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.

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.

A data-driven approach to categorize patients with traumatic spinal cord injury: cluster analysis of a multicentre database.

Background: Conducting clinical trials for traumatic spinal cord injury (tSCI) presents challenges due to patient heterogeneity. Identifying clinically similar subgroups using patient demographics and baseline injury characteristics could lead to better patient-centered care and integrated care delivery. Purpose: We sought to (1) apply an unsupervised machine learning approach of cluster analysis to identify subgroups of tSCI patients using patient demographics and injury characteristics at baseline, (2) to find clinical similarity within subgroups using etiological variables and outcome variables, and (3) to create multi-dimensional labels for categorizing patients. Study design: Retrospective analysis using prospectively collected data from a large national multicenter SCI registry. Methods: A method of spectral clustering was used to identify patient subgroups based on the following baseline variables collected since admission until rehabilitation: location of the injury, severity of the injury, Functional Independence Measure (FIM) motor, and demographic data (age, and body mass index). The FIM motor score, the FIM motor score change, and the total length of stay were assessed on the subgroups as outcome variables at discharge to establish the clinical similarity of the patients within derived subgroups. Furthermore, we discussed the relevance of the identified subgroups based on the etiological variables (energy and mechanism of injury) and compared them with the literature. Our study also employed a qualitative approach to systematically describe the identified subgroups, crafting multi-dimensional labels to highlight distinguishing factors and patient-focused insights. Results: Data on 334 tSCI patients from the Rick Hansen Spinal Cord Injury Registry was analyzed. Five significantly different subgroups were identified (p-value ≤0.05) based on baseline variables. Outcome variables at discharge superimposed on these subgroups had statistically different values between them (p-value ≤0.05) and supported the notion of clinical similarity of patients within each subgroup. Conclusion: Utilizing cluster analysis, we identified five clinically similar subgroups of tSCI patients at baseline, yielding statistically significant inter-group differences in clinical outcomes. These subgroups offer a novel, data-driven categorization of tSCI patients which aligns with their demographics and injury characteristics. As it also correlates with traditional tSCI classifications, this categorization could lead to improved personalized patient-centered care.

Beneficial Effects of Preoperative Exercise on the Outcomes of Lumbar Fusion Spinal Surgery.

Purpose: To determine whether there was an association between self-reported preoperative exercise and postoperative outcomes after lumbar fusion spinal surgery. Method: We performed a retrospective multivariable analysis of the prospective Canadian Spine Outcomes and Research Network (CSORN) database of 2,203 patients who had elective single-level lumbar fusion spinal surgeries. We compared adverse events and hospital length of stay between patients who reported regular exercise (twice or more per week) prior to surgery ("Regular Exercise") to those exercising infrequently (once or less per week) ("Infrequent Exercise") or those who did no exercise ("No Exercise"). For all final analyses, we compared the Regular Exercise group to the combined Infrequent Exercise or No Exercise group. Results: After making adjustments for known confounding factors, we demonstrated that patients in the Regular Exercise group had fewer adverse events (adjusted odds ratio 0.72; 95% CI: 0.57, 0.91; p = 0.006) and significantly shorter lengths of stay (adjusted mean 2.2 vs. 2.5 d, p = 0.029) than the combined Infrequent Exercise or No Exercise group. Conclusions: Patients who exercised regularly twice or more per week prior to surgery had fewer postoperative adverse events and significantly shorter hospital lengths of stay compared to patients that exercised infrequently or did no exercise. Further study is required to determine effectiveness of a targeted prehabilitation programme.

