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Anesthesiologists work to prevent or minimize secondary injury of the nervous system and improve the outcome of medical procedures.To this end,anesthesiologists must have a thorough understanding of pathophysiology and optimize their skills and equipment to make an anesthesia plan.Anesthesiologists should conduct careful physical examinations of patients and consider neuroprotection at preoperative interviews,consider cervical spinal cord movement and compression during airway management,and suggest awake fiberoptic bronchoscope intubation for stable patients and direct laryngoscopy with manual in-line immobilization in emergency situations.During induction,anesthesiologists should avoid hypotension and depolarizing muscle relaxants.Mean artery pressure should be maintained within 85–90 mmHg（1 mmHg = 0.133 kPa; vasoactive drug selection and fluid management）.Normal arterial carbon dioxide pressure and normal blood glucose levels should be maintained.Intraoperative neurophysiological monitoring is a useful option.Anesthesiologists should be attentive to postoperative respiratory insufficiency（carefully considering postoperative extubation）,thrombus,and infection.In conclusion,anesthesiologists should carefully plan the treatment of patients with acute cervical spinal cord injuries to protect the nervous system and improve patient outcome.

Some studies have suggested that early surgical treatment can effectively improve the prognosis of cervical spinal cord injury without radiological abnormality, but no research has focused on the development of a prognostic model of cervical spinal cord injury without radiological abnormality. This retrospective analysis included 43 patients with cervical spinal cord injury without radiological abnormality. Seven potential factors were assessed: age, sex, external force strength causing damage, duration of disease, degree of cervical spinal stenosis, Japanese Orthopaedic Association score, and physiological cervical curvature. A model was established using multiple binary logistic regression analysis. The model was evaluated by concordant profiling and the area under the receiver operating characteristic curve. Bootstrapping was used for internal validation. The prognostic model was as follows: logit(P) = −25.4545 + 21.2576VALUE + 1.2160SCORE − 3.4224TIME, where VALUE refers to the Pavlov ratio indicating the extent of cervical spinal stenosis, SCORE refers to the Japanese Orthopaedic Association score (0-17) after the operation, and TIME refers to the disease duration (from injury to operation). The area under the receiver operating characteristic curve for all patients was 0.8941 (95% confidence interval, 0.7930-0.9952). Three factors assessed in the predictive model were associated with patient outcomes: a great extent of cervical stenosis, a poor preoperative neurological status, and a long disease duration. These three factors could worsen patient outcomes. Moreover, the disease prognosis was considered good when logit(P) ≥ −2.5105. Overall, the model displayed a certain clinical value. This study was approved by the Biomedical Ethics Committee of the Second Affiliated Hospital of Xi'an Jiaotong University, China (approval number: 2018063) on May 8, 2018.

Paralysis of the upper extremities following cervical spinal cord injury (SCI) significantly impairs one's ability to live independently. While regaining hand function or grasping ability is considered one of the most desired functions in tetraplegics, limited therapeutic development in this direction has been demonstrated to date in humans with a high severe cervical injury. The underlying hypothesis is that after severe cervical SCI, nonfunctional sensory-motor networks within the cervical spinal cord can be transcutaneously neuromodulated to physiological states that enable and amplify voluntary control of the hand. Improved voluntary hand function occurred within a single session in every subject tested. After eight sessions of non-invasive transcutaneous stimulation, combined with training over 4 weeks, maximum voluntary hand grip forces increased by ∼325% (in the presence of stimulation) and ∼225% (when grip strength was tested without simultaneous stimulation) in chronic cervical SCI subjects (American Spinal Injury Association Impairment Scale [AIS] B, n = 3; AIS C, n = 5) 1-21 years post-injury). Maximum grip strength improved in both the left and right hands and the magnitude of increase was independent of hand dominance. We refer to the neuromodulatory method used as transcutaneous enabling motor control to emphasize that the stimulation parameters used are designed to avoid directly inducing muscular contractions, but to enable task performance according to the subject's voluntary intent. In some subjects, there were improvements in autonomic function, lower extremity motor function, and sensation below the level of the lesion. Although a neuromodulation-training effect was observed in every subject tested, further controlled and blinded studies are needed to determine the responsiveness of a larger and broader population of subjects varying in the type, severity, and years post-injury. It appears rather convincing, however, that a “central pattern generation” phenomenon as generally perceived in the lumbosacral networks in controlling stepping neuromodulator is not a critical element of spinal neuromodulation to regain function among spinal networks.

