Depressive symptoms show an increased prevalence in individuals affected by spinal cord injury (SCI), yet their in-depth characterization and association with clinical outcomes remain underexplored. We investigated depressive symptoms, operationalized through the items in the Beck Depression Inventory (BDI), in a longitudinal, observational study of 165 individuals with SCI, and explored their trajectories and association with neurological and functional recovery. 134 and 43 individuals with major depressive disorder (MDD) diagnosis from two reference cohorts were investigated to evaluate similarities and differences of the clinical manifestation of depression. At baseline (one month after injury), 25% of individuals with SCI showed a clinically relevant degree of overall depressive symptoms, and 21% at follow-up (six or twelve months after injury). Predominant depressive symptoms involved physical-somatic phenomena such as sleep disturbances, fatigue, changes in eating habits, and reduced libido. In contrast, individuals with MDD diagnosis exhibited a broader range of symptoms, particularly those related to self-rejection and self-blame. A development of a clinically relevant degree of overall depressive symptoms from the baseline to the follow-up stage in individuals with SCI was primarily reflected in increases in BDI scores for items related to self-hatred, anhedonia, emotional overload, or cognitive stress. A random forest (RF) model using psychiatric, SCI-specific, and demographic baseline features to predict the presence of a clinically relevant degree of overall depressive symptoms at follow-up demonstrated only mediocre predictive performance. In contrast, similar RF models exhibited good performances in predicting neurological and functional recovery following SCI, relying primarily on SCI-specific (rather than psychiatric) baseline features. Depressive symptoms in individuals with SCI appeared to be largely unrelated to neurological and functional recovery and were primarily related to physical-somatic phenomena. This distinguishes them from the broader range of symptoms observed in individuals with MDD diagnosis, which more commonly encompass self-blame, self-hatred, and other cognitive-emotional dimensions. To help reduce the risk of undetected development of a clinically relevant degree of overall depressive symptoms during SCI treatment, it may be useful to focus particularly on cognitive-emotional symptoms, alongside physical-somatic symptoms, which may be affected by the direct consequences of the injury itself.

The Integrated Neurological Change Score (INCS) combines changes in sensory and motor subscores from the International Standards for Spinal Cord Injury Classification (ISNCSCI) into a composite measure. We evaluated the INCS sensitivity to therapeutic outcomes, robustness against ceiling effects, and association to functional improvement in patients with acute cervical spinal cord injury (SCI). To this end, we conducted a retrospective analysis of data from the Nogo Inhibition in Spinal Cord Injury (NISCI) clinical trial alongside a matched cohort from the European Multicenter Study about Spinal Cord Injury (EMSCI). The NISCI trial assessed the safety and efficacy of the anti-Nogo-A antibody (NG-101) in acute cervical SCI, reporting a potential therapeutic effect in motor incomplete patients. Our findings show that the sensitivity of INCS to the effect of NG-101 is comparable to that obtained employing the changes in the Upper Extremity Motor Score (the primary outcome in the NISCI trial). Moreover, the INCS is less susceptible to ceiling effects compared to measures of upper and lower extremity or total motor scores, as observed in the NISCI trial and in the matched EMSCI cohort. This robustness may facilitate the design of more inclusive clinical trials without compromising statistical power. Finally, INCS correlates strongly with functional outcomes in self-care and walking ability, outperforming ISNCSCI motor scores. In conclusion, the INCS represents a sensitive measure of neurological change corroborating the value of ISNCSCI standards for use in SCI trials.

Abstract NG101 is a recombinant antibody that neutralizes the nerve growth inhibitor Nogo-A, promoting neural repair and improving upper extremity motor function in spinal cord injury (SCI). This study evaluated spinal cord MRI biomarkers to detect treatment-related structural changes and enhance patient stratification using data from 106 participants with acute cervical SCI in the phase 2b NISCI trial. We assessed lesion volume, tissue bridges, and remote changes in cross-sectional cord area (CSA), and tract-specific myelin-sensitive magnetization transfer saturation (MTsat) over six months. Compared to placebo, NG101-treated participants exhibited faster lesion volume reduction and a slower decline of CSA and MTsat in the corticospinal tracts and dorsal columns. Crucially, multimodal stratification incorporating MRI and electrophysiological measures substantially enhanced the detection of clinical treatment effects. These findings suggest NG101 slows trauma-induced progressive macro- and microstructural degeneration or promotes fiber sprouting. Combining MRI with electrophysiology enables sensitive detection of treatment effects and efficient trial designs. ClinicalTrials.gov identifier: NCT03935321.

