ATF3 is a neuron-specific biomarker for spinal cord injury and ischaemic stroke.

BACKGROUND: Although many molecules have been investigated as biomarkers for spinal cord injury (SCI) or ischemic stroke, none of them are specifically induced in central nervous system (CNS) neurons following injuries with low baseline expression. However, neuronal injury constitutes a major pathology associated with SCI or stroke and strongly correlates with neurological outcomes. Biomarkers characterized by low baseline expression and specific induction in neurons post-injury are likely to better correlate with injury severity and recovery, demonstrating higher sensitivity and specificity for CNS injuries compared to non-neuronal markers or pan-neuronal markers with constitutive expressions. METHODS: In animal studies, young adult wildtype and global Atf3 knockout mice underwent unilateral cervical 5 (C5) SCI or permanent distal middle cerebral artery occlusion (pMCAO). Gene expression was assessed using RNA-sequencing and qRT-PCR, while protein expression was detected through immunostaining. Serum ATF3 levels in animal models and clinical human samples were measured using commercially available enzyme-linked immune-sorbent assay (ELISA) kits. RESULTS: Activating transcription factor 3 (ATF3), a molecular marker for injured dorsal root ganglion sensory neurons in the peripheral nervous system, was not expressed in spinal cord or cortex of naïve mice but was induced specifically in neurons of the spinal cord or cortex within 1 day after SCI or ischemic stroke, respectively. Additionally, ATF3 protein levels in mouse blood significantly increased 1 day after SCI or ischemic stroke. Importantly, ATF3 protein levels in human serum were elevated in clinical patients within 24 hours after SCI or ischemic stroke. Moreover, Atf3 knockout mice, compared to the wildtype mice, exhibited worse neurological outcomes and larger damage regions after SCI or ischemic stroke, indicating that ATF3 has a neuroprotective function. CONCLUSIONS: ATF3 is an easily measurable, neuron-specific biomarker for clinical SCI and ischemic stroke, with neuroprotective properties. HIGHLIGHTS: ATF3 was induced specifically in neurons of the spinal cord or cortex within 1 day after SCI or ischemic stroke, respectively. Serum ATF3 protein levels are elevated in clinical patients within 24 hours after SCI or ischemic stroke. ATF3 exhibits neuroprotective properties, as evidenced by the worse neurological outcomes and larger damage regions observed in Atf3 knockout mice compared to wildtype mice following SCI or ischemic stroke.

Correction: Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome.

[This corrects the article DOI: 10.1371/journal.pone.0265254.].

Safety and comparative efficacy of initiating low-molecular-weight heparin within 24 hours of injury or surgery for venous thromboembolism prophylaxis in patients with spinal cord injury: a prospective TRACK-SCI registry study.

OBJECTIVE: Venous thromboembolism (VTE) following traumatic spinal cord injury (SCI) is a significant clinical concern. This study sought to determine the incidence of VTE and hemorrhagic complications among patients with SCI who received low-molecular-weight heparin (LMWH) within 24 hours of injury or surgery and identify variables that predict VTE using the prospective Transforming Research and Clinical Knowledge in SCI (TRACK-SCI) database. METHODS: The TRACK-SCI database was queried for individuals with traumatic SCI from 2015 to 2022. Primary outcomes of interest included rates of VTE (including deep vein thrombosis [DVT] and pulmonary embolism [PE]) and in-hospital hemorrhagic complications that occurred after LWMH administration. Secondary outcomes included intensive care unit and hospital length of stay, discharge location type, and in-hospital mortality. RESULTS: The study cohort consisted of 162 patients with SCI. Fifteen of the 162 patients withdrew from the study, leading to loss of data for certain variables for these patients. One hundred thirty patients (87.8%) underwent decompression and/or fusion surgery for SCI. DVT occurred in 11 (7.4%) of 148 patients, PE in 9 (6.1%) of 148, and any VTE in 18 (12.2%) of 148 patients. The analysis showed that admission lower-extremity motor score (p = 0.0408), injury at the thoracic level (p = 0.0086), admission American Spinal Injury Association grade (p = 0.0070), and younger age (p = 0.0372) were significantly associated with VTE. There were 3 instances of postoperative spine surgery-related bleeding (2.4%) in the 127 patients who had spine surgery with bleeding complication data available, with one requiring return to surgery (0.8%). Thirteen (8.8%) of 147 patients had a bleeding complication not related to spine surgery. There were 2 gastrointestinal bleeds associated with nasogastric tube placement, 3 cases of postoperative non-spine-related surgery bleeding, and 8 cases of other bleeding complications (5.4%) not related to any surgery. CONCLUSIONS: Initiation of LMWH within 24 hours was associated with a low rate of spine surgery-related bleeding. Bleeding complications unrelated to SCI surgery still occur with LMWH administration. Because neurosurgical intervention is typically the limiting factor in initializing chemical DVT prophylaxis, many of these bleeding complications would have likely occurred regardless of the protocol.

Expert-augmented automated machine learning optimizes hemodynamic predictors of spinal cord injury outcome.

Artificial intelligence and machine learning (AI/ML) is becoming increasingly more accessible to biomedical researchers with significant potential to transform biomedicine through optimization of highly-accurate predictive models and enabling better understanding of disease biology. Automated machine learning (AutoML) in particular is positioned to democratize artificial intelligence (AI) by reducing the amount of human input and ML expertise needed. However, successful translation of AI/ML in biomedicine requires moving beyond optimizing only for prediction accuracy and towards establishing reproducible clinical and biological inferences. This is especially challenging for clinical studies on rare disorders where the smaller patient cohorts and corresponding sample size is an obstacle for reproducible modeling results. Here, we present a model-agnostic framework to reinforce AutoML using strategies and tools of explainable and reproducible AI, including novel metrics to assess model reproducibility. The framework enables clinicians to interpret AutoML-generated models for clinical and biological verifiability and consequently integrate domain expertise during model development. We applied the framework towards spinal cord injury prognostication to optimize the intraoperative hemodynamic range during injury-related surgery and additionally identified a strong detrimental relationship between intraoperative hypertension and patient outcome. Furthermore, our analysis captured how evolving clinical practices such as faster time-to-surgery and blood pressure management affect clinical model development. Altogether, we illustrate how expert-augmented AutoML improves inferential reproducibility for biomedical discovery and can ultimately build trust in AI processes towards effective clinical integration.