Background Individuals with a clinically complete spinal cord injury are unable to stand independently without external assistance. Studies have shown the combination of spinal cord epidural stimulation (scES) targeted for standing with activity-based recovery training (ABRT) can promote independence of standing in individuals with spinal cord injury. This cohort study aimed to assess the effects of stand-ABRT with scES in individuals with cervical chronic spinal cord injury. We evaluated the ability of these individuals to stand independently from physical assistance across multiple sessions. Methods Thirty individuals participated in this study, all unable to stand independently at the start of the intervention. Individuals were participating in a randomized clinical trial and received stand-ABRT in addition to targeted cardiovascular scES or voluntary scES. During the standing intervention, participants were asked to stand 2 h a day, 5 days a week for 80 sessions (Groups 1 and 2) or 160 sessions (Groups 3 and 4). Results A total of 3,524 training days were considered for analysis. Group 1 had 507 days, group 2 with 578 days, and 1152 and 1269 days for groups 3 and 4 respectively. 71% of sessions reached the two-hour standing goal. All individuals achieved outcomes of lower limb independent extension with spinal cord epidural stimulation, with a wide range throughout a training day. Sixteen participants achieved unassisted hip extension while maintaining unassisted bilateral knee and trunk extension. Participants receiving initial voluntary scES training performed better in unassisted bilateral knee and trunk extension than those receiving initial cardiovascular scES. The lower-limb standing activation pattern changes were consistent with the greater standing independence observed by all groups. Conclusions Individuals with chronic cervical spinal cord injury were able to achieve various levels of extension without manual assistance during standing with balance assist following stand-ABRT with scES. These results provide evidence that scES modulates network excitability of the injured spinal cord to allow for the integration of afferent and supraspinal descending input to promote standing in individuals with spinal cord injury. Trial registration The study was registered on Clinical Trials.gov (NCT03364660) prior to subject enrollment.

Biomarkers of acute human spinal cord injury (SCI) could provide a more objective measure of spinal cord damage and a better predictor of neurological outcome than current standardized neurological assessments. In SCI, there is growing interest in establishing biomarkers from cerebrospinal fluid (CSF) and from magnetic resonance imaging (MRI). Here, we compared the ability of CSF and MRI biomarkers to classify injury severity and predict neurological recovery in a cohort of acute cervical SCI patients. CSF samples and MRI scans from 36 acute cervical SCI patients were examined. From the CSF samples taken 24 h post-injury, the concentrations of inflammatory cytokines (interleukin [IL]-6, IL-8, monocyte chemotactic protein-1), and structural proteins (tau, glial fibrillary acidic protein, and S100β) were measured. From the pre-operative MRI scans, we measured intramedullary lesion length, hematoma length, hematoma extent, CSF effacement, cord expansion, and maximal spinal cord compression. Baseline and 6-month post-injury assessments of American Spine Injury Association Impairment Scale (AIS) grade and motor score were conducted. Both MRI measures and CSF biomarker levels were found to correlate with baseline injury grade, and in combination they provided a stronger model for classifying baseline AIS grade than CSF or MRI biomarkers alone. For predicting neurological recovery, the inflammatory CSF biomarkers best predicted AIS grade conversion, whereas structural biomarker levels best predicted motor score improvement. A logistic regression model utilizing CSF biomarkers alone had a 91.2% accuracy at predicting AIS conversion, and was not strengthened by adding MRI features or even knowledge of the baseline AIS grade. In a direct comparison of MRI and CSF biomarkers, the CSF biomarkers discriminate better between different injury severities, and are stronger predictors of neurological recovery in terms of AIS grade and motor score improvement. These findings demonstrate the utility of measuring the acute biological responses to SCI as biomarkers of injury severity and neurological prognosis.

