Cross-sectional study. Given recent epidemiological data which indicate a rising incidence of traumatic and non-traumatic spinal cord injury, we sought to analyze changes in the annual number of training positions, applicants, and unfilled training positions in United States spinal cord injury medicine (SCIM) training. Fellowship programs participating in the SCIM Match. Data were obtained from the National Resident Matching Program from 2016 to 2024. Annual trends were analyzed with linear regression. The annual number of SCIM training programs (19-22, 15.8% increase, P < 0.001) and training positions (28-32, 14.3% increase, P < 0.001) increased over the study period. There was no significant change in the annual number of applicants (16-19, 18.8% increase, P = 0.878). The annual training position-to-applicant ratio ranged from 1.2-1.8 with no significant change over the study period (P = 0.555). The rate of unfilled training positions did not change over the study period (50.0-43.8%, P = 0.523). The annual match rate ranged between 87.0-100% with no clear trend over the study period (P = 0.423). There were no differences in the percentage of applicants matching at their first-choice (62.5-73.7%, P = 0.780) second-choice (12.5-10.5%, P = 0.333), and third-choice (12.5-0%, P = 0.966) fellowships over the study period. There has been an increase in the number of SCIM training programs and positions, but this has not been matched by an increased number of interested applicants. Policy efforts are needed to increase interest in SCIM and meet anticipated growth in clinical needs.

A retrospective cohort study. To develop a machine learning (ML) model to predict ambulation prognosis one year post-injury in rehabilitation-phase spinal cord injury (SCI) individuals classified as American Spinal Injury Association Impairment Scale (AIS) grades B and C, and to implement it as a web application. A multicenter database in the United States. Data were collected from the National Spinal Cord Injury Database (NSCID) for the years 2011 to 2021. Traumatic SCI cases with complete neurological data at rehabilitation admission were included, based on the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI). Model predictors included age at injury, acute length of stay, neurological level of injury, motor scores, and sensory scores. ML models were developed using nested 5-fold cross-validation and four algorithms: logistic regression, random forest, support vector machine, and extreme gradient boosting (XGB). Performance was assessed and compared using area under the curve (AUC), Brier score, and calibration slope, with a focus on AIS grades B and C. A web application was developed using the R package shiny and deployed via shinyapps.io. 2034 cases were included in the analysis. XGB demonstrated the best performance in terms of AUC (0.855), Brier score (0.153), and calibration slope (0.900) and was selected as the final model. This model was implemented as a web application. The developed model showed good performance for AIS grades B and C and was made practical via web application implementation.

Longitudinal pre-clinical study. To determine the impact of crank length and cadence on pedal reaction forces and cardiovascular responses in a preclinical model of high thoracic severe spinal cord injury. The Kentucky Spinal Cord Injury Research Center at the University of Louisville, Louisville, KY USA. Five female Sprague-Dawley rats received T2 severe contusion SCIs and served as their own controls. To better understand the biomechanical and cardiovascular responses to cycling, we utilized a commercially available motorized rat cycle with custom cranks and pedals to collect pedal reaction forces using two different crank lengths and at a range of cycling cadences. Simultaneously, heart rate (HR) and blood pressure (BP) were collected via an indwelling telemeter. Collected data were analyzed pre-, during, and post-cycling, weekly up to six weeks post-injury. The longer crank length increased forces and spasticity, although differences were more pronounced during extension that involved lengthening of the flexor muscles. HR and systolic/diastolic pressures were elevated during cycling and changed in parallel with force events, although few differences were observed between standard and short crank length cycling. These results suggest that MC may constitute a mild exercise strategy post-SCI; clinical translation may be dependent on the ability of the subject-specific cycling parameters to generate reflex-induced eccentric muscle contractions during cycling, emphasizing the importance of crank length (leg range-of-motion) and cycling cadence on the value of motorized cycling after severe SCI.

Cross-sectional study. The magnitude and nature of National Institutes of Health (NIH) funding for spinal cord injury (SCI) research is poorly characterized. This study elucidates the portfolio of NIH grants awarded for SCI research. N/A METHODS: Data on NIH grants awarded for SCI research were extracted from the NIH RePORTER database (2013-2023). NIH funding was analyzed for twenty-five clinical areas and compound annual growth rates (CAGRs) were calculated over the study period. From 2013-2023, the NIH extramural research budget increased from $28.3 to $45.0 billion (CAGR 4.7%). A total of $986 million was awarded for SCI research, which increased from $93.6 to $97.7 million over the study period (CAGR 0.4%). Among the twenty-five clinical areas, dementia ($21.8 billion, CAGR 18.7%) and diabetes ($20.6 billion, CAGR 21.5%) had the most NIH funding. For SCI research, most NIH funding was awarded by the National Institute of Neurological Disorders and Stroke (67%) via the R01 (57%) grant mechanism. The clinical areas receiving the most NIH funding for SCI research were disease mechanisms (47%), prosthetics (22%), biologic therapies (18%), and pharmacologic therapies (6%). Several principal investigator characteristics were associated with higher NIH funding totals for SCI research including male (P < 0.001), full professor (P < 0.001), and MD, PhD degree (P = 0.044). Growth in the annual NIH budget for SCI research has not kept pace with growth in the overall NIH extramural research budget. Future strategies are needed to support PIs in obtaining NIH grant funding for SCI research.

