There is convincing preclinical evidence that early decompression in the setting of spinal cord injury (SCI) improves neurologic outcomes. However, the effect of early surgical decompression in ...patients with acute SCI remains uncertain. Our objective was to evaluate the relative effectiveness of early (<24 hours after injury) versus late (≥ 24 hours after injury) decompressive surgery after traumatic cervical SCI.
We performed a multicenter, international, prospective cohort study (Surgical Timing In Acute Spinal Cord Injury Study: STASCIS) in adults aged 16-80 with cervical SCI. Enrolment occurred between 2002 and 2009 at 6 North American centers. The primary outcome was ordinal change in ASIA Impairment Scale (AIS) grade at 6 months follow-up. Secondary outcomes included assessments of complications rates and mortality.
A total of 313 patients with acute cervical SCI were enrolled. Of these, 182 underwent early surgery, at a mean of 14.2(± 5.4) hours, with the remaining 131 having late surgery, at a mean of 48.3(± 29.3) hours. Of the 222 patients with follow-up available at 6 months post injury, 19.8% of patients undergoing early surgery showed a ≥ 2 grade improvement in AIS compared to 8.8% in the late decompression group (OR = 2.57, 95% CI:1.11,5.97). In the multivariate analysis, adjusted for preoperative neurological status and steroid administration, the odds of at least a 2 grade AIS improvement were 2.8 times higher amongst those who underwent early surgery as compared to those who underwent late surgery (OR = 2.83, 95% CI:1.10,7.28). During the 30 day post injury period, there was 1 mortality in both of the surgical groups. Complications occurred in 24.2% of early surgery patients and 30.5% of late surgery patients (p = 0.21).
Decompression prior to 24 hours after SCI can be performed safely and is associated with improved neurologic outcome, defined as at least a 2 grade AIS improvement at 6 months follow-up.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. Spine surgeons must consider a large quantity of ...information relating to disease presentation, imaging features, and patient characteristics to determine if a patient will benefit from surgery for DCM. We applied a supervised machine learning approach to develop a classification model to predict individual patient outcome after surgery for DCM. Patients undergoing surgery for DCM as a part of the AOSpine CSM-NA or CSM-I prospective, multi-centre studies were included in the analysis. Out of 757 patients 605, 583, and 539 patients had complete follow-up information at 6, 12, and 24 months respectively and were included in the analysis. The primary outcome was improvement in the SF-6D quality of life indicator score by the minimum clinically important difference (MCID). The secondary outcome was improvement in the modified Japanese Orthopedic Association (mJOA) score by the MCID. Predictor variables reflected information about pre-operative disease severity, disease presentation, patient demographics, and comorbidities. A machine learning approach of feature engineering, data pre-processing, and model optimization was used to create the most accurate predictive model of outcome after surgery for DCM. Following data pre-processing 48, 108, and 101 features were chosen for model training at 6, 12, and 24 months respectively. The best performing predictive model used a random forest structure and had an average area under the curve (AUC) of 0.70, classification accuracy of 77%, and sensitivity of 78% when evaluated on a testing cohort that was not used for model training. Worse pre-operative disease severity, longer duration of DCM symptoms, older age, higher body weight, and current smoking status were associated with worse surgical outcomes. We developed a model that predicted positive surgical outcome for DCM with good accuracy at the individual patient level on an independent testing cohort. Our analysis demonstrates the applicability of machine-learning to predictive modeling in spine surgery.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Although there is a strong biological rationale for early decompression of the injured spinal cord, the influence of the timing of surgical decompression for acute spinal cord injury (SCI) remains ...debated, with substantial variability in clinical practice. We aimed to objectively evaluate the effect of timing of decompressive surgery for acute SCI on long-term neurological outcomes.