Study design Cross-sectional Database Study. Objective While the American Spinal Injury Association (ASIA) Impairment Scale is the standard for assessing spinal cord injuries (SCI), it has limitations due to subjectivity and impracticality. Advances in machine learning (ML) and image recognition have spurred research into their use for outcome prediction. This study aims to analyze deep learning techniques for identifying and classifying cervical SCI severity from MRI scans. Methods The study included patients with traumatic and nontraumatic cervical SCI admitted from 2019 to 2022. MRI images were labeled by two senior resident physicians. A deep convolutional neural network was trained using axial and sagittal cervical MRI images from the dataset. Model performance was assessed using Dice Score and IoU to measure segmentation accuracy by comparing predicted and ground truth masks. Classification accuracy was evaluated with the F1 Score, balancing false positives and negatives. Result In the axial spinal cord segmentation, we achieved a Dice score of 0.94 for and IoU score of 0.89. In the sagittal spinal cord segmentation, we obtained Dice score up to 0.9201 and IoU scores up to 0.8541. The model for axial image score classification gave a satisfactory result with an F1 score of 0.72 and AUC of 0.79. Conclusion Our models successfully identified cervical SCI on T2-weighted MR images with satisfactory performance. Further research is needed to develop more advanced models for predicting patient outcomes in SCI cases.

Traumatic cervical spinal cord injury (TCSCI) often causes varying degrees of motor dysfunction, common assessed by the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), in association with the American Spinal Injury Association (ASIA) Impairment Scale. Accurate prediction of motor function recovery is extremely important for formulating effective diagnosis, therapeutic and rehabilitation programs. The aim of this study is to investigate the validity of a novel nested ensemble algorithm that uses the very early ASIA motor score (AMS) of ISNCSCI examination to predict motor function recovery 6 months after injury in TCSCI patients. This retrospective study included complete data of 315 TCSCI patients. The dataset consisting of the first AMS at ≤ 24 h post-injury and follow-up AMS at 6 months post-injury was divided into a training set (80%) and a test set (20%). The nested ensemble algorithm was established in a two-stage manner. Support Vector Classification (SVC), Adaboost, Weak-learner and Dummy were used in the first stage, and Adaboost was selected as second-stage model. The prediction results of the first stage models were uploaded into second-stage model to obtain the final prediction results. The model performance was evaluated using precision, recall, accuracy, F1 score, and confusion matrix. The nested ensemble algorithm was applied to predict motor function recovery of TCSCI, achieving an accuracy of 80.6%, a F1 score of 80.6%, and balancing sensitivity and specificity. The confusion matrix showed few false-negative rate, which has crucial practical implications for prognostic prediction of TCSCI. This novel nested ensemble algorithm, simply based on very early AMS, provides a useful tool for predicting motor function recovery 6 months after TCSCI, which is graded in gradients that progressively improve the accuracy and reliability of the prediction, demonstrating a strong potential of ensemble learning to personalize and optimize the rehabilitation and care of TCSCI patients.

PurposeTo investigate the impact of early post-injury respiratory dysfunction for neurological and ambulatory ability recovery in patients with cervical spinal cord injury (SCI) and/or fractures.MethodsWe included 1,353 elderly patients with SCI and/or fractures from 78 institutions in Japan. Patients who required early tracheostomy and ventilator management and those who developed respiratory complications were included in the respiratory dysfunction group, which was further classified into mild and severe respiratory groups based on respiratory weaning management. Patient characteristics, laboratory data, neurological impairment scale scores, complications at injury, and surgical treatment were evaluated. We performed a propensity score-matched analysis to compare neurological outcomes and mobility between groups.ResultsOverall, 104 patients (7.8%) had impaired respiratory function. In propensity score-matched analysis, the respiratory dysfunction group had a lower home discharge and ambulation rates (p = 0.018, p = 0.001, respectively), and higher rate of severe paralysis (p < 0.001) at discharge. At the final follow-up, the respiratory dysfunction group had a lower ambulation rate (p = 0.004) and higher rate of severe paralysis (p < 0.001). Twenty-six patients with severe disability required respiratory management for up to 6 months post-injury and died of respiratory complications. The mild and severe respiratory dysfunction groups had a high percentage of severe paraplegic cases with low ambulatory ability; there was no significant difference between them. The severe respiratory dysfunction group tended to have a poorer prognosis. ConclusionRespiratory dysfunction in elderly patients with SCI and/or cervical fracture in the early post-injury period reflects the severity of the condition and may be a useful prognostic predictor.

