Predictive Algorithm for Surgery Recommendation in Thoracolumbar Burst Fractures Without Neurological Deficits.

STUDY DESIGN: Predictive algorithm via decision tree. OBJECTIVES: Artificial intelligence (AI) remain an emerging field and have not previously been used to guide therapeutic decision making in thoracolumbar burst fractures. Building such models may reduce the variability in treatment recommendations. The goal of this study was to build a mathematical prediction rule based upon radiographic variables to guide treatment decisions. METHODS: Twenty-two surgeons from the AO Knowledge Forum Trauma reviewed 183 cases from the Spine TL A3/A4 prospective study (classification, degree of certainty of posterior ligamentous complex (PLC) injury, use of M1 modifier, degree of comminution, treatment recommendation). Reviewers' regions were classified as Europe, North/South America and Asia. Classification and regression trees were used to create models that would predict the treatment recommendation based upon radiographic variables. We applied the decision tree model which accounts for the possibility of non-normal distributions of data. Cross-validation technique as used to validate the multivariable analyses. RESULTS: The accuracy of the model was excellent at 82.4%. Variables included in the algorithm were certainty of PLC injury (%), degree of comminution (%), the use of M1 modifier and geographical regions. The algorithm showed that if a patient has a certainty of PLC injury over 57.5%, then there is a 97.0% chance of receiving surgery. If certainty of PLC injury was low and comminution was above 37.5%, a patient had 74.2% chance of receiving surgery in Europe and Asia vs 22.7% chance in North/South America. Throughout the algorithm, the use of the M1 modifier increased the probability of receiving surgery by 21.4% on average. CONCLUSION: This study presents a predictive analytic algorithm to guide decision-making in the treatment of thoracolumbar burst fractures without neurological deficits. PLC injury assessment over 57.5% was highly predictive of receiving surgery (97.0%). A high degree of comminution resulted in a higher chance of receiving surgery in Europe or Asia vs North/South America. Future studies could include clinical and other variables to enhance predictive ability or use machine learning for outcomes prediction in thoracolumbar burst fractures.

Expert Opinion, Real-World Classification, and Decision-Making in Thoracolumbar Burst Fractures Without Neurologic Deficits?

STUDY DESIGN: Retrospective analysis of prospectively collected data. OBJECTIVES: To compare decision-making between an expert panel and real-world spine surgeons in thoracolumbar burst fractures (TLBFs) without neurological deficits and analyze which factors influence surgical decision-making. METHODS: This study is a sub-analysis of a prospective observational study in TL fractures. Twenty two experts were asked to review 183 CT scans and recommend treatment for each fracture. The expert recommendation was based on radiographic review. RESULTS: Overall agreement between the expert panel and real-world surgeons regarding surgery was 63.2%. In 36.8% of cases, the expert panel recommended surgery that was not performed in real-world scenarios. Conversely, in cases where the expert panel recommended non-surgical treatment, only 38.6% received non-surgical treatment, while 61.4% underwent surgery. A separate analysis of A3 and A4 fractures revealed that expert panel recommended surgery for 30% of A3 injuries and 68% of A4 injuries. However, 61% of patients with both A3 and A4 fractures received surgery in the real world. Multivariate analysis demonstrated that a 1% increase in certainty of PLC injury led to a 4% increase in surgery recommendation among the expert panel, while a .2% increase in the likelihood of receiving surgery in the real world. CONCLUSION: Surgical decision-making varied between the expert panel and real-world treating surgeons. Differences appear to be less evident in A3/A4 burst fractures making this specific group of fractures a real challenge independent of the level of expertise.

Classifying clinical phenotypes of functional recovery for acute traumatic spinal cord injury. An observational cohort study.