Objectif : déterminer s'il y avait une association entre les exercices préopératoires autodéclarés et les résultats postopératoires après une chirurgie de fusion lombaire. Méthodologie : analyse multivariable rétrospective de la base de données prospective Canadian Spine Outcomes and Research Network (CSORN) composée de 2 203 patients qui avaient subi une chirurgie de fusion lombaire univertébrale non urgente. Les chercheurs ont comparé les événements indésirables et la durée du séjour hospitalier entre les patients qui déclaraient faire de l'exercice régulier (au moins deux fois par semaine) avant l'opération (« exercice régulier ¼) à ceux qui n'en faisaient pas souvent (une fois ou moins par semaine; « exercice peu fréquent ¼) et qui n'en faisaient pas du tout (« absence d'exercice ¼). Pour toutes les analyses définitives, ils ont comparé le groupe qui faisait de l'exercice régulier aux groupes combinés d'exercice peu fréquent et d'absence d'exercice. Résultats : après correction pour tenir compte des facteurs confusionnels connus, les chercheurs ont démontré que les patients du groupe faisant de l'exercice régulier présentaient moins d'événements indésirables (rapport de cotes rajusté 0,72; IC à 95 % : 0,57, 0,91; p = 0,006) et leur séjour à l'hôpital était significativement plus court (moyenne corrigée 2,2 jours par rapport à 2,5 jours, p = 0,029) que dans le groupe combiné d'exercice peu fréquent et d'absence d'exercice. Conclusions : les patients qui faisaient de l'exercice régulièrement au moins deux fois par semaine avant l'opération présentaient moins d'événements indésirables après l'opération et étaient hospitalisés beaucoup moins longtemps que ceux qui ne faisaient pas beaucoup d'exercice ou n'en faisaient pas du tout. Il faudra réaliser d'autres études pour déterminer l'efficacité d'un programme de préréadaptation ciblé.

Morphable models of the lumbar spine to vary geometry based on pathology, demographics, and anatomical measurements.

The shape of the lumbar spine influences its function and dysfunction. Yet examining the influence of geometric differences associated with pathology or demographics on lumbar biomechanics is challenging in vivo where these effects cannot be isolated, and the use of simple anatomical measurements does not fully capture the complex three-dimensional geometry. The goal of this work was to develop and share morphable models of the lumbar spine that allow geometry to be varied according to pathology, demographics, or anatomical measurements. Partial least squares regression was used to generate statistical shape models that quantify geometric differences associated with pathology, demographics, and anatomical measurements from the lumbar spines of 87 patients. To determine if the morphable models detected meaningful geometric differences, the ability of the morphable models to classify spines was compared with models generated from random labels. The models for disc herniation (p < 0.04), spondylolisthesis (p < 0.001), and sex (p < 0.01) all performed significantly better than the random models. Age was predicted with a root mean square error of 14.1 years using the age-based model. The morphable models for anatomical measurements were able to produce instances with root mean square errors less than 0.8°, 0.3 cm2, and 0.7 mm between desired and resulting measurements. This method can be used to produce morphable models that enable further analysis of the relationship among shape, pathology, demographics, and function through computational simulations. The morphable models and code are available at https://github.com/aclouthier/morphable-lumbar-model.

Patient, clinical, surgical, and institutional factors associated with length of stay in scheduled degenerative thoracolumbar spine surgery: National Multicenter Cohort Analysis from the Canadian Spine Outcomes and Research Network.

OBJECTIVE: Length of stay (LOS) is a contributor to costs and resource utilization. The primary goal of this study was to identify patient, clinical, surgical, and institutional variables that influence LOS after elective surgery for thoracolumbar degenerative pathology. The secondary objective was to examine variability in LOS and institutional strategies used to decrease LOS. METHODS: This is a retrospective study of prospectively collected data from a multicentric cohort enrolled in the Canadian Spine Outcomes and Research Network (CSORN) between January 2015 and October 2020 who underwent elective thoracolumbar surgery (discectomy [1 or 2 levels], laminectomy [1 or 2 levels], and posterior instrumented fusion [up to 5 levels]). Prolonged LOS was defined as LOS greater than the median. Logistic regression models were used to determine factors associated with prolonged LOS for each procedure. A survey was sent to the principal investigators of the participating healthcare institutions to understand institutional practices that are used to decrease LOS. RESULTS: A total of 3700 patients were included (967 discectomies, 1094 laminectomies, and 1639 fusions). The median LOSs for discectomy, laminectomy, and fusion were 0.0 (IQR 1.0), 1.0 (IQR 2.0), and 4.0 (IQR 2.0) days, respectively. On multivariable analysis, predictors of prolonged LOS for discectomy were having more leg pain, higher Oswestry Disability Index (ODI) scores, symptom duration more than 2 years, having undergone an open procedure, occurrence of an adverse event (AE), and treatment at an institution without protocols to reduce LOS (p < 0.05). Predictors of prolonged LOS for laminectomy were increased age, living alone, higher ODI scores, higher BMI, open procedures, longer operative time, AEs, and treatment at an institution without protocols to reduce LOS (p < 0.05). For posterior instrumented fusion, predictors of prolonged LOS were older age, living alone, more comorbidities, higher ODI scores, longer operative time, AEs, and treatment at an institution without protocols to reduce LOS (p < 0.05). The laminectomy group had the largest variability in LOS (SD 4.4 days, range 0-133 days). Three hundred fifty-four patients (22%) had an LOS above the 75th percentile. Ten institutions (53%) had either Enhanced Recovery After Surgery or standardized protocols in place. CONCLUSIONS: Among the factors identified in this study, worse baseline ODI scores, experiencing AEs, and treatment at an institution without protocols aimed at reducing LOS were predictive of prolonged LOS in all surgical groups. The laminectomy group had the largest variability in LOS.

