Prediction Of Neurological Outcome Research Articles

Early Clinical Predictors of Neurological Outcome in Children With Asphyxial Out-of-Hospital Cardiac Arrest Treated With Therapeutic Hypothermia.

Aim: The aim of the current study was to identify early clinical predictors of neurologic outcome in children with asphyxial out-of-hospital cardiac arrest (OHCA) treated with therapeutic hypothermia.Methods: The present retrospective cohort study of comatose children treated with therapeutic hypothermia or normothermia after asphyxial OHCA was conducted between January 2010 and June 2018. All children aged between 1 month and 18 years of age, with a history of at least 3 min of chest compressions were eligible for inclusion. Their 6-month neurological outcomes were evaluated using the Pediatric Cerebral Performance Category (PCPC) score and early clinical predictors were determined.Results: A total of 100 patients met the eligibility criteria for the study. Sixty-four (64%) of the children were male, and the mean age of participants was 4.59 ± 5.45 years. Forty (40%) of the children had underlying disorders. The overall 1-month survival rate was 36%. Only 12 (12%) of the patients had favorable outcomes (PCPC ≤ 2). Thirty-four (34%) of the 100 children were receiving therapeutic hypothermia. In the univariate analysis, an initial lactate level of ≤ 80 mg/dL, a Glasgow coma scale (GCS) score of 5–8, a GCS motor score ≥4 and a present pupil reflex before therapeutic hypothermia, were significantly associated with favorable 6-month neurological outcomes. However, after the multivariate logistic analysis, only initial serum lactate level and GCS before therapeutic hypothermia were significantly associated with favorable 6-month neurological outcomes.Conclusion: Initial serum lactate level and GCS before therapeutic hypothermia were significantly associated with 6-month favorable neurological outcomes in pediatric asphyxial OHCA patients who were treated with therapeutic hypothermia. Therefore, these early clinical predictors could be helpful to facilitate future clinical research in children with asphyxial OHCA treated with therapeutic hypothermia.

What is the Role of Post Acute EEG in Prediction of Late Neurological Outcome in Severe Disorders of Consciousness?

What is the Role of Post Acute EEG in Prediction of Late Neurological Outcome in Severe Disorders of Consciousness?

Ultra-early neurologic outcome prediction of out-of-hospital cardiac arrest survivors using combined diffusion-weighted imaging findings and quantitative analysis of apparent diffusion coefficient

AimThis study examined whether the presence of cortical necrosis (CN) on ultra-early diffusion-weighted imaging (DWI) and the severity of cytotoxic oedema (CytE) with cerebral oedema (CbrE), measured using quantitative analysis of apparent diffusion coefficient (ADC), could predict neurological outcomes before targeted temperature management in out-of-hospital cardiac arrest survivors (OHCAs). MethodsIn this retrospective study, the first DWI with ADC scans was performed within 6 h; the second was obtained between 72 and 96 h after return of spontaneous circulation. The primary outcome was neurological outcomes at 6 months after OHCA. The % voxels of ADC value (PV) was calculated; CbrE and CytE values were > or < than 650−6 mm2/s, respectively. The best performance PV was obtained from CytE (thld-CytE) and CbrE values (thld-CbrE). Prognostic performances of CN, thld-CytE, thld-CbrE, and converted scores were calculated in combination. The changes in DWI findings and the difference between the PV (ΔPV) from the first and second DWI were analysed. ResultsThirty-six patients were included. CN (area under receiver operating characteristic curve [AUC] = 0.800), thld-CytE (PV420; AUC = 0.730), and thld-CbrE (PV1090; AUC = 0.775) showed meaningful performance, and the combined score showed best performance for poor outcome prediction (AUC = 0.956). DWI findings of CN patients was worse at the second DWI. ΔPV significantly increased in the poor outcome group, CN patients, and the group including both, thld-CytE and thld-CbrE. ConclusionsIn OHCAs, ultra-early DWI with ADC could successfully predict poor neurological outcomes by combining scores of CN, thld-CytE, and thld-CbrE.

Efficacy of Ultra-Early (< 12 h), Early (12-24 h), and Late (>24-138.5 h) Surgery with Magnetic Resonance Imaging-Confirmed Decompression in American Spinal Injury Association Impairment Scale Grades A, B, and C Cervical Spinal Cord Injury.

In cervical traumatic spinal cord injury (TSCI), the therapeutic effect of timing of surgery on neurological recovery remains uncertain. Additionally, the relationship between extent of decompression, imaging biomarker evidence of injury severity, and outcome is incompletely understood. We investigated the effect of timing of decompression on long-term neurological outcome in patients with complete spinal cord decompression confirmed on postoperative magnetic resonance imaging (MRI). American Spinal Injury Association (ASIA) Impairment Scale (AIS) grade conversion was determined in 72 AIS grades A, B, and C patients 6 months after confirmed decompression. Thirty-two patients underwent decompressive surgery ultra-early (< 12 h), 25 underwent decompressive surgery early (12–24 h), and 15 underwent decompressive surgery late (> 24–138.5 h) after injury. Age, gender, injury mechanism, intramedullary lesion length (IMLL) on MRI, admission ASIA motor score, and surgical technique were not statistically different among groups. Motor complete patients (p = 0.009) and those with fracture dislocations (p = 0.01) tended to be operated on earlier. Improvement of one grade or more was present in 55.6% of AIS grade A, 60.9% of AIS grade B, and 86.4% of AIS grade C patients. Admission AIS motor score (p = 0.0004) and pre-operative IMLL (p = 0.00001) were the strongest predictors of neurological outcome. AIS grade improvement occurred in 65.6%, 60%, and 80% of patients who underwent decompression ultra-early, early, and late, respectively (p = 0.424). Multiple regression analysis revealed that IMLL was the only significant variable predictive of AIS grade conversion to a better grade (odds ratio, 0.908; confidence interval [CI], 0.862–0.957; p < 0.001). We conclude that in patients with post-operative MRI confirmation of complete decompression following cervical TSCI, pre-operative IMLL, not the timing of surgery, determines long-term neurological outcome.