There are no approved interventional therapies, aside from neurorehabilitation, that enhance neurological recovery after acute traumatic spinal cord injury. A key challenge is the lack of biomarkers surpassing clinical standards for optimal stratification. We evaluated electrophysiological markers of preserved neuronal function to improve enrichment strategies over clinical measures. We hypothesized that participants with preserved electrophysiological markers would achieve greater neurological and functional recovery in response to a plasticity-inducing intervention. We conducted a retrospective stratification analysis of data from the recently completed randomized, placebo-controlled, phase 2b Nogo Inhibition in spinal cord injury (NISCI) trial (NCT03935321) investigating the efficacy of NG101, a recombinant human antibody that neutralizes the neurite outgrowth-inhibiting protein Nogo-A. Participants aged 18-70 years with acute (4-28 days) cervical spinal cord injury were eligible. At screening, all participants underwent clinical neurological examination and electrophysiological recordings (i.e. somatosensory evoked potentials). Treatment effect sizes for the recovery of upper extremity motor scores and spinal cord independence measure of self-care (6-month change) between NG101 and placebo groups were compared for stratification based on clinical versus electrophysiological criteria. Power analyses were conducted to estimate the required sample sizes needed for each method. The cohort included 116 participants (45.5 ± 16.8 years old, 74 NG101 and 41 placebo). Clinical stratification showed greater functional recovery in motor-incomplete participants treated with NG101 versus placebo [estimate 0.02 (95% confidence interval: 0.006-0.038), P = 0.007]. Electrophysiological stratification revealed greater functional recovery in participants with preserved somatosensory evoked potentials treated with NG101 versus placebo [0.04 (0.015-0.054), P < 0.001]. Effect sizes were large for electrophysiological stratification (Cohen's d = 0.94) but small for clinical stratification (Cohen's d = 0.46). Power analyses demonstrated smaller required sample sizes for electrophysiological stratification (required n = 32) versus clinical stratification (required n = 120). This study shows the value of electrophysiology in comparison to clinical measures for biomarker-driven enrichment and improved power in acute spinal cord injury trials. We emphasize the importance of functionally spared neuronal pathways in promoting recovery in response to plasticity-inducing interventions, such as anti-Nogo-A antibodies.

BACKGROUND:Spinal cord injury (SCI) leads to lifelong disability with highly variable neurological recovery, complicating prognostication and conceptualization of clinical trials. The American Spinal Injury Association Impairment Scale (AIS) is widely used to classify injury severity. Although AIS A injuries are considered sensorimotor complete, they show substantial heterogeneity in residual function and recovery. Data-driven approaches offer an opportunity to uncover latent subgroups beyond conventional classifications. We evaluate whether unsupervised, data-driven clustering can identify distinct subgroups within patients with traumatic SCI and characterize neurological patterns in sensorimotor complete SCI. METHODS:We applied an unsupervised clustering model to International Standards of Neurological Classification of Spinal Cord Injury (ISNCSCI) examination scores from the European Multicenter Study about Spinal Cord Injury dataset (3165 patients), to derive neurological groupings independent of predefined ISNCSCI classifications. Clusters were derived from the full cohort, followed by focused analyses of individuals classified as AIS A at their first documented assessment. External reproducibility was evaluated using data from the Sygen clinical trial. RESULTS:Six distinct clusters were identified. Patients graded as AIS A were represented in 5 clusters, which differed markedly in injury level (paraplegic vs tetraplegic) and indicators of recovery potential, including neurological sparing, upper and lower extremity motor scores, and AIS conversion rates. These patterns were consistently reproduced in the Sygen cohort. CONCLUSIONS:Proposed framework complements conventional AIS grading by revealing distinct neurological conditions related to the variability among patients with baseline sensorimotor complete injuries. Proposed data-driven framework enables more comprehensive prognostic assessments and improves patient stratification in clinical trials.