PURPOSE: Identify patient subgroups with different functional outcomes after SCI and study the association between functional status and initial ISNCSCI components. METHODS: Using CART, we performed an observational cohort study on data from 675 patients enrolled in the Rick-Hansen Registry(RHSCIR) between 2014 and 2019. The outcome was the Spinal Cord Independence Measure (SCIM) and predictors included AIS, NLI, UEMS, LEMS, pinprick(PPSS), and light touch(LTSS) scores. A temporal validation was performed on data from 62 patients treated between 2020 and 2021 in one of the RHSCIR participating centers. RESULTS: The final CART resulted in four subgroups with increasing totSCIM according to PPSS, LEMS, and UEMS: 1)PPSS < 27(totSCIM = 28.4 ± 16.3); 2)PPSS ≥ 27, LEMS < 1.5, UEMS < 45(totSCIM = 39.5 ± 19.0); 3)PPSS ≥ 27, LEMS < 1.5, UEMS ≥ 45(totSCIM = 57.4 ± 13.8); 4)PPSS ≥ 27, LEMS ≥ 1.5(totSCIM = 66.3 ± 21.7). The validation model performed similarly to the original model. The adjusted R-squared and F-test were respectively 0.556 and 62.2(P-value <0.001) in the development cohort and, 0.520 and 31.9(P-value <0.001) in the validation cohort. CONCLUSION: Acknowledging the presence of four characteristic subgroups of patients with distinct phenotypes of functional recovery based on PPSS, LEMS, and UEMS could be used by clinicians early after tSCI to plan rehabilitation and establish realistic goals. An improved sensory function could be key for potentiating motor gains, as a PPSS ≥ 27 was a predictor of a good function.

After a traumatic Spinal Cord Injury (SCI), early neurological examination using the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) is recommended to determine initial injury severity and prognosis.This study identified three initial ISNCSCI components defining four subgroups of SCI patients with different expectations in functional outcomes, namely the initial pinprick sensory score, the Lower Extremity Motor Score, and the Upper Extremity Motor Score.Clinicians could use these subgroups early after tSCI to plan rehabilitation and set realistic therapeutic goals regarding functional outcomes.In clinical practice, careful and accurate assessment of pinprick sensation early after the SCI is crucial when predicting function or stratifying patients based on the expected function.

An Economic Analysis of the Association Among Secondary Health Conditions, Health Care Costs, and Quality of Life for Persons With Spinal Cord Injury.

Background: A previous analysis using the Canadian Spinal Cord Injury (SCI) Community Survey data identified that there were individuals with a high number of secondary health conditions, high health care utilization, poor health outcomes, and unmet health care needs. Objectives: The objectives of this study were to estimate the annual health care costs of persons with SCI who report secondary health conditions, and to determine the association between these secondary health conditions with health care utilization and self-reported life satisfaction and quality of life. Methods: The survey respondents were divided into four groups: traumatic SCI (tSCI; those who said they received needed care and those who said they did not) and nontraumatic SCI (ntSCI; those who said they received needed care and those who said they did not). The average annual health care costs per respondent were estimated for each group. Using regression analysis, we estimated the change in average annual health care costs that were associated with an additional secondary health condition for respondents in each group. Results: Participants who reported not receiving needed care had on average 23% more secondary health conditions than those receiving needed care. The increase in average annual health care costs associated with one additional secondary health conditions was between $428 ($37-$820) (ntSCI, receiving needed care) and $1240 ($739-$1741) (tSCI, not receiving needed care). Conclusion: This study provides insight into potential cost savings associated with a reduction of secondary health conditions as well as an estimate of the reduction in health care costs associated with moving from not receiving all needed care to receiving needed care.

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.

Construct validity of the international standards to document remaining autonomic function after spinal cord injury (ISAFSCI) (1st edition).

STUDY DESIGN: Observational study. OBJECTIVES: To assess the construct validity of the International Standards to Document Remaining Autonomic Function after Spinal Cord Injury (ISAFSCI) (2012 1st Edition). SETTING: Two Canadian spinal cord injury (SCI) centers. METHODS: Data were collected between 2011-2014. Assessments included the ISAFSCI, standardized measures of autonomic function and a clinical examination. Construct validity of ISAFSCI was assessed by testing a priori hypotheses on expected ISAFSCI responses to standard measures (convergent hypotheses) and clinical variables (clinical hypotheses). RESULTS: Forty-nine participants with an average age of 45 ± 12 years were included, of which 42 (85.7%) were males, 37 (77.6%) had a neurological level of injury at or above T6, and 23 (46.9%) were assessed as having motor and sensory complete SCI. For the six General Autonomic Function component hypotheses, two hypotheses (1 clinical, 1 convergent) related to autonomic control of blood pressure and one clinical hypothesis for temperature regulation were statistically significant. In terms of the Lower Urinary Tract, Bowel and Sexual Function component of the ISAFSCI, all the hypotheses (5 convergent, 3 clinical) were statistically significant except for the hypotheses on female sexual items (2 convergent, 2 clinical), likely due to small sample size. CONCLUSION: The construct validity of ISAFSCI (2012 1st Edition) for the General Autonomic Function component was considered to be weak while it was much stronger for the Lower Urinary Tract, Bowel and Sexual Function component based on a priori hypotheses. These results can inform future psychometric studies of the ISAFSCI (2021 2nd Edition).