Evaluation of non-traumatic myelopathy using magnetic resonance imaging

Background: Prompt and concise diagnosis of etiologic agent behind Non-Traumatic Myelopathy (NTM) and localization of the site of lesion are essential for prediction of neurological and functional outcomes. Magnetic Resonance Imaging (MRI) plays a key role in evaluation of myelopathy. Objectives: The objective of the present study was to characterize the spinal cord lesions in Non-traumatic Myelopathy and to evaluate the etiological factors leading to NTM. Materials and Methods: A hospital based cross-sectional study was done from November 2017 to May 2019 in a tertiary care centre of South India, where 85 patients with clinical suspicion of NTM were evaluated with MRI of spine. The MRI data collected was analyzed and described. Results: Out of 85 patients in our study group, 44 (51.8%) were males and 41 (48.2%) were females, without any significant gender predilection. The age group ranged from 5 to 83 years, with majority of patients in the 7th decade (25.9%). Degenerative myelopathy was the most common etiology accounting for 57.6% of the patients, followed by infective (28.2%), primary neoplastic (9.4%), congenital (1.1%), demyelinating (1.1%), metastatic (1.1%) and nutritional (1.1%) etiologies. Conclusion: MRI characteristics of the most common lesions were sufficiently distinct to allow them to be differentiated from each other and from most other entities. Other characteristics such as extradural versus intradural, intramedullary versus extramedullary, nature of enhancement on Post Gadolinium study, the presence of epidural, prevertebral and paravertebral involvement permit further differentiation among the various other abnormalities. MRI is a very sensitive, specific, non-invasive radiation-free modality for evaluation of NTM.

XGBoost, a Machine Learning Method, Predicts Neurological Recovery in Patients with Cervical Spinal Cord Injury.

The accurate prediction of neurological outcomes in patients with cervical spinal cord injury (SCI) is difficult because of heterogeneity in patient characteristics, treatment strategies, and radiographic findings. Although machine learning algorithms may increase the accuracy of outcome predictions in various fields, limited information is available on their efficacy in the management of SCI. We analyzed data from 165 patients with cervical SCI, and extracted important factors for predicting prognoses. Extreme gradient boosting (XGBoost) as a machine learning model was applied to assess the reliability of a machine learning algorithm to predict neurological outcomes compared with that of conventional methodology, such as a logistic regression or decision tree. We used regularly obtainable data as predictors, such as demographics, magnetic resonance variables, and treatment strategies. Predictive tools, including XGBoost, a logistic regression, and a decision tree, were applied to predict neurological improvements in the functional motor status (ASIA [American Spinal Injury Association] Impairment Scale [AIS] D and E) 6 months after injury. We evaluated predictive performance, including accuracy and the area under the receiver operating characteristic curve (AUC).Regarding predictions of neurological improvements in patients with cervical SCI, XGBoost had the highest accuracy (81.1%), followed by the logistic regression (80.6%) and the decision tree (78.8%). Regarding AUC, the logistic regression showed 0.877, followed by XGBoost (0.867) and the decision tree (0.753). XGBoost reliably predicted neurological alterations in patients with cervical SCI. The utilization of predictive machine learning algorithms may enhance personalized management choices through pre-treatment categorization of patients.

Predictors of Neurological Outcome Following Subaxial Cervical Spine Trauma

BackgroundThe treatment of traumatic subaxial cervical spine injuries remains controversial. The American Spinal Injury Association (ASIA) impairment scale (AIS) is a widely-used metric to score neurological function after spinal cord injury (SCI). Here, we evaluated the outcomes of patients who underwent treatment of subaxial cervical spine injuries to identify predictors of neurologic function after injury and treatment.MethodsWe performed a retrospective logistic regression analysis to determine predictors of neurological outcome; 76 patients met the inclusion criteria and presented for a three-month follow-up. The mean age was 50.6±18.7 years old and the majority of patients were male (n=49, 64%).ResultsThe majority of patients had stable AIS scores at three months (n=56, 74%). A subset of patients showed improvement at three months (n=16, 21%), while a small subset of patients had neurological decline at three months (n=4, 5%). In our model, increasing patient age (odds ratio [OR] 1.39, 1.10-2.61 95% confidence interval [CI], P<0.001) and a previous or current diagnosis of cancer (OR 22.4, 1.25-820 95% CI, P=0.04) significantly increased the odds of neurological decline at three months. In patients treated surgically, we found that delay in surgical treatment (>24 hours) was associated with a decreased odds of neurological improvement (OR 0.24, 0.05-0.99 95% CI, P=0.048). Cervical spine injuries are heterogeneous and difficult to manage.ConclusionWe found that increasing patient