Abstract Background Spinal cord injury (SCI) causes long-term neurological deficits resulting in functional disabilities. While longitudinal recovery patterns of sensorimotor outcomes after SCI have been studied, few analyses have applied machine learning to systematically model the relationship between neurological impairments and functional independence at different post-injury phases. Methods This study compared ordinal and nominal classification models predicting functional independence from sensorimotor status cross-sectionally. Inputs included motor and sensory scores from the International Standards for Neurological Classification of SCI, age, sex, and time since injury collected in the European Multicenter Study about SCI. Models were evaluated on a task from each domain of the Spinal Cord Independence Measure, namely grooming (self-care), bladder management (respiration and sphincter management), and indoor mobility (mobility). Analyses were stratified into early (≤ 40 days), intermediate (70–100 days), and late (> 182 days) post-injury phases. Models were ranked based on five evaluation metrics, and interpretability explored using Shapley Additive Explanations (SHAP). Results Model accuracy improved over time (early phase: 46–71%, late phase: 50–85%), indicating that functional independence is more reliably determined from sensorimotor scores in later post-injury phases. Across all scenarios, random forest achieved the best overall performance (0.93 ± 0.03, averaged across different metrics). Ordinal models yielded fewer severe misclassifications compared to nominal models. Motor scores were stronger predictors than sensory scores, with lower limb function (L2–L4) strongly associated with mobility, voluntary anal contraction with bladder control, and upper limb function (C6, C8) with grooming ability, highlighting that models utilise known relationships. Conclusion We show that both multiclass and ordinal models can accurately classify SCIM-based functional independence outcomes after SCI from neurological assessments at different time points post-injury. Ordinal approaches provide particular clinical value by minimizing severe misclassifications, a crucial advantage when distinguishing between functional independence classes that require fundamentally different care approaches. Interpretability analysis showed that the predictions are grounded in clinical knowledge. The developed models provide the basis for a modular prognostic framework, in which predicted ISNCSCI scores can be used to derive the most likely functional independence class, enabling a modular, computationally efficient and scalable approach to prediction in SCI care across a range of neurological and functional outcomes.

Background and Objectives Spinal cord injury (SCI) incidence is rising among the elderly, yet the relationship between age and recovery remains controversial. The aim of this study was to evaluate the relationship between age and neurologic and functional outcomes and to identify an age cutoff associated with a decline in recovery. Methods We conducted a prospective cohort study using data from patients with traumatic and ischemic SCI enrolled in the European Multicenter Study about Spinal Cord Injury between 2001 and 2022. Linear regression models assessed the relationship between age and changes from baseline to 1 year after SCI in the total motor score (TMS) of the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) and in the Spinal Cord Independence Measure (SCIM) total score. Additional analyses examined the relationship between age and the evolution of ISNCSCI light-touch and pinprick scores, as well as ambulation parameters (6-minute walking test, 10-meter walking test, and Walking Index for Spinal Cord Injury). Models were adjusted for baseline scores, sex, year of injury, American Spinal Injury Association Impairment Scale (AIS) grade, and level of injury. The age cutoff was determined using a change-point model. Results A total of 2,171 patients (median age 47 years, 77.9% male, 51.9% injured at the cervical level, and 50.0% with a motor complete injury [AIS-A and AIS-B]) were included in the analysis. Increased age was not associated with changes in TMS (p = 0.896) but was significantly associated with reduced SCIM improvement (p < 0.001), with an estimated decline of 4.3 SCIM points per decade of age. Sensory outcomes were not significantly affected by age (Delta light-touch: p = 0.273; Delta pinprick: p = 0.520) while ambulation recovery declined with increasing age (all outcomes p < 0.01). A noticeable reduction in functional recovery was observed in patients older than 70 years. Discussion Older age does not seem to affect neurologic recovery but is linked to poorer functional and ambulation outcomes. These findings, including the identified age cutoff, should inform future clinical trial design and guide tailored care strategies for older adults with SCI.