Using Clinical Vignettes and a Modified Expert Delphi Panel to Determine Parameters for Identifying Non-Traumatic Spinal Cord Injury in Health Administrative and Electronic Medical Record Databases.

OBJECTIVE: To obtain expert consensus on the parameters and etiologic conditions required to retrospectively identify cases of non-traumatic spinal cord injury (NTSCI) in health administrative and electronic medical record (EMR) databases based on the rating of clinical vignettes. DESIGN: A modified Delphi process included 2 survey rounds and 1 remote consensus panel. The surveys required the rating of clinical vignettes, developed after chart reviews and expert consultation. Experts who participated in survey rounds were invited to participate in the Delphi Consensus Panel. SETTING: An international collaboration using an online meeting platform. PARTICIPANTS: Thirty-one expert physicians and/or clinical researchers in the field of spinal cord injury (SCI). MAIN OUTCOME MEASURE(S): Agreement on clinical vignettes as NTSCI. Parameters to classify cases of NTSCI in health administrative and EMR databases. RESULTS: In health administrative and EMR databases, cauda equina syndromes should be considered SCI and classified as a NTSCI or TSCI based on the mechanism of injury. A traumatic event needs to be listed for injury to be considered TSCI. To be classified as NTSCI, neurologic sufficient impairments (motor, sensory, bowel, and bladder) are required, in addition to an etiology. It is possible to have both a NTSCI and a TSCI, as well as a recovered NTSCI. If information is unavailable or missing in health administrative and EMR databases, the case may be listed as "unclassifiable" depending on the purpose of the research study. CONCLUSION: The Delphi panel provided guidelines to appropriately classify cases of NTSCI in health administrative and EMR databases.

The effect of a quality improvement project on post-operative opioid use following outpatient spinal surgery.

Background: Prescribing opioids upon discharge after surgery is common practice; however, there are many inherent risks including dependency, diversion, and medical complications. Our prospective pre- and post-intervention study investigates the effect of a standardized analgesic prescription on the quantity of opioids prescribed and patients' level of pain and satisfaction with pain control in the early post-operative period. Methods: With the implementation of an electronic medical record, a standardized prescription was built employing multimodal analgesia and a stepwise approach to analgesics based on level of pain. Patients received an education handout pre-operatively explaining the prescription. Consecutive patients over a three-month period undergoing elective spine surgery as day or overnight stay cases who received usual care were compared to a similar cohort who received the standardized prescription and education. Patient satisfaction with post-operative pain control, post-operative pain scores, number of refills required, and opioids prescribed in oral morphine equivalents (OMEs) were compared before and after implementation of the standardized analgesic prescription. Results: Twenty-six patients received usual care (Control group) and 26 patients received the standardized prescription and education handout (Intervention group). There were significantly fewer OMEs prescribed in the Intervention group compared to the Control group. There was no difference between groups in: patient post-operative pain intensity score, post-operative satisfaction score, or number of refills required. Conclusions: This study demonstrates that a standardized prescription consisting of an appropriate amount of opioid and non-opioid analgesics is effective in reducing the OMEs prescribed post-operatively in elective spine surgery procedures, without compromising patient pain control or satisfaction or increasing the number of refills required.

