over time. When adjusted for these response shift effects, Physical showed small true change improvements at 2- and 5-year follow-up, despite FIM stability. CONCLUSIONS: We detected recalibration and reconceptualization response shift effects in 1- to 5-year follow-up of people with SCI. Despite stable motor and cognitive function, people with SCI are adapting to their condition. This adaptation reflects a progressive disconnection between symptoms and physical or mental health, and a real improvement in the Physical latent variable.

The impact of spine stability on cervical spinal cord injury with respect to demographics, management, and outcome: a prospective cohort from a national spinal cord injury registry.

BACKGROUND CONTEXT: Emergent surgery for patients with a traumatic spinal cord injury (SCI) is seen as the gold standard in acute management. However, optimal treatment for those with the clinical diagnosis of central cord syndrome (CCS) is less clear, and classic definitions of CCS do not identify a unique population of patients. PURPOSE: The study aimed to test the authors' hypothesis that spine stability can identify a unique group of patients with regard to demographics, management, and outcomes, which classic CCS definitions do not. STUDY DESIGN/SETTING: This is a prospective observational study. PATIENT SAMPLE: The sample included participants with cervical SCI included in a prospective Canadian registry. OUTCOME MEASURES: The outcome measures were initial hospitalization length of stay, change in total motor score from admission to discharge, and in-hospital mortality. METHODS: Patients with cervical SCI from a prospective Canadian SCI registry were grouped into stable and unstable spine cohorts. Bivariate analyses were used to identify differences in demographic, injury, management, and outcomes. Multivariate analysis was used to better understand the impact of spine stability on motor score improvement. No conflicts of interest were identified. RESULTS: Compared with those with an unstable spine, patients with cervical SCI and a stable spine were older (58.8 vs. 44.1 years, p<.0001), more likely male (86.4% vs. 76.1%, p=.0059), and have more medical comorbidities. Patients with stable spine cervical SCI were more likely to have sustained their injury by a fall (67.4% vs. 34.9%, p<.0001), and have high cervical (C1-C4; 58.5% vs. 43.3%, p=.0009) and less severe neurologic injuries (ASIA Impairment Scale C or D; 81.3% vs. 47.5%, p<.0001). Those with stable spine injuries were less likely to have surgery (67.6% vs. 92.6%, p<.0001), had shorter in-hospital lengths of stay (median 84.0 vs. 100.5 days, p=.0062), and higher total motor score change (20.7 vs. 19.4 points, p=.0014). Multivariate modeling revealed that neurologic severity of injury and spine stability were significantly related to motor score improvement; patients with stable spine injuries had more motor score improvement. CONCLUSIONS: We propose that classification of stable cervical SCI is more clinically relevant than classic CCS classification as this group was found to be unique with regard to demographics, neurologic injury, management, and outcome, whereas classic CCS classifications do not . This classification can be used to assess optimal management in patients where it is less clear if and when surgery should be performed.

Health Conditions: Effect on Function, Health-Related Quality of Life, and Life Satisfaction After Traumatic Spinal Cord Injury. A Prospective Observational Registry Cohort Study.

OBJECTIVE: To analyze relations among injury, demographic, and environmental factors on function, health-related quality of life (HRQoL), and life satisfaction in individuals with traumatic spinal cord injury (SCI). DESIGN: Prospective observational registry cohort study. SETTING: Specialized acute and rehabilitation SCI centers. PARTICIPANTS: Participants (N=340) from the Rick Hansen Spinal Cord Injury Registry (RHSCIR) who were prospectively recruited from 2004 to 2014 were included. The model cohort participants were 79.1% men, with a mean age of 41.6±17.3 years. Of the participants, 34.7% were motor/sensory complete (ASIA Impairment Scale [AIS] grade A). INTERVENTIONS: None. MAIN OUTCOME MEASURES: Path analysis was used to determine relations among SCI severity (AIS grade and anatomic level [cervical/thoracolumbar]), age at injury, education, number of health conditions, functional independence (FIM motor score), HRQoL (Medical Outcomes Study 36-Item Short-Form Health Survey [Version 2] Physical Component Score [PCS] and Mental Component Score [MCS]), and life satisfaction (Life Satisfaction-11 [LiSat-11]). Model fit was assessed using recommended published indices. RESULTS: Goodness of fit of the model was supported by all indices, indicating the model results closely matched the RHSCIR data. Higher age, higher severity injuries, cervical injuries, and more health conditions negatively affected FIM motor score, whereas employment had a positive effect. Higher age, less education, more severe injuries (AIS grades A-C), and more health conditions negatively correlated with PCS (worse physical health). More health conditions were negatively correlated with a lower MCS (worse mental health), however were positively associated with reduced function. Being married and having higher function positively affected Lisat-11, but more health conditions had a negative effect. CONCLUSIONS: Complex interactions and enduring effects of health conditions after SCI have a negative effect on function, HRQoL, and life satisfaction. Modeling relations among these types of concepts will inform clinicians how to positively effect outcomes after SCI (eg, development of screening tools and protocols for managing individuals with traumatic SCI who have multiple health conditions).