Neurological recovery following spinal cord injury (SCI) is commonly studied through changes in high-level descriptors of injury severity, such as the American Spinal Injury Association Impairment Scale (AIS) grade, or total upper and/or lower extremity motor scores. More recently, the analysis of segmental motor scores has attracted interest as it provides a more detailed understanding of the exact location and extent of changes occurring during recovery. We propose to augment the analysis of segmental motor recovery with a qualitative descriptor of local motor score patterns, which is defined for all upper and lower extremity myotomes below the neurological level of injury (NLI) and based on a categorization of the changes along the rostrocaudal motor score sequence. Our hypothesis is that recovery of segmental motor scores depends on the residual function as described by the newly proposed descriptors of local motor score patterns. Using data of 1385 patients from the European Multicenter Study about SCI, we analyze differences in recovery at approximately 6 months after injury between local motor score patterns and find an increased probability of full motor recovery for myotomes associated with increased motor scores in the caudal direction. We further use an aggregated descriptor of motor score patterns focusing on increases of motor scores in the caudal direction as an alternative or complementary feature to the AIS grade in prediction models for segmental motor scores at recovery. We observe equivalent predictive performance as measured by the root mean square error between actual and predicted motor scores below the NLI for models using the same set of features and additionally either the AIS grade (median = 0.79) or local pattern (median = 0.80). This is noteworthy as the definition of local motor score patterns requires only the examination of the 10 key muscles of the International Standards for Neurological Classification of SCI on each side of the body, while the AIS grade can only be reliably determined if extensive sensory testing is performed in addition. These results indicate the potential benefits of considering information inherent to the rostrocaudal sequence of motor scores for a better understanding of motor recovery. Furthermore, it supports the development and use of abbreviated sensorimotor examinations specifically in the early phase after SCI.

Recovery after spinal cord injury (SCI) follows a complex and variable trajectory, yet the field lacks clear, data-driven definitions of the temporal stages of recovery. This study aimed to model the trajectory of recovery after SCI and define distinct post-injury phases based on real-world clinical data. We analyzed longitudinal data from 4407 individuals with traumatic SCI enrolled in the European Multicenter Study about Spinal Cord Injury (EMSCI). Neurological improvement was quantified using the Integrated Neurological Change Score (INCS). Functional recovery was assessed using the Spinal Cord Independence Measure (SCIM) and a derived measure of hand motor function based on motor scores of the C6, C8, and T1 myotomes. Longitudinal recovery trajectories were modeled using random forest regression, locally estimated scatterplot smoothing (LOESS), and neural networks. Lastly, latent class mixed models (LCMM) were employed to identify subgroups with distinct recovery profiles. Across all models, neurological recovery followed a four-stage sigmoidal pattern: an acute phase (up to ∼2 weeks post-injury) with minimal change; a transition phase (∼2 to 9–11 weeks) marked by substantial neurological change; a pre-chronic phase (∼10 weeks to 7–8 months) characterized by ongoing but non-linear recovery; and a chronic phase (beyond ∼7–8 months) in which recovery plateaued. Neurological improvement consistently preceded functional gains captured by SCIM and hand motor strength. Latent class analysis identified four distinct recovery profiles: class 1 (marked recovery), classes 2 and 3 (moderate recovery), and class 4 (minimal to no recovery). Notably, despite significant variability in the magnitude of lower extremity recovery across classes, the timing of the transition phase was remarkably consistent, aligning with the population-level window of approximately 10–11 weeks post-injury. The majority of neurological and functional improvement occurs within the first ∼10 weeks post-injury. These findings align with the concept of a period of heightened neuroplasticity and provide a data-driven framework for timing assessments and interventions in SCI recovery.