We did a pooled analysis of individual patient data derived from four independent, prospective, multicentre data sources, including data from December, 1991, to March, 2017. Three of these studies had been published; of these, only one study previously specifically analysed the effect of the timing of surgical decompression. These four datasets were selected because they were among the highest quality acute SCI datasets available and contained highly granular data. Individual patient data were obtained by request from study authors. All patients who underwent decompressive surgery for acute SCI within these datasets were included. Patients were stratified into early (<24 h after spinal injury) and late (≥24 h after spinal injury) decompression groups. Neurological outcomes were assessed by American Spinal Injury Association (ASIA), or International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI), examination. The primary endpoint was change in total motor score from baseline to 1 year after spinal injury. Secondary endpoints were ASIA Impairment Scale (AIS) grade and change in upper-extremity motor, lower-extremity motor, light touch, and pin prick scores after 1 year. One-stage meta-analyses were done by hierarchical mixed-effects regression adjusting for baseline score, age, mechanism of injury, AIS grade, level of injury, and administration of methylprednisolone. Effect sizes were summarised by mean difference (MD) for sensorimotor scores and common odds ratio (cOR) for AIS grade, with corresponding 95% CIs. As a secondary analysis, change in total motor score was regressed against time to surgical decompression (h) as a continuous variable, using a restricted cubic spline with adjustment for the same covariates as in the primary analysis.
We identified 1548 eligible patients from the four datasets. Outcome data at 1 year after spinal injury were available for 1031 patients (66·6%). Patients who underwent early surgical decompression (n=528) experienced greater recovery than patients who had late decompression surgery (n=1020) at 1 year after spinal injury; total motor scores improved by 23·7 points (95% CI 19·2–28·2) in the early surgery group versus 19·7 points (15·3–24·0) in the late surgery group (MD 4·0 points 1·7–6·3; p=0·0006), light touch scores improved by 19·0 points (15·1–23·0) vs 14·8 points (11·2–18·4; MD 4·3 1·6–7·0; p=0·0021), and pin prick scores improved by 18·3 points (13·7–22·9) versus 14·2 points (9·8–18·6; MD 4·0 1·5–6·6; p=0·0020). Patients who had early decompression also had better AIS grades at 1 year after surgery, indicating less severe impairment, compared with patients who had late surgery (cOR 1·48 95% CI 1·16–1·89; p=0·0019). When time to surgical decompression was modelled as a continuous variable, there was a steep decline in change in total motor score with increasing time during the first 24–36 h after injury (p<0·0001); and after 36 h, change in total motor score plateaued.
Surgical decompression within 24 h of acute SCI is associated with improved sensorimotor recovery. The first 24–36 h after injury appears to represent a crucial time window to achieve optimal neurological recovery with decompressive surgery following acute SCI.
None.
...although the age-standardised incidence of TBI in 2016 was nearly 30 times greater than that of SCI (369 per 100 000 vs 13 per 100 000), the age-standardised prevalence of TBI was only about ...double that of SCI (759 per 100 000 vs 368 per 100 000), and the age-standardised YLD rate for TBI was lower than that of SCI (111 per 100 000 vs 130 per 100 000). ...this study showed that the age-standardised incidence and prevalence of SCI remained stable globally from 1990 to 2016. ...with demographic shifts, the overall pattern and morphology of these injuries are likely to have changed despite stability in the overall incidence, and such changes in distribution might vary by geographical region. ...it would be prudent to examine how the age composition and patterns and mechanisms of injury among patients with SCI (and TBI) have changed over time and across different locations.