ObjectiveTo develop a classification and regression tree (CART) model to predict the need of tracheostomy in patients with traumatic cervical spinal cord injury (TCSCI) and to quantify scores of risk factors to make individualized clinical assessments.MethodsThe clinical characteristics of patients with TCSCI admitted to our hospital from January 2014 to December 2020 were retrospectively analyzed. The demographic characteristics (gender, age, smoking history), mechanism of injury, injury characteristics (ASIA impairment grades, neurological level of impairment, injury severity score), preexisting lung disease and preexisting medical conditions were statistically analyzed. The risk factors of tracheostomy were analyzed by univariate logistic regression analysis (ULRA) and multiple logistic regression analysis (MLRA). The CART model was established to predict tracheostomy.ResultsThree hundred and forty patients with TCSCI met the inclusion criteria, in which 41 patients underwent the tracheostomy. ULRA and MLRA showed that age > 50, ISS > 16, NLI > C5 and AIS A were significantly associated with tracheostomy. The CART model showed that AIS A and NLI > C5 were at the first and second decision node, which had a significant influence on the decision of tracheostomy. The final scores for tracheostomy from CART algorithm, composed of age, ISS, NLI and AIS A with a sensitivity of 0.78 and a specificity of 0.96, could also predict tracheostomy.ConclusionThe establishment of CART model provided a certain clinical guidance for the prediction of tracheostomy in TCSCI. Quantifications of risk factors enable accurate prediction of individual patient risk of need for tracheostomy.

This study aims to assess the cardiovascular, respiratory, and gas metabolic responses elicited during functional electrical stimulation (FES)-cycling exercise in individuals with subacute traumatic motor-complete cervical spinal cord injury (CSCI) classified as ASIA Impairment Scale (AIS) grades A and B. This assessment was conducted utilizing cardiopulmonary exercise testing (CPET). Participants who met the eligibility criteria, characterized by subacute traumatic motor-complete CSCI, first underwent static pulmonary function testing. This was followed by a recumbent FES-cycling protocol, which involved incremental speed increases of 5 revolutions per minute (RPM). Throughout the exercise, continuous monitoring of electrocardiographic data, blood pressure, respiratory parameters, and gas metabolism was performed using CPET. Key physiological metrics, including minute ventilation (VE), tidal volume (VT), systolic blood pressure (SBP), diastolic blood pressure (DBP), heart rate (HR), oxygen uptake (VO 2 ), and oxygen pulse (O 2 pulse), were recorded at 2-minute intervals. A total of 18 participants in the subacute phase of recovery, with an injury duration ranging from 19 to 61 days, completed the study. Static pulmonary function testing indicated the presence of restrictive ventilatory dysfunction in all participants, with 22.2% exhibiting concurrent obstructive ventilatory dysfunction and 77.8% demonstrating a reduced ventilatory reserve. During FES-cycling exercise, significant inter-phase variations were observed across all measured parameters ( p  < 0.05). The variables of VE, SBP, DBP, HR, VO 2 , and O 2 pulse exhibited concordant trends with the progression of RPM, with statistically significant differences identified between successive phases for VE, VO 2 , and O 2 pulse ( p  < 0.05). Conversely, VT displayed discordant trends in relation to RPM. Individuals in the subacute phase of traumatic motor-complete CSCI demonstrate significant acute cardiorespiratory physiological responses to FES cycling exercise. These responses encompass an augmentation in VE, VT, and VO 2 , concomitant with an escalation in HR, O 2 pulse, and BP.