Subsidence of Spinal Fusion Cages: A Systematic Review.

BACKGROUND: Although many research studies investigating subsidence of intervertebral fusion cages have been published, to our knowledge, no study has comprehensively compared cage subsidence among all lumbar intervertebral fusion (LIF) techniques. This study aimed to review the literature reporting evidence of cage subsidence linked to LIF. The amount of subsidence was compared and associated with the procedures and corresponding implants used, and the effect of cage subsidence on clinical outcomes was investigated. METHODS: For this systematic review, the MEDLINE and PubMed databases were used to identify relevant studies. Search terms included lumbar, lumbar vertebrae, lumbar spine, cage, spinal fusion, prosthesis, prosthesis implantation, implantation, implants, interbody, spacer, and subsidence. Studies included in this review were those having more than 10 patients and reporting the amount of subsidence observed using computed tomography or x-ray imaging after surgery and at follow-up visits after a minimum of 6 weeks postsurgery. Data and scale definitions related to subsidence were extracted from articles for comparison of subsidence prevalence between the 5 LIF surgical procedures. RESULTS: Forty articles were identified for inclusion. The review included data from 390 anterior lumbar intervertebral fusions (ALIFs), 2130 lateral lumbar intervertebral fusions (LLIFs), 560 posterior lumbar intervertebral fusions (PLIFs), 245 oblique lumbar intervertebral fusions (OLIFs), and 1634 transverse lumbar intervertebral fusions (TLIFs) for a total of 4959 patients who underwent LIF surgery. The minimum and maximum percentages of the number of patients having subsidence for each procedure in the included studies were as follows: ALIF stand-alone, 6% and 23.1%; LLIF stand-alone, 8.7% and 39.6%; LLIF with posterior fixation, 3.3% and 20.7%; OLIF with posterior fixation, 4.4% and 36.9%; PLIF with posterior fixation, 7.4% and 31.8%; and TLIF, 0.0% and 51.2%. CONCLUSIONS: The number of patients experiencing subsidence varied between studies within each fusion procedure. Our findings indicate that all 5 surgical methods are at risk of subsidence. Overall, ALIF without posterior fixation resulted in the lowest reported subsidence occurrence among the 5 surgical approaches. There is conflicting evidence on the association between subsidence and negative clinical outcomes. CLINICAL RELEVANCE: This review defines and compares subsidence incidence between all LIF procedures and investigates the risk of symptomatic clinical outcomes.

A scoping review of complication prediction models in spinal surgery: An analysis of model development, validation and impact.

Background: Predictive analytics are being used increasingly in the field of spinal surgery with the development of models to predict post-surgical complications. Predictive models should be valid, generalizable, and clinically useful. The purpose of this review was to identify existing post-surgical complication prediction models for spinal surgery and to determine if these models are being adequately investigated with internal/external validation, model updating and model impact studies. Methods: This was a scoping review of studies pertaining to models for the prediction of post-surgical complication after spinal surgery published over 10 years (2010-2020). Qualitative data was extracted from the studies to include study classification, adherence to Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines and risk of bias (ROB) assessment using the Prediction model study Risk Of Bias Assessment Tool (PROBAST). Model evaluation was determined using area under the curve (AUC) when available. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement was used as a basis for the search methodology in four different databases. Results: Thirty studies were included in the scoping review and 80% (24/30) included model development with or without internal validation. Twenty percent (6/30) were exclusively external validation studies and only one study included an impact analysis in addition to model development and internal validation. Two studies referenced the TRIPOD guidelines and there was a high ROB in 100% of the studies using the PROBAST tool. Conclusions: The majority of post-surgical complication prediction models in spinal surgery have not undergone standardized model development and internal validation or adequate external validation and impact evaluation. As such there is uncertainty as to their validity, generalizability, and clinical utility. Future efforts should be made to use existing tools to ensure standardization in development and rigorous evaluation of prediction models in spinal surgery.

Allogeneic blood transfusions and infection risk in lumbar spine surgery: An American College of Surgeons National Surgery Quality Improvement Program Study.