There are currently about 85 000 Canadians living with spinal cord injuries, more than half of which are secondary to trauma.1 As the population ages, the incidence and prevalence of traumatic spinal ...cord injury are expected to increase, primarily as a result of fall-related injuries among older adults2. Therefore, treating spinal cord injuries is relevant not only to spine surgeons and physiatrists, but also to the general clinician who will increasingly encounter such patients in the emergency department or family practice. The initial trauma, or primary injury to the spinal cord, starts a sequence of pathological events collectively referred to as secondary injury. These secondary mechanisms begin within seconds of the primary injury and continue for several weeks thereafter, leading to an expanded region of tissue destruction (Figure 1). The initial disruption of the spinal cord vasculature leads to the development of microhemorrhages in the grey and white matter, interstitial edema and the release of coagulation factors and vasoactive amines.3 These events promote thrombosis and vasospasm of the microvasculature of the spinal cord causing tissue hypoxia and impaired neuronal homeostasis. At the cellular level, impairments include ionic imbalance, peroxidation of membrane lipids, formation of free radicals and release of toxic levels of the excitatory neurotransmitter glutamate.4 Neuroprotective agents act to mitigate secondary injury mechanisms to reduce the extent of neural damage. We performed a comprehensive literature search of MEDLINE for the key words "spinal cord injury" and the medical subheading "treatment." We limited the search to clinical articles published between 1980 and 2012 in English journals. We excluded studies involving animals, review articles and case reports. We supplemented this strategy by searching the Cochrane Database of Systematic Reviews for the term "spinal cord injury." We identified and reviewed 401 abstracts for relevance to the topic. We selected 45 abstracts for which we obtained the full-text version to use as the basis for this review. In addition, we reviewed the 2002 American Association of Neurological Surgeons/Congress of Neurological Surgeons cervical spinal cord injury consensus guidelines, as well as the Consortium for Spinal Cord Medicine 2008 spinal cord injury early acute management clinical practice guidelines.
Traumatic spinal cord injury (SCI) has devastating consequences for the physical, social and vocational well-being of patients. The demographic of SCIs is shifting such that an increasing proportion ...of older individuals are being affected. Pathophysiologically, the initial mechanical trauma (the primary injury) permeabilizes neurons and glia and initiates a secondary injury cascade that leads to progressive cell death and spinal cord damage over the subsequent weeks. Over time, the lesion remodels and is composed of cystic cavitations and a glial scar, both of which potently inhibit regeneration. Several animal models and complementary behavioural tests of SCI have been developed to mimic this pathological process and form the basis for the development of preclinical and translational neuroprotective and neuroregenerative strategies. Diagnosis requires a thorough patient history, standardized neurological physical examination and radiographic imaging of the spinal cord. Following diagnosis, several interventions need to be rapidly applied, including haemodynamic monitoring in the intensive care unit, early surgical decompression, blood pressure augmentation and, potentially, the administration of methylprednisolone. Managing the complications of SCI, such as bowel and bladder dysfunction, the formation of pressure sores and infections, is key to address all facets of the patient's injury experience.
Patients with mild degenerative cervical myelopathy (DCM) are often managed non-operatively, and surgery is recommended if neurological progression occurs. However, detection of progression is often ...subjective. Quantitative MRI (qMRI) directly measures spinal cord (SC) tissue changes, detecting axonal injury, demyelination, and atrophy. This longitudinal study compared multiparametric qMRI with clinical measures of progression in non-operative DCM patients.
26 DCM patients were followed. Clinical data included modified Japanese Orthopedic Association (mJOA) and additional assessments. 3T qMRI data included cross sectional area, diffusion fractional anisotropy, magnetization transfer ratio, and T2*-weighted white/grey matter signal ratio, extracted from the compressed SC and above/below. Progression was defined as 1) patients' subjective impression, 2) 2-point mJOA decrease, 3) ≥3 clinical measures worsening ≥5%, 4) increased compression on MRI, or 5) ≥1 of 10 qMRI measures or composite score worsening (p < 0.004, corrected).
Follow-up (13.5 ± 4.9 months) included mJOA in all 26 patients, MRI in 25, and clinical/qMRI in 22. 42.3% reported subjective worsening, compared with mJOA (11.5%), MRI (20%), comprehensive assessments (54.6%), and qMRI (68.2%). Relative to subjective worsening, qMRI showed 100% sensitivity and 53.3% specificity compared with comprehensive assessments (75%, 60%), mJOA (27.3%, 100%), and MRI (18.2%, 81.3%). A decision-making algorithm incorporating qMRI identified progression and recommended surgery for 11 subjects (42.3%).