Multimorbidity in persons with non-traumatic spinal cord injury and its impact on healthcare utilization and health outcomes.

STUDY DESIGN: Cross-sectional survey in Canada. OBJECTIVES: To explore multimorbidity (the coexistence of two/more health conditions) in persons with non-traumatic spinal cord injury (NTSCI) and evaluate its impact on healthcare utilization (HCU) and health outcomes. SETTING: Community-dwelling persons. METHODS: Data from the Spinal Cord Injury Community Survey (SCICS) was used. A multimorbidity index (MMI) consisting of 30 secondary health conditions (SHCs), the 7-item HCU questionnaire, the Short Form-12 (SF-12), Life Satisfaction-11 first question, and single-item Quality of Life (QoL) measure were administered. Additionally, participants were grouped as "felt needed healthcare was received" (Group 1, n = 322) or "felt needed healthcare was not received" (Group 2, n = 89) using the HCU question. Associations among these variables were assessed using multivariable analysis. RESULTS: 408 of 412 (99%) participants with NTSCI reported multimorbidity. Constipation, spasticity, and fatigue were the most prevalent self-reported SHCs. Group 1 had a higher MMI score compared to Group 2 (p < 0.001). A higher MMI score correlated with the feeling of not receiving needed care (OR 1.4, 95% CI 1.08-1.21), lower SF-12 (physical/mental component summary scores), being unsatisfied with life, and lower QoL (all p < 0.001). Additionally, Group 1 had more females (p < 0.001), non-Caucasians (p = 0.034), and lower personal annual income (p = 0.025). CONCLUSIONS: Persons with NTSCI have multimorbidity, and the MMI score was associated with increased HCU and worse health outcomes. This work emphasizes the critical need for improved healthcare and monitoring. Future work determining specific thresholds for the MMI could be helpful for triage screening to identify persons at higher risk of poor outcomes.

Incidence and prevalence of traumatic spinal cord injury in Canada using health administrative data.

Introduction: Incidence and prevalence data are needed for the planning, funding, delivery and evaluation of injury prevention and health care programs. The objective of this study was to estimate the Canadian traumatic spinal cord injury (TSCI) incidence, prevalence and trends over time using national-level health administrative data. Methods: ICD-10 CA codes were used to identify the cases for the hospital admission and discharge incidence rates of TSCI in Canada from 2005 to 2016. Provincial estimates were calculated using the location of the admitting facility. Age and sex-specific incidence rates were set to the 2015/2016 rates for the 2017 to 2019 estimates. Annual incidence rates were used as input for the prevalence model that applied annual survivorship rates derived from life expectancy data. Results: For 2019, it was estimated that there were 1,199 cases (32.0 per million) of TSCI admitted to hospitals, with 123 (10% of admissions) in-hospital deaths and 1,076 people with TSCI (28.7 per million) were discharged in Canada. The estimated number of people living with TSCI was 30,239 (804/million); 15,533 (52%) with paraplegia and 14,706 (48%) with tetraplegia. Trends included an increase in the number of people injured each year from 874 to 1,199 incident cases (37%), an older average age at injury rising from 46.6 years to 54.3 years and a larger proportion over the age of 65 changing from 22 to 38%, during the 15-year time frame. Conclusion: This study provides a standard method for calculating the incidence and prevalence of TSCI in Canada using national-level health administrative data. The estimates are conservative based on the limitations of the data but represent a large Canadian sample over 15 years, which highlight national trends. An increasing number of TSCI cases among the elderly population due to falls reported in this study can inform health care planning, prevention strategies, and future research.

Impact of Specialized Versus Non-Specialized Acute Hospital Care on Survival Among Patients With Acute Incomplete Traumatic Spinal Cord Injuries: A Population-Based Observational Study from British Columbia, Canada.