Narrative review. Vascular autoregulation in the central nervous system (CNS) maintains appropriate perfusion in the context of changing blood pressure. Impaired autoregulation in various diseases often contributes to their pathophysiology. While this mechanism is well characterized in the brain, it remains understudied in the spinal cord, limiting evidence-based blood pressure management in spinal cord pathology. In this review, we summarize the current understanding of spinal cord autoregulation, highlight advancements in cerebral autoregulation, and offer a framework for its clinical application in spinal cord care. A literature search was conducted comparing preclinical evidence of spinal cord autoregulation with current clinical practices in the brain. Although autoregulation has been recognized in the spinal cord, it has been mostly measured in animals, and its clinical impact has been limited. In contrast, cerebral autoregulation has influenced patient care through continuous monitoring of dynamic autoregulation and clinical trials using personalized blood pressure targets. These innovations require measurement of blood flow or a surrogate, which is performed infrequently in the cord. Furthermore, confounding variables, such as arterial CO2 levels, temperature, and pharmacology, must be tightly controlled, as they can affect blood flow and thus interfere with autoregulation measurements. Spinal cord autoregulation is an essential variable in neurology and neurosurgery. A better understanding of this process could improve outcomes in various conditions, including traumatic injury, ischemic injury, and other spinal diseases. As spinal cord blood flow measurement technologies improve, there is a growing opportunity to apply autoregulation to direct patient care.

Systematic Review. To describe applications of AI for traumatic SCI management with focus on diagnostics, prognostication, and therapeutic interventions. PubMed, Scopus and Cochrane libraries were searched (March 2025). Studies published in English between January 1st, 2020, and March 18, 2025, dealing with clinical aspects in the acute, post-injury rehabilitative and first year phases of SCI were included. Studies on brain computer interface, robotics and non-neurologic aspects of SCI were excluded. Extracted were country of study, study design, focus of study, total participants, American Spinal Injury Association (ASIA) Impairment Scale (AIS), machine learning (ML) models, inputs, outcomes and performance metrices. A total of 23 studies with 120,931 individuals were identified. Classical Machine Learning Models, Ensemble Learning Models and Deep Learning Models were the most used ML families. Age, AIS, neurologic level of injury, sex, mechanism of injury and motor score were the most common inputs. Predictions of neurologic status, functionality status, Hospital/ICU utilizations, complications, survival, discharge destination and results of image segmentation and patient grouping were the outputs of interest. The performance metrices were satisfactory in most and higher than humans in some studies. AI can facilitate personalized approach to diagnosis of SCI, prediction of outcomes like neurological improvement, complications, functionality indicators like walking, selfcare and independence, re-admissions, prolonged length of stays, discharge destination and mortality after injury. It was also useful to suggest specific MAP goals and time of surgical intervention. These functions complement clinical judgement.

Cross-sectional observational study. Deep-tissue injury (DTI) originates in subcutaneous soft tissue and progresses outward without early skin changes, making diagnosis difficult in people with spinal-cord injury (SCI). We evaluated the incidence of DTI with magnetic resonance imaging (MRI) and sought associated risk factors. Kibikogen Rehabilitation Center for Employment Injuries, Japan. Fifty-six wheelchair-dependent adults with SCI of at least 1 month's duration underwent pelvic sagittal STIR MRI screening. DTI-positive sites were defined by signal changes in subcutaneous fat or muscle. Ultrasonography, body composition, seating-related variables, and laboratory data were collected concurrently. Univariate and multivariate logistic-regression analyses identified independent risk factors. MRI detected subclinical DTI in 33 of 112 ischial regions (29.5%). Ultrasonography was concordant in only 15 sites (45.5%). Multivariable analysis showed that longer daily wheelchair use (p = 0.018), greater subcutaneous-tissue thickness at the ischial tuberosities (p = 0.028), and less-frequent pressure-relief manoeuvres (p = 0.031; protective) were independently associated with DTI. BMI, peak interface pressure, and routine haematologic or nutritional markers were not significant. MRI screening revealed subclinical DTI in nearly one-third of wheelchair-dependent patients with SCI and outperformed ultrasonography for early detection. Extended sitting time, thicker subcutaneous fat at the ischial tuberosity, and infrequent pressure relief emerged as modifiable risk factors. A risk-based MRI surveillance strategy may enable timely preventive interventions and reduce progression to overt pressure ulcers.

Retrospective cohort study. To identify clinical and demographic factors associated with functional recovery and length of hospital stay in individuals with spinal cord injury undergoing inpatient rehabilitation. Physical Medicine and Rehabilitation Center at Ankara Bilkent City Hospital, Turkey. Medical records of patients with spinal cord injury admitted for inpatient rehabilitation between January 2020 and September 2023 were retrospectively reviewed. Demographic characteristics, injury-related variables, neurological level, ASIA classification, SCIM III scores, complications, assistive rehabilitation interventions, bladder management, and functional status were collected. Univariate analyses (Mann-Whitney U, Kruskal-Wallis, Chi-square) were performed, followed by multivariate regression to identify independent predictors of functional outcomes. A total of 342 patients were included (mean age 38.9 ± 16.2 years). The mean length of stay was 41.6 ± 20.3 days. Univariate analyses showed that age, time since injury, neurological level, multiple hospitalizations, SCIM III scores, complications, advanced rehabilitation technologies, and bladder catheterization were significantly associated with both functional status and hospitalization duration (p < 0.05). Multivariate regression demonstrated that age (β = -0.24, 95% CI: -0.35 to -0.13, p < 0.001), presence of complications (β = -0.31, 95% CI: -0.46 to -0.17, p < 0.001), and bladder catheterization (β = -0.19, 95% CI: -0.32 to -0.07, p = 0.004) were independent predictors of discharge SCIM III scores. Age, neurological integrity, complications, and bladder management are key determinants of functional outcomes in SCI rehabilitation, while these factors also influence length of stay. Early complication prevention, optimized bladder care, and tailored rehabilitation strategies may enhance recovery and shorten hospitalization. No commercial sponsorship was received for this study.