Diagnostic blood RNA profiles for human acute spinal cord injury.

Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity.

Injury volume extracted from MRI predicts neurologic outcome in acute spinal cord injury: A prospective TRACK-SCI pilot study.

Conventional MRI measures of traumatic spinal cord injury severity largely rely on 2-dimensional injury characteristics such as intramedullary lesion length and cord compression. Recent advances in spinal cord (SC) analysis have led to the development of a robust anatomic atlas incorporated into an open-source platform called the Spinal Cord Toolbox (SCT) that allows for quantitative volumetric injury analysis. In the current study, we evaluate the prognostic value of volumetric measures of spinal cord injury on MRI following registration of T2-weighted (T2w) images and segmented lesions from acute SCI patients with a standardized atlas. This IRB-approved prospective cohort study involved the image analysis of 60 blunt cervical SCI patients enrolled in the TRACK-SCI clinical research protocol. Axial T2w MRI data obtained within 24 h of injury were processed using the SCT. Briefly, SC MRIs were automatically segmented using the sct_deepseg_sc tool in the SCT and segmentations were manually corrected by a neuro-radiologist. Lesion volume data were used as predictor variables for correlation with lower extremity motor scores at discharge. Volumetric MRI measures of T2w signal abnormality comprising the SCI lesion accurately predict lower extremity motor scores at time of patient discharge. Similarly, MRI measures of injury volume significantly correlated with motor scores to a greater degree than conventional 2-D metrics of lesion size. The volume of total injury and of injured spinal cord motor regions on T2w MRI is significantly and independently associated with neurologic outcome at discharge after injury.

Transforming Research and Clinical Knowledge in Spinal Cord Injury (TRACK-SCI): an overview of initial enrollment and demographics.

OBJECTIVE: Traumatic spinal cord injury (SCI) is a dreaded condition that can lead to paralysis and severe disability. With few treatment options available for patients who have suffered from SCI, it is important to develop prospective databases to standardize data collection in order to develop new therapeutic approaches and guidelines. Here, the authors present an overview of their multicenter, prospective, observational patient registry, Transforming Research and Clinical Knowledge in SCI (TRACK-SCI). METHODS: Data were collected using the National Institute of Neurological Disorders and Stroke (NINDS) common data elements (CDEs). Highly granular clinical information, in addition to standardized imaging, biospecimen, and follow-up data, were included in the registry. Surgical approaches were determined by the surgeon treating each patient; however, they were carefully documented and compared within and across study sites. Follow-up visits were scheduled for 6 and 12 months after injury. RESULTS: One hundred sixty patients were enrolled in the TRACK-SCI study. In this overview, basic clinical, imaging, neurological severity, and follow-up data on these patients are presented. Overall, 78.8% of the patients were determined to be surgical candidates and underwent spinal decompression and/or stabilization. Follow-up rates to date at 6 and 12 months are 45% and 36.3%, respectively. Overall resources required for clinical research coordination are also discussed. CONCLUSIONS: The authors established the feasibility of SCI CDE implementation in a multicenter, prospective observational study. Through the application of standardized SCI CDEs and expansion of future multicenter collaborations, they hope to advance SCI research and improve treatment.

Clinical Implementation of Novel Spinal Cord Perfusion Pressure Protocol in Acute Traumatic Spinal Cord Injury at U.S. Level I Trauma Center: TRACK-SCI Study.

OBJECTIVE: We sought to report the safety of implementation of a novel standard of care protocol using spinal cord perfusion pressure (SCPP) maintenance for managing traumatic spinal cord injury (SCI) in lieu of mean arterial pressure goals at a U.S. Level I trauma center. METHODS: Starting in December 2017, blunt SCI patients presenting <24 hours after injury with admission American Spinal Injury Association Impairment Scale (AIS) A-C (or AIS D at neurosurgeon discretion) received lumbar subarachnoid drain (LSAD) placement for SCPP monitoring in the intensive care unit and were included in the TRACK-SCI (Transforming Research and Clinical Knowledge in Spinal Cord Injury) data registry. This SCPP protocol comprises standard care at our institution. SCPPs were monitored for 5 days (goal ≥65 mm Hg) achieved through intravenous fluids and vasopressor support. AISs were assessed at admission and day 7. RESULTS: Fifteen patients enrolled to date were aged 60.5 ± 17 years. Injury levels were 93.3% (cervical) and 6.7% (thoracic). Admission AIS was 20.0%/20.0%/26.7%/33.3% for A/B/C/D. All patients maintained mean SCPP ≥65 mm Hg during monitoring. Fourteen of 15 cases required surgical decompression and stabilization with time to surgery 8.8 ± 7.1 hours (71.4% <12 hours). At day 7, 33.3% overall and 50% of initial AIS A-C had an improved AIS. Length of stay was 14.7 ± 8.3 days. None had LSAD-related complications. There were 7 respiratory complications. One patient expired after transfer to comfort care. CONCLUSIONS: In our initial experience of 15 patients with acute SCI, standardized SCPP goal-directed care based on LSAD monitoring for 5 days was feasible. There were no SCPP-related complications. This is the first report of SCPP implementation as clinical standard of care in acute SCI.