Given the complexity of care necessitated after an acute traumatic spinal cord injury (SCI), it seems intuitively beneficial for such care to be delivered at hospitals with specialized SCI expertise. Demonstrating these benefits is not straightforward, however. We sought to determine whether specialized acute hospital care influenced the most fundamental outcomes after SCI: mortality within the first year of injury. We compared survival among patients with incomplete tSCI admitted to a single quaternary-level trauma hospital with a specialized acute SCI program versus those admitted to trauma hospitals without specialized acute SCI care. We performed a population-based retrospective observational cohort study using administrative and clinical data linked from multiple sources in British Columbia (BC) from 2001 to 2017. Among a cohort of 1920 patients, there were 193 deaths within one year. We failed to identify a significant overall benefit for survival after adjusting for potential confounders, and the confidence intervals (CIs) were compatible with both benefit and harm (odds ratio [OR] 1.01, 95% CI 0.17 to 6.11, p = 0.99). Significant associations were observed with age greater than 65 (OR 4.92, 95% CI 1.66 to 14.57, p < 0.01), Charlson Comorbidity Index (OR 1.61, 95% CI 1.42 to 1.83, p < 0.01), Injury Severity Score (OR 1.08, 95% CI 1.06 to 1.11, p < 0.01), and traumatic brain injury (OR 2.12, 95% CI 1.32 to 3.41, p < 0.01). Among patients with acute tSCI, admission to a hospital with specialized acute SCI care was not associated with improved overall one-year survival. Subgroup analyses, however, suggested heterogeneity of effects, with little benefit for older patients with less polytrauma and substantial benefit for younger patients with greater polytrauma.

Association of CSF and Serum Neurofilament Light and Glial Fibrillary Acidic Protein, Injury Severity, and Outcome in Spinal Cord Injury.

BACKGROUND AND OBJECTIVES: Traumatic spinal cord injury (SCI) is highly heterogeneous, and tools to better delineate pathophysiology and recovery are needed. Our objective was to profile the response of 2 biomarkers, neurofilament light (NF-L) and glial fibrillary acidic protein (GFAP), in the serum and CSF of patients with acute SCI to evaluate their ability to objectively characterize injury severity and predict neurologic recovery. METHODS: Blood and CSF samples were obtained from prospectively enrolled patients with acute SCI through days 1-4 postinjury, and the concentration of NF-L and GFAP was quantified using Simoa technology. Neurologic assessments defined the ASIA Impairment Scale (AIS) grade and motor score (MS) at presentation and 6 months postinjury. RESULTS: One hundred eighteen patients with acute SCI (78 AIS A, 20 AIS B, and 20 AIS C) were enrolled, with 113 (96%) completing 6-month follow-up. NF-L and GFAP levels were strongly associated between paired serum and CSF specimens, were both increased with injury severity, and distinguished among baseline AIS grades. Serum NF-L and GFAP were significantly (p = 0.02 to <0.0001) higher in AIS A patients who did not improve at 6 months, predicting AIS grade conversion with a sensitivity and specificity (95% CI) of 76% (61, 87) and 77% (55, 92) using NF-L and 72% (57, 84) and 77% (55, 92) using GFAP at 72 hours, respectively. Independent of clinical baseline assessment, a serum NF-L threshold of 170 pg/mL at 72 hours predicted those patients who would be classified as motor complete (AIS A/B) compared with motor incomplete (AIS C/D) at 6 months with a sensitivity of 87% (76, 94) and specificity of 84% (69, 94); a serum GFAP threshold of 13,180 pg/mL at 72 hours yielded a sensitivity of 90% (80, 96) and specificity of 84% (69, 94). DISCUSSION: The potential for NF-L and GFAP to classify injury severity and predict outcome after acute SCI will be useful for patient stratification and prognostication in clinical trials and inform communication of prognosis. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that higher serum NF-L and GFAP are associated with worse neurological outcome after acute SCI. TRIAL REGISTRATION INFORMATION: Registered on ClinicalTrials.gov: NCT00135278 (March 2006) and NCT01279811 (January 2012).

Pattern of neurological recovery in persons with an acute cervical spinal cord injury over the first 14 days post injury.