BackgroundThe aim of clinical trials for spinal cord injury (SCI) is to improve everyday-life activity outcomes, which requires reliable methods for monitoring patient activity. This study evaluates sensor-derived activity metrics in comparison to established clinical assessment methods.MethodsWearable inertial sensors collected data from 69 individuals with acute, traumatic cervical SCI participating in the Nogo-A Inhibition in Spinal Cord Injury trial (NCT03935321), a phase 2b, multicenter, randomized, placebo-controlled trial. During inpatient rehabilitation, participants wore up to 5 inertial sensors for up to 3 consecutive days each week. An estimation of average daily energy expenditure (EE) was used as an indicator of physical activity and compared to the recovery of Upper Extremity Motor Scores (UEMS) and Spinal Cord Independence Measures (SCIM).ResultsParticipants in the verum (n = 41; 59.4%) and placebo (n = 28; 40.6%) groups showed similar initial activity levels, however, the verum group exhibited a significantly greater weekly increase in average daily EE (ΔEE = 11.6 kcal/day/week, 95% CI [1.5, 21.8], P = .025). In contrast, no significant group differences were observed in changes in UEMS (ΔUEMS = 0.1/week, 95% CI [-0.2, 0.3], P = .603) or SCIM (ΔSCIM = 0.2, per week 95% CI [-0.7, 1.1], P = .644).ConclusionContinuous sensor-based activity monitoring offers objective and sensitive insights into changes in physical capabilities, effectively complementing periodic clinical assessments. Thus, sensor-derived outcome measures offer potential for improving the evaluation of clinical studies in individuals with SCI.Clinical Trail Registration:https://clinicaltrials.gov; NCT03935321.

Background:In the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), motor levels are inferred from sensory levels for high cervical, thoracic, and low sacral injuries, as key muscles are only assessed in upper and lower extremities. This is known as the "motor follows sensory level" rule. Objectives:To develop regression models for estimating motor scores from sensory scores in segments without clinically testable key muscles and to validate the consensus-based "motor follows sensory level" approach. Methods:A total of 6940 ISNCSCI examinations from the European Multicenter Study about Spinal Cord Injury were reviewed. Multiple linear and random forest regression models were trained on scores in clinically testable segments to predict motor from sensory scores of the same spinal segment and side. Models based on ipsilateral light touch or pinprick scores alone, as well as all bilateral sensory scores, were also evaluated. Predicted motor scores were used to recalculate motor levels for the segments without clinically testable key muscles and compared to the true motor levels. Results:The ipsilateral regression models showed minimal differences (R 2 0.64-0.65; RMSE 1.34). Normal motor scores were predicted only for normal sensory function; in the linear model, this was captured by the equation: motor score = 0.18 + 1.22 * light touch score + 0.96 * pinprick score. Model-based motor levels were shifted caudally 0.18 segments (linear regression) and 0.32 segments (random forest regression). Conclusion:As models predict normal motor function only for normal sensory scores, predicted motor levels deviate only marginally, supporting the "motor follows sensory level" rule.

Background: A solid rationale exists for early sacral neuromodulation in the form of causal therapy that improves neurogenic lower urinary tract dysfunction after complete spinal cord injury. However, the short and early time frame for minimally invasive therapy poses a series of ethical and medical issues, which has impeded clinical realisation thus far. Objectives: We performed a cross-sectional study on patients with chronic spinal cord injury to learn about patients’ attitudes towards early treatment to prepare for large randomised controlled trials. Methods: A cohort of patients (n = 86, mixed genders) with spinal cord injury over two years was analysed. Their lower urinary tract-related quality of life was assessed using the Qualiveen-30 tool. The extent of neurogenic lower urinary tract dysfunction, patients’ awareness of it, and their attitude towards early sacral neuromodulation were explored with a specific questionnaire. Results: A total of 61.9% (n = 52) of patients declared that, in retrospect, they would have agreed to early treatment prior to the emergence of their autonomic dysfunction. Of these patients, 51.8% (n = 29) would have also consented to early sacral neuromodulation. Quality of life had no impact on their decision. More than half of the patients (n = 49, 57.0%) stated they had not grasped the momentous nature of neurogenic lower urinary tract dysfunction when being informed about it. This finding was subsequently correlated with a decreased lower urinary tract-related quality of life. Conclusion: Patients with neurogenic lower urinary tract dysfunction are likely to agree to an early therapeutic approach. Clinical implementation requires knowledge and acceptance of the procedure on the part of patients and their caregivers.