BACKGROUND: Allogenic blood transfusions can lead to immunomodulation. Our purpose was to investigate whether perioperative transfusions were associated with postoperative infections and any other adverse events (AEs), after adjusting for potential confounding factors, following common elective lumbar spinal surgery procedures. STUDY DESIGN AND METHODS: We performed a multivariate, propensity-score matched, regression-adjusted retrospective analysis of the American College of Surgeons National Surgical Quality Improvement Program database between 2012 and 2016. All lumbar spinal surgery procedures were identified (n = 174,891). A transfusion group (perioperative transfusion within 72 h before, during, or after principal surgery; n = 1992) and a control group (no transfusion; n = 1992) were formed. Following adjustment for between-group baseline features, adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) were calculated using a multivariate logistic regression model for any surgical site infection (SSI), superficial SSI, deep SSI, wound dehiscence, pneumonia, urinary tract infection, sepsis, any infection, mortality, and any AEs. RESULTS: Transfusion was associated with an increased risk of each specific infection, mortality, and any AEs. Statistically significant between-group differences were demonstrated with respect to any SSI (aOR: 1.48; 95% CI: 1.01-2.16), deep SSI (aOR: 1.66; 95% CI: 0.98-2.85), sepsis (aOR: 2.69; 95% CI: 1.43-5.03), wound dehiscence (aOR: 2.27; 95% CI: 0.86-6.01), any infection (aOR: 1.46; 95% CI: 1.13-1.88), any AEs (aOR: 1.80; 95% CI: 1.48-2.18), and mortality (aOR: 2.17; 95% CI: 0.77-6.36). CONCLUSION: We showed an association between transfusion and infection in lumbar spine surgery after adjustment for various applicable covariates. Sepsis had the highest association with transfusion. Our results reinforce a growing trend toward minimizing perioperative transfusions, which may lead to reduced infections following lumbar spine surgery.

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.

Preoperative Factors Predict Postoperative Trajectories of Pain and Disability Following Surgery for Degenerative Lumbar Spinal Stenosis.

STUDY DESIGN: Longitudinal analysis of prospectively collected data. OBJECTIVE: Investigate potential predictors of poor outcome following surgery for degenerative lumbar spinal stenosis (LSS). SUMMARY OF BACKGROUND DATA: LSS is the most common reason for an older person to undergo spinal surgery, yet little information is available to inform patient selection. METHODS: We recruited LSS surgical candidates from 13 orthopedic and neurological surgery centers. Potential outcome predictors included demographic, health, clinical, and surgery-related variables. Outcome measures were leg and back numeric pain rating scales and Oswestry disability index scores obtained before surgery and after 3, 12, and 24 postoperative months. We classified surgical outcomes based on trajectories of leg pain and a composite measure of overall outcome (leg pain, back pain, and disability). RESULTS: Data from 529 patients (mean [SD] age = 66.5 [9.1] yrs; 46% female) were included. In total, 36.1% and 27.6% of patients were classified as experiencing a poor leg pain outcome and overall outcome, respectively. For both outcomes, patients receiving compensation or with depression/depression risk were more likely, and patients participating in regular exercise were less likely to have poor outcomes. Lower health-related quality of life, previous spine surgery, and preoperative anticonvulsant medication use were associated with poor leg pain outcome. Patients with ASA scores more than two, greater preoperative disability, and longer pain duration or surgical waits were more likely to have a poor overall outcome. Patients who received preoperative chiropractic or physiotherapy treatment were less likely to report a poor overall outcome. Multivariable models demonstrated poor-to acceptable (leg pain) and excellent (overall outcome) discrimination. CONCLUSION: Approximately one in three patients with LSS experience a poor clinical outcome consistent with surgical non-response. Demographic, health, and clinical factors were more predictive of clinical outcome than surgery-related factors. These predictors may assist surgeons with patient selection and inform shared decision-making for patients with symptomatic LSS. LEVEL OF EVIDENCE: 2.

Opioid use trends in patients undergoing elective thoracic and lumbar spine surgery.