Predicting rehabilitation length of stay in Canada: It's not just about impairment.

INTRODUCTION: Current tertiary Spinal Cord Injury (SCI) rehabilitation funding and rehabilitation length of stay (R-LOS) in most North American jurisdictions are linked to an individual's impairment. Our objectives were to: 1) describe the impact of relevant demographic, impairment and medical complexity variables at rehabilitation admission on R-LOS among adult Canadians with traumatic SCI; and 2) identify factors which extend R-LOS. METHODS: Data from 1,376 adults with traumatic SCI were obtained via chart abstraction and administrative data linkage from 15 Rick Hansen SCI Registry sites (2004-2014). Variables included age, sex, neurological impairment (level, severity), rehabilitation onset days, R-LOS, Glasgow Coma Score (GCS) at admission, prior ventilation or endotracheal tube (Vent/ETT), or indwelling bladder catheter at acute discharge, pain interference score, intensive care unit (ICU) length of stay (LOS), and lower extremity motor scores (LEMS) at rehabilitation admission. Variables related to R-LOS in bivariate analysis were included in multivariate analysis to determine their impact on R-LOS. RESULTS: Prior Vent/ETT tube, indwelling bladder catheter, GCS, LEMS, and neurological impairment were related to R-LOS in bivariate analysis. Multivariate linear regression analyses identified five variables as significant predictors: age, Vent/ETT for >24 hours in acute care, indwelling bladder catheter at acute discharge, LEMS, and NLI/AIS subgroup at rehabilitation admission explained 32% of the variation in R-LOS (p<0.001). CONCLUSIONS: Based on the enclosed formula, and knowledge of an individual's age at injury, spinal cord impairment (level and severity), prior Vent/ETT, presence of an indwelling bladder catheter, and LEMS at admission, administrators and clinicians may readily identify patients for whom an extended R-LOS beyond conventional LOS targets is likely.

The Economic Burden of Urinary Tract Infection and Pressure Ulceration in Acute Traumatic Spinal Cord Injury Admissions: Evidence for Comparative Economics and Decision Analytics from a Matched Case-Control Study.

Secondary complications of spinal cord injury (SCI) are a burden to affected individuals and the rest of society. There is limited evidence of the economic burden or cost of complications in SCI populations in Canada, however, which is necessary for comparative economic analyses and decision analytic modeling of possible solutions to these common health problems. Comparative economic analyses can inform resource allocation decisions, but the outputs are only as good as the inputs. In this article, new evidence of the excess or incremental costs of urinary tract infection (UTI) and pressure ulceration (PU) in acute traumatic SCI from an exploratory case series analysis of admissions to a Level I specialized Canadian spine facility (2008-2013) is presented. Participants in a national SCI registry were case-control matched (1:1) on the predicted probability of experiencing UTI or PU during initial acute SCI admission. The excess costs of UTI and PU are estimated as the mean of the differences in total direct acute SCI admission costs (length of stay, accommodation, nursing, pharmacy) from the perspective of the admitting facility between participants matched or paired on demographic and SCI characteristics. Even relatively minor UTI and PU, respectively, added an average of $7,790 (standard deviation [SD] $6,267) and $18,758 (SD $27,574) to the direct cost of acute SCI admission in 2013 Canadian dollars (CAD). This case series analysis established evidence of the excess costs of UTI and PU in acute SCI admissions, which will support decision-informing analyses in 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.

Spinal Cord Injury Clinical Registries: Improving Care across the SCI Care Continuum by Identifying Knowledge Gaps.

Timely access and ongoing delivery of care and therapeutic interventions is needed to maximize recovery and function after traumatic spinal cord injury (tSCI). To ensure these decisions are evidence-based, access to consistent, reliable, and valid sources of clinical data is required. The Access to Care and Timing Model used data from the Rick Hansen SCI Registry (RHSCIR) to generate a simulation of healthcare delivery for persons after tSCI and to test scenarios aimed at improving outcomes and reducing the economic burden of SCI. Through model development, we identified knowledge gaps and challenges in the literature and current health outcomes data collection throughout the continuum of SCI care. The objectives of this article were to describe these gaps and to provide recommendations for bridging them. Accurate information on injury severity after tSCI was hindered by difficulties in conducting neurological assessments and classifications of SCI (e.g., timing), variations in reporting, and the lack of a validated SCI-specific measure of associated injuries. There was also limited availability of reliable data on patient factors such as multi-morbidity and patient-reported measures. Knowledge gaps related to structures (e.g., protocols) and processes (e.g., costs) at each phase of care have prevented comprehensive evaluation of system performance. Addressing these knowledge gaps will enhance comparative and cost-effectiveness evaluations to inform decision-making and standards of care. Recommendations to do so were: standardize data element collection and facilitate database linkages, validate and adopt more outcome measures for SCI, and increase opportunities for collaborations with stakeholders from diverse backgrounds.