BACKGROUND AND OBJECTIVES:Spinal cord injury (SCI) incidence is rising among the elderly, yet the relationship between age and recovery remains controversial. The aim of this study was to evaluate the relationship between age and neurologic and functional outcomes and to identify an age cutoff associated with a decline in recovery. METHODS:We conducted a prospective cohort study using data from patients with traumatic and ischemic SCI enrolled in the European Multicenter Study about Spinal Cord Injury between 2001 and 2022. Linear regression models assessed the relationship between age and changes from baseline to 1 year after SCI in the total motor score (TMS) of the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) and in the Spinal Cord Independence Measure (SCIM) total score. Additional analyses examined the relationship between age and the evolution of ISNCSCI light-touch and pinprick scores, as well as ambulation parameters (6-minute walking test, 10-meter walking test, and Walking Index for Spinal Cord Injury). Models were adjusted for baseline scores, sex, year of injury, American Spinal Injury Association Impairment Scale (AIS) grade, and level of injury. The age cutoff was determined using a change-point model. RESULTS:A total of 2,171 patients (median age 47 years, 77.9% male, 51.9% injured at the cervical level, and 50.0% with a motor complete injury [AIS-A and AIS-B]) were included in the analysis. Increased age was not associated with changes in TMS (p = 0.896) but was significantly associated with reduced SCIM improvement (p < 0.001), with an estimated decline of 4.3 SCIM points per decade of age. Sensory outcomes were not significantly affected by age (Δlight-touch: p = 0.273; Δpinprick: p = 0.520) while ambulation recovery declined with increasing age (all outcomes p < 0.01). A noticeable reduction in functional recovery was observed in patients older than 70 years. DISCUSSION:Older age does not seem to affect neurologic recovery but is linked to poorer functional and ambulation outcomes. These findings, including the identified age cutoff, should inform future clinical trial design and guide tailored care strategies for older adults with SCI. TRIAL REGISTRATION INFORMATION:ClinicalTrials.gov Identifier NCT01571531.

Objective: To identify risk factors for dysphagia in individuals who sustained traumatic cervical SCI. The pathophysiologic mechanisms of dysphagia in individuals with traumatic cervical spinal cord injury (SCI) are not well understood yet. Several risk factors for developing dysphagia after SCI were postulated including mechanical ventilation, tracheostomy, age, female sex, anterior surgical approach, SCI severity, and multilevel spinal fusion. Design: Retrospective analysis: Candidate explanatory variables, including injury severity, age, neurological level of injury, surgical approach, number of fused spinal segments, and tracheostomy including its type, were analyzed using univariate and multivariable statistical analyses. Setting: We included patients, who were treated at the BG Trauma Center Murnau between 2013 and 2022. Participants: Datasets of a total of 407 patients with traumatic cervical SCI were included. Main Outcome Measures: Dysphagia prevalence and identification of associated risk factors. Results: Our analysis included 407 individuals, of whom 22.6% had dysphagia. Tracheostomy and age were identified as the main risk factors for dysphagia after traumatic cervical SCI. Contrary to previous literature, injury severity, an anterior surgical approach, the type of tracheostomy, a higher neurological level of SCI, and multilevel spinal fusion did not show an increased risk after accounting for other factors. Conclusions: Our study identifies age and tracheostomy as primary risk factors for dysphagia after SCI, allowing to identify patients at risk and inform early-stage clinical management. Archives of Physical Medicine and Rehabilitation 2025;106:1189-97 (c) 2025 by the American Congress of Rehabilitation Medicine.