Background: Opioid use in North America has increased rapidly in recent years. Preoperative opioid use is associated with several negative outcomes. Our objectives were to assess patterns of opioid use over time in Canadian patients who undergo spine surgery and to determine the effect of spine surgery on 1-year postoperative opioid use. Methods: A retrospective analysis was performed on prospectively collected data from the Canadian Spine Outcomes and Research Network for patients undergoing elective thoracic and lumbar surgery. Self-reported opioid use at baseline, before surgery and at 1 year after surgery was compared. Baseline opioid use was compared by age, sex, radiologic diagnosis and presenting complaint. All patients meeting eligibility criteria from 2008 to 2017 were included. Results: A total of 3134 patients provided baseline opioid use data. No significant change in the proportion of patients taking daily (range 32.3%-38.2%) or intermittent (range 13.7%-22.5%) opioids was found from pre-2014 to 2017. Among patients who waited more than 6 weeks for surgery, the frequency of opioid use did not differ significantly between the baseline and preoperative time points. Significantly more patients using opioids had a chief complaint of back pain or radiculopathy than neurogenic claudication (p < 0.001), and significantly more were under 65 years of age than aged 65 years or older (p < 0.001). Approximately 41% of patients on daily opioids at baseline remained so at 1 year after surgery. Conclusion: These data suggest that additional opioid reduction strategies are needed in the population of patients undergoing elective thoracic and lumbar spine surgery. Spine surgeons can be involved in identifying patients taking opioids preoperatively, emphasizing the risks of continued opioid use and referring patients to appropriate evidence-based treatment programs.

Contexte: En Amérique du Nord, l'utilisation d'opioïdes a augmenté rapidement dans les dernières années. La prise d'opioïdes en période préopératoire est associée à plusieurs issues négatives. Cette étude visait à évaluer l'évolution des tendances dans l'utilisation d'opioïdes des patients canadiens ayant subi une chirurgie spinale, et de déterminer les effets de la chirurgie sur leur utilisation 1 an après l'opération. Méthodes: Une analyse rétrospective a été réalisée à partir de données recueillies de manière prospective par le Canadian Spine Outcomes and Research Network pour les patients ayant subi une chirurgie thoracique ou une chirurgie spinale élective. On a comparé l'utilisation autodéclarée d'opioïdes au début du suivi, avant la chirurgie et 1 an après la chirurgie. L'utilisation d'opioïdes au départ a été comparée selon le sexe, l'âge, le diagnostic radiologique et le motif de consultation. Entre 2008 et 2017, tous les patients satisfaisant aux critères d'admissibilités ont été inclus dans l'étude. Résultats: Au total, 3134 patients ont fourni des données sur leur prise d'opioïdes au début du suivi. Il n'y avait pas de changement significatif dans la proportion de patients utilisant quotidiennement (32,3 % à 38,2 %) ou occasionnellement (13,7 % à 22,5 %) des opioïdes entre les patients à l'étude avant 2014 et ceux à l'étude de 2014 à 2017. Parmi les patients qui ont attendu plus de 6 semaines avant la chirurgie, la fréquence de la prise d'opioïdes n'a pas changé de manière significative entre le début du suivi et la rencontre préopératoire. Une proportion significativement plus grande de patients qui utilisaient des opioïdes consultaient principalement pour des douleurs au dos ou une radiculopathie que pour une claudication neurogène (p < 0,001), et il y avait une proportion significativement plus grande de patients de moins de 65 ans qui utilisaient des opioïdes que de patients de 65 ans ou plus (p < 0,001). Environ 41 % des patients qui prenaient quotidiennement des opioïdes au départ le faisaient aussi 1 an après la chirurgie. Conclusion: Ces données suggèrent que des stratégies supplémentaires de réduction de l'utilisation d'opioïdes sont nécessaires pour les patients qui subissent une chirurgie thoracique ou une chirurgie spinale élective. Il est possible de demander aux chirurgiens spécialisés dans ce domaine de repérer les patients qui prennent des opioïdes avant l'opération, puisque l'utilisation prolongée comporte des risques, et de les aiguiller vers un programme de traitement adéquat et fondé sur des données probantes.