Quantitative MRI shows high sensitivity to detect myelopathic progression. Our results suggest that neuroplasticity and behavioural adaptation may mask progressive SC tissue injury. qMRI appears to be a useful method to confirm subtle myelopathic progression in individual patients, representing an advance toward clinical translation of qMRI.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord dysfunction in adults worldwide. DCM encompasses various acquired (age-related) and congenital pathologies related to ...degeneration of the cervical spinal column, including hypertrophy and/or calcification of the ligaments, intervertebral discs and osseous tissues. These pathologies narrow the spinal canal, leading to chronic spinal cord compression and disability. Owing to the ageing population, rates of DCM are increasing. Expeditious diagnosis and treatment of DCM are needed to avoid permanent disability. Over the past 10 years, advances in basic science and in translational and clinical research have improved our understanding of the pathophysiology of DCM and helped delineate evidence-based practices for diagnosis and treatment. Surgical decompression is recommended for moderate and severe DCM; the best strategy for mild myelopathy remains unclear. Next-generation quantitative microstructural MRI and neurophysiological recordings promise to enable quantification of spinal cord tissue damage and help predict clinical outcomes. Here, we provide a comprehensive, evidence-based review of DCM, including its definition, epidemiology, pathophysiology, clinical presentation, diagnosis and differential diagnosis, and non-operative and operative management. With this Review, we aim to equip physicians across broad disciplines with the knowledge necessary to make a timely diagnosis of DCM, recognize the clinical features that influence management and identify when urgent surgical intervention is warranted.
Abstract
Machine learning (ML) holds great promise in transforming healthcare. While published studies have shown the utility of ML models in interpreting medical imaging examinations, these are ...often evaluated under laboratory settings. The importance of real world evaluation is best illustrated by case studies that have documented successes and failures in the translation of these models into clinical environments. A key prerequisite for the clinical adoption of these technologies is demonstrating generalizable ML model performance under real world circumstances. The purpose of this study was to demonstrate that ML model generalizability is achievable in medical imaging with the detection of intracranial hemorrhage (ICH) on non-contrast computed tomography (CT) scans serving as the use case. An ML model was trained using 21,784 scans from the RSNA Intracranial Hemorrhage CT dataset while generalizability was evaluated using an external validation dataset obtained from our busy trauma and neurosurgical center. This real world external validation dataset consisted of every unenhanced head CT scan (n = 5965) performed in our emergency department in 2019 without exclusion. The model demonstrated an AUC of 98.4%, sensitivity of 98.8%, and specificity of 98.0%, on the test dataset. On external validation, the model demonstrated an AUC of 95.4%, sensitivity of 91.3%, and specificity of 94.1%. Evaluating the ML model using a real world external validation dataset that is temporally and geographically distinct from the training dataset indicates that ML generalizability is achievable in medical imaging applications.
Background: The ability of frailty compared to age alone to predict adverse events in the surgical management of Degenerative Cervical Myelopathy (DCM) has not been defined in the literature. ...Methods: 41,369 patients with a diagnosis of DCM undergoing surgery were collected from the National Surgical Quality Improvement Program (NSQIP) Database 2010–2018. Univariate analysis for each measure of frailty (modified frailty index 11- and 5-point; MFI-11, MFI-5), modified Charlson Co-morbidity index and ASA grade) were calculated for the following outcomes: mortality, major complication, unplanned reoperation, unplanned readmission, length of hospital stay, and discharge to a non-home destination. Multivariable modeling of age and frailty with a base model was performed to define the discriminative ability of each measure. Results: Age and frailty have a significant effect on all outcomes, but the MFI-5 has the largest effect size. Increasing frailty correlated significantly with the risk of perioperative adverse events, longer hospital stay, and risk of a non-home discharge destination. Multivariable modeling incorporating MFI-5 with age and the base model had a robust predictive value (0.85). MFI-5 had a high categorical assessment correlation with a MFI-11 of 0.988 (p < 0.001). Conclusions and Relevance: Measures of frailty have a greater effect size and a higher discriminative value to predict adverse events than age alone. MFI-5 categorical assessment is essentially equivalent to the MFI-11 score for DCM patients. A multivariable model using MFI-5 provides an accurate predictive tool that has important clinical applications.
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