Background Spinal cord injury results in permanent neurological impairment and disability due to the absence of spontaneous regeneration. NG101, a recombinant human antibody, neutralises the neurite growth-inhibiting protein Nogo-A, promoting neural repair and motor recovery in animal models of spinal cord injury. We aimed to evaluate the efficacy of intrathecal NG101 on recovery in patients with acute cervical traumatic spinal cord injury. Methods This randomised, double-blind, placebo-controlled phase 2b clinical trial was done at 13 hospitals in the Czech Republic, Germany, Spain, and Switzerland. Patients aged 18-70 years with acute, complete or incomplete cervical spinal cord injury (neurological level of injury C1-C8) within 4-28 days of injury were eligible for inclusion. Participants were initially randomly assigned 1:1 to intrathecal treatment with 45 mg NG101 or placebo (phosphate- buffered saline); 18 months into the study, the ratio was adjusted to 3:1 to achieve a final distribution of 2:1 to improve enrolment and drug exposure. Randomisation was done using a centralised, computer-based randomisation system and was stratified according to nine distinct outcome categories with a validated upper extremity motor score (UEMS) prediction model based on clinical parameters at screening. Six intrathecal injections were administered every 5 days over 4 weeks, starting within 28 days of injury. Investigators, study personnel, and study participants were masked to treatment allocation. The primary outcome was change in UEMS at 6 months, analysed alongside safety in the full analysis set. The completed trial was registered at ClinicalTrials.gov, NCT03935321. Findings From May 20, 2019, to July 20, 2022, 463 patients with acute traumatic cervical spinal cord injury were screened, 334 were deemed ineligible and excluded, and 129 were randomly assigned to an intervention (80 patients in the NG101 group and 49 in the placebo group). The full analysis set comprised 78 patients from the NG101 group and 48 patients from the placebo group. 107 (85%) patients were male and 19 (15%) patients were female, with a median age of 515 years (IQR 300-600). Across all patients, the primary endpoint showed no significant difference between groups (with UEMS change at 6 months 137 [95% CI -144 to 418]; placebo group mean 1920 [SD 1178] at baseline and 3091 [SD 1549] at day 168; NG101 group mean 1823 [SD 1514] at baseline and 3131 [1954] at day 168). Treatment-related adverse events were similar between groups (nine in the NG101 group and six in the placebo group). 25 severe adverse events were reported: 18 in 11 (14%) patients in the NG101 group and seven in six (13%) patients in the placebo group. Although no treatment-related fatalities were reported in the NG101 group, one fatality not related to treatment occurred in the placebo group. Infections were the most common adverse event affecting 44 (92%) patients in the placebo group and 65 (83%) patients in the NG101 group. Interpretation NG101 did not improve UEMS in patients with acute spinal cord injury. Post-hoc subgroup analyses assessing UEMS and Spinal Cord Independence Measure of self-care in patients with motor-incomplete injury indicated potential beneficial effects that require investigation in future studies.

Imaging modalities, particularly magnetic resonance imaging (MRI), have become the gold standard for assessing lesion characteristics of traumatic spinal cord injuries (SCI). Diffusion tensor imaging (DTI), an advanced MRI technique, offers insights into microstructural changes in white matter tracts. While previous studies focused on either acute or chronic SCI, few have examined longitudinal changes during the transition from acute to chronic stages of injury. This study addresses this gap by analyzing the evolution of DTI metrics over the first year following cervical SCI. This prospective longitudinal study involved 52 patients with traumatic cervical SCI. MRI and neurological examinations using the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) were performed 1 month, 3 months, and 1 year post-injury. Linear mixed model analyses assessed DTI measures over time. Fractional anisotropy (FA) values gradually decreased in the reference area at the cranio-cervical junction (C0–C4; p < 0.001), indicating ongoing tissue degeneration up to one year after injury, independent of initial clinical severity. FA values at the lesion site correlated moderately with the total motor score 1 month post-SCI (R = 0.37, p = 0.033). Mean diffusivity (MD) increased significantly over time (p < 0.001), suggesting progressive microstructural changes. Axial diffusivity (AD) decreased until 3 months after injury (p < 0.001), then returned to its initial values by 1 year, reflecting dynamic pathophysiological events. This study highlights the potential of DTI for monitoring microstructural changes after SCI. Longitudinal imaging offers insights into evolving pathology, supports prognostic modeling, and may aid treatment monitoring and outcome prediction.

Objectives:To investigate incidence, conversion, neurological characteristics, and age-dependent functional independence of individuals with initial spinal cord injury (SCI) recovering to American Spinal Injury Association Impairment Scale (AIS) E, meaning normal sensory and motor functions according to the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI). Methods:We analyzed 12,221 EMSCI (European Multicenter Study about Spinal Cord Injury) ISNCSCI datasets from 5 time points over the first year after SCI of 4286 individuals (age: 48.7 ± 19 years; 23% female; 92% traumatic, 8% ischemic). Results:Sixty-five of 82 individuals with at least one AIS E exam had an initial assessment within 6 weeks after injury with neurological level of injury peaking at C4 (16.9%) and L2 (15.4%), predominantly AIS grade D (89.2%), and mean total sensory/motor scores reaching 89.4% of their maximum. First AIS E conversion was detected at a median of 171 (interquartile range 274) days after injury. A change point analysis of Spinal Cord Independence Measure (SCIM) III assessments at the time of conversion of 75 AIS E individuals demonstrates a decline of full functional independence with age particularly over 70 years (<40, 76.9%; 40-70, 42.9%; >70, 14.3%). Conclusion:The current AIS E definition insufficiently reflects the reality experienced by older people without deficits in the ISNCSCI, as functional impairments remain predominantly in mobility-related activities. To detect whether these deficits are related to comorbidities attributable to aging rather than remnant deficits of SCI, functional assessments such as the SCIM should be performed in an age-matched non-SCI control group.

Successfully completing clinical trials for rare and heterogeneous disorders, like spinal cord injuries (SCI), remains challenging, thereby reducing the ability to test and translate promising preclinical findings. We propose synthetic controls, derived from data-driven predictions of recovery in patients undergoing standard treatments, to mitigate these challenges, in particular related to patient recruitment. Based on data from the European Multicenter Study about Spinal Cord Injury (EMSCI) and the Sygen trial, we construct synthetic controls from personalized predictions of neurological recovery of sequences of segmental motor scores. A total of six architectures (linear, tree, and deep learning models) are compared. We demonstrate the applicability of synthetic controls through a simulation framework modeling the randomization process in a clinical trial and a case study that re-evaluates the recently completed Nogo Inhibition in SCI (NISCI) trial as a single-arm trial post hoc. The primary dataset included 4196 patients from EMSCI and 587 patients from the Sygen trial for external validation. We identified a convolutional neural network as the best-performing architecture to predict segmental motor score sequences, achieving a median root mean squared error below the neurological level of injury of 0.55. Our trial simulations demonstrate that synthetic controls are a viable alternative to randomization, as the proposed solution reduces intercohort heterogeneity and leads to no significant differences with randomized controls in our case study reassessing a clinical trial. We provide a comprehensive benchmark of data-driven prediction architectures for neurological recovery after SCI. Apart from offering individual patients a specific recovery prediction, these models constitute the basis for synthetic controls. Using real-world data from a completed trial in SCI, we show that synthetic controls could mitigate the challenges of small cohorts and patient recruitment in rare disorders, offering the opportunity to maximize the number of patients receiving an investigative treatment. https://gitlab.ethz.ch/BMDSlab/publications/sci/sci-in-silico-trials .

In light of growing biomedical data, machine learning (ML) models offer tremendous potential for personalized prediction in medicine. However, the additional value provided by these computational tools should always be critically evaluated. Using the example of predicting walking ability after spinal cord injury (SCI), we highlight a popular scenario in which data-driven predictions are feasible but not clinically meaningful, as the task can be performed equally well by humans. We asked 11 human observers from diverse backgrounds (five researchers without clinical training but proven knowledge of SCI and the International Standards for Neurological Classification of SCI [ISNCSCI], and six neurologists experienced in SCI) to predict walking ability following SCI based on acute phase neurological status assessed by the ISNCSCI motor and sensory scores (≤40 days after injury [DAI]). Following an established clinical prediction rule, walking ability was defined by a binary label derived from the indoor walking ability subitem of the Spinal Cord Independence Measure. We compared the performance of human observers with extreme gradient boosting and logistic regression-based models, which represent popular approaches in clinical literature on SCI. Using 794 patients from the European Multicenter Study about SCI, we show that all approaches provide similar, excellent performance at population level (area under the receiver operating characteristic 0.93-0.95; accuracy 0.88-0.90). Importantly, predictions combined from multiple neurologists (accuracy: 0.89) were comparable with model-based predictions (accuracy: 0.88-0.90), whereas individual neurologists (accuracy: 0.79 [0.01]; mean [standard deviation]) were marginally outperformed by computational approaches (accuracy: 0.88-0.90), particularly for more heterogeneous incomplete injuries. Individual SCI researchers performed equally well compared with neurologists (accuracy: 0.78 [0.02]). Our results show that prediction of walking function following SCI, if described through a binary label, does not benefit from ML, as ensembles of clinical experts and researchers each achieve performance similar to a range of ML models and an established clinical prediction rule. This highlights two key considerations in clinical applications of data-driven prediction models in SCI: first, the importance of carefully choosing clinical outcome measures to target in a prediction task to achieve a true benefit, and second, the necessity of benchmarking human performance on specific tasks to determine whether meaningful differences are present.