Introduction: Following a traumatic spinal cord injury (SCI) it is critical to document the level and severity of injury. Neurological recovery occurs dynamically after injury and a baseline neurological exam offers a snapshot of the patient's impairment at that time. Understanding when this exam occurs in the recovery process is crucial for discussing prognosis and acute clinical trial enrollment. The objectives of this study were to: (1) describe the trajectory of motor recovery in persons with acute cervical SCI in the first 14 days post-injury; and (2) evaluate if the timing of the baseline neurological assessment in the first 14 days impacts the amount of motor recovery observed. Methods: Data were obtained from the Rick Hansen Spinal Cord Injury Registry (RHSCIR) site in Vancouver and additional neurological data was extracted from medical charts. Participants with a cervical injury (C1-T1) who had a minimum of three exams (including a baseline and discharge exam) were included. Data on the upper-extremity motor score (UEMS), total motor score (TMS) and American Spinal Injury Association (ASIA) Impairment Scale (AIS) were included. A linear mixed-effect model with additional variables (AIS, level of injury, UEMS, time, time2, and TMS) was used to explore the pattern and amount of motor recovery over time. Results: Trajectories of motor recovery in the first 14 days post-injury showed significant improvements in both TMS and UEMS for participants with AIS B, C, and D injuries, but was not different for high (C1-4) vs. low (C5-T1) cervical injuries or AIS A injuries. The timing of the baseline neurological examination significantly impacted the amount of motor recovery in participants with AIS B, C, and D injuries. Discussion: Timing of baseline neurological exams was significantly associated with the amount of motor recovery in cervical AIS B, C, and D injuries. Studies examining changes in neurological recovery should consider stratifying by severity and timing of the baseline exam to reduce bias amongst study cohorts. Future studies should validate these estimates for cervical AIS B, C, and D injuries to see if they can serve as an "adjustment factor" to control for differences in the timing of the baseline neurological exam.

Network analysis of multimorbidity and health outcomes among persons with spinal cord injury in Canada.

Introduction: Multimorbidity, defined as the coexistence of two or more health conditions, is common in persons with spinal cord injury (SCI). Network analysis is a powerful tool to visualize and examine the relationship within complex systems. We utilized network analysis to explore the relationship between 30 secondary health conditions (SHCs) and health outcomes in persons with traumatic (TSCI) and non-traumatic SCI (NTSCI). The study objectives were to (1) apply network models to the 2011-2012 Canadian SCI Community Survey dataset to identify key variables linking the SHCs measured by the Multimorbidity Index-30 (MMI-30) to healthcare utilization (HCU), health status, and quality of life (QoL), (2) create a short form of the MMI-30 based on network analysis, and (3) compare the network-derived MMI to the MMI-30 in persons with TSCI and NTSCI. Methods: Three network models (Gaussian Graphical, Ising, and Mixed Graphical) were created and analyzed using standard network measures (e.g., network centrality). Data analyzed included demographic and injury variables (e.g., age, sex, region of residence, date, injury severity), multimorbidity (using MMI-30), HCU (using the 7-item HCU questionnaire and classified as "felt needed care was not received" [HCU-FNCNR]), health status (using the 12-item Short Form survey [SF-12] Physical and Mental Component Summary [PCS-12 and MCS-12] score), and QoL (using the 11-item Life Satisfaction questionnaire [LiSAT-11] first question and a single item QoL measure). Results: Network analysis of 1,549 participants (TSCI: 1137 and NTSCI: 412) revealed strong connections between the independent nodes (30 SHCs) and the dependent nodes (HCU-FNCNR, PCS-12, MCS-12, LiSAT-11, and the QoL score). Additionally, network models identified that cancer, deep vein thrombosis/pulmonary embolism, diabetes, high blood pressure, and liver disease were isolated. Logistic regression analysis indicated the network-derived MMI-25 correlated with all health outcome measures (p <0.001) and was comparable to the MMI-30. Discussion: The network-derived MMI-25 was comparable to the MMI-30 and was associated with inadequate HCU, lower health status, and poor QoL. The MMI-25 shows promise as a follow-up screening tool to identify persons living with SCI at risk of having poor health outcomes.

Effect of body mass index on survival after spinal cord injury.