Capturing adverse events in elective orthopedic surgery: comparison of administrative, surgeon and reviewer reporting

Summary: Ensuring adverse event (AE) recording is standardized and accurate is paramount for patient safety. In this discussion, we outline our comparison of AE data collected by orthopedic surgeons and independent clinical reviewers using the Spine Adverse Events Severity System (SAVES) and Orthopedic Surgical Adverse Events Severity System (OrthoSAVES) against AE data recorded by hospital administrative discharge abstract coders. In 164 spine, hip, knee and shoulder patients, reviewers recorded significantly more AEs than coders, and coders recorded significantly more AEs than surgeons. The AEs were recorded similarly by reviewers using SAVES and OrthoSAVES in 48 spine patients. Despite our small sample size and use of different AE tools, we believe it is important to highlight that coders, surgeons and reviewers recorded AEs differently. While further investigations on its utility and cost-effectiveness are necessary, we assert that it is feasible to use Ortho-SAVES to prospectively record AEs across all orthopedic subspecialties.

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.

Patients undergoing surgery for lumbar spinal stenosis experience unique courses of pain and disability: A group-based trajectory analysis.

OBJECTIVE: Identify patient subgroups defined by trajectories of pain and disability following surgery for degenerative lumbar spinal stenosis, and investigate the construct validity of the subgroups by evaluating for meaningful differences in clinical outcomes. METHODS: We recruited patients with degenerative lumbar spinal stenosis from 13 surgical spine centers who were deemed to be surgical candidates. Study outcomes (leg and back pain numeric rating scales, modified Oswestry disability index) were measured before surgery, and after 3, 12, and 24 months. Group-based trajectory models were developed to identify trajectory subgroups for leg pain, back pain, and pain-related disability. We examined for differences in the proportion of patients achieving minimum clinically important change in pain and disability (30%) and clinical success (50% reduction in disability or Oswestry score ≤22) 12 months from surgery. RESULTS: Data from 548 patients (mean[SD] age = 66.7[9.1] years; 46% female) were included. The models estimated 3 unique trajectories for leg pain (excellent outcome = 14.4%, good outcome = 49.5%, poor outcome = 36.1%), back pain (excellent outcome = 13.1%, good outcome = 45.0%, poor outcome = 41.9%), and disability (excellent outcome = 30.8%, fair outcome = 40.1%, poor outcome = 29.1%). The construct validity of the trajectory subgroups was confirmed by between-trajectory group differences in the proportion of patients meeting thresholds for minimum clinically important change and clinical success after 12 postoperative months (p < .001). CONCLUSION: Subgroups of patients with degenerative lumbar spinal stenosis can be identified by their trajectories of pain and disability following surgery. Although most patients experienced important reductions in pain and disability, 29% to 42% of patients were classified as members of an outcome trajectory subgroup that experienced little to no benefit from surgery. These findings may inform appropriate expectation setting for patients and clinicians and highlight the need for better methods of treatment selection for patients with degenerative lumbar spinal stenosis.

Management of cervical spine epidural abscess: a systematic review.

BACKGROUND: Cervical spinal epidural abscess (CSEA) is a localized infection between the thecal sac and cervical spinal column which may result in neurological deficit and death if inadequately treated. Two treatment options exist: medical management and surgical intervention. Our objective was to analyze CSEA patient outcomes in order to determine the optimal method of treatment. METHODS: An electronic literature search for relevant case series and retrospective reviews was conducted through June 2016. Data abstraction and study quality assessment were performed by two independent reviewers. A lack of available data led to a post hoc decision not to perform meta-analysis of the results; study findings were synthesized qualitatively. RESULTS: 927 studies were identified, of which 11 were included. Four studies were ranked as good quality, and seven ranked as fair quality. In total, data from 173 patients were included. Mean age was 55 years; 61.3% were male. Intravenous drug use was the most common risk factor for CSEA development. Staphylococcus aureus was the most commonly cultured pathogen. 140 patients underwent initial surgery, an additional 18 patients were surgically treated upon failure of medical management, and 15 patients were treated with antibiotics alone. CONCLUSION: The rates of medical management failure described in our review were much higher than those reported in the literature for thoracolumbar spinal epidural abscess patients, suggesting that CSEA patients may be at a greater risk for poor outcomes following nonoperative treatment. Thus, early surgery appears most viable for optimizing CSEA patient outcomes. Further research is needed in order to corroborate these recommendations.