Introduction: Increased mortality after acute and chronic spinal cord injury (SCI) remains a challenge and mandates a better understanding of the factors contributing to survival in these patients. This study investigated whether body mass index (BMI) measured after acute traumatic SCI is associated with a change in mortality. Methods: A prospective longitudinal cohort study was conducted with 742 patients who were admitted to the Acute Spine Unit of the Vancouver General Hospital between 2004 and 2016 with a traumatic SCI. An investigation of the association between BMI on admission and long-term mortality was conducted using classification and regression tree (CART) and generalized additive models (spline curves) from acute care up to 7.7 years after SCI (chronic phase). Multivariable models were adjusted for (i) demographic factors (e.g., age, sex, and Charlson Comorbidity Index) and (ii) injury characteristics (e.g., neurological level and severity and Injury Severity Score). Results: After the exclusion of incomplete datasets (n = 602), 643 patients were analyzed, of whom 102 (18.5%) died during a period up to 7.7 years after SCI. CART identified three distinct mortality risk groups: (i) BMI: > 30.5 kg/m2, (ii) 17.5-30.5 kg/m2, and (iii) < 17.5 kg/m2. Mortality was lowest in the high BMI group (BMI > 30.5 kg/m2), followed by the middle-weight group (17.5-30.5 kg/m2), and was highest in the underweight group (BMI < 17.5 kg/m2). High BMI had a mild protective effect against mortality after SCI (hazard ratio 0.28, 95% CI: 0.09-0.88, p = 0.029), concordant with a modest "obesity paradox". Moreover, being underweight at admission was a significant risk factor for mortality up to 7.7 years after SCI (hazard ratio 5.5, 95% CI: 2.34-13.17, p < 0.001). Discussion: Mortality risk (1 month to 7.7 years after SCI) was associated with differences in BMI at admission. Further research is needed to better understand the underlying mechanisms. Given an established association of BMI with metabolic determinants, these results may suggest unknown neuro-metabolic pathways that are crucial for patient survival.

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.

Neurogenic Bowel in Acute Rehabilitation Following Spinal Cord Injury: Impact of Laxatives and Opioids.

OBJECTIVE: To explore the association between bowel dysfunction and use of laxatives and opioids in an acute rehabilitation setting following spinal cord injury (SCI). METHODS: Data was collected regarding individuals with acute traumatic/non-traumatic SCI over a two-year period (2012-2013) during both the week of admission and discharge of their inpatient stay. RESULTS: An increase in frequency of bowel movement (BM) (p = 0.003) and a decrease in frequency of fecal incontinence (FI) per week (p < 0.001) between admission and discharge was found across all participants. There was a reduction in the number of individuals using laxatives (p = 0.004) as well as the number of unique laxatives taken (p < 0.001) between admission and discharge in our cohort. The number of individuals using opioids and the average dose of opioids in morphine milligram equivalents (MME) from admission to discharge were significantly reduced (p = 0.001 and p = 0.02, respectively). There was a positive correlation between the number of laxatives and frequency of FI at discharge (r = 0.194, p = 0.014), suggesting that an increase in laxative use results in an increased frequency of FI. Finally, there was a significant negative correlation between average dose of opioids (MME) and frequency of BM at discharge, confirming the constipating effect of opioids (r = -0.20, p = 0.009).

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.

Linking Spinal Cord Injury Data Sets to Describe the Patient Journey Following Injury: A Protocol.

BACKGROUND: To optimize traumatic spinal cord injury (tSCI) care, administrative and clinical linked data are required to describe the patient's journey. OBJECTIVES: To describe the methods and progress to deterministically link SCI data from multiple databases across the SCI continuum in British Columbia (BC) and Ontario (ON) to answer epidemiological and health service research questions. METHODS: Patients with tSCI will be identified from the administrative Hospital Discharge Abstract Database using International Classification of Diseases (ICD) codes from Population Data BC and ICES data repositories in BC and ON, respectively. Admissions for tSCI will range between 1995-2017 for BC and 2009-2017 for ON. Linkage will occur with multiple administrative data holdings from Population Data BC and ICES to create the "Admin SCI Cohorts." Clinical data from the Rick Hansen SCI Registry (and VerteBase in BC) will be transferred to Population Data BC and ICES. Linkage of the clinical data with the incident cases and administrative data at Population Data BC and ICES will create subsets of patients referred to as the "Clinical SCI Cohorts" for BC and ON. Deidentified patient-level linked data sets will be uploaded to a secure research environment for analysis. Data validation will include several steps, and data analysis plans will be created for each research question. DISCUSSION: The creation of provincially linked tSCI data sets is unique; both clinical and administrative data are included to inform the optimization of care across the SCI continuum. Methods and lessons learned will inform future data-linking projects and care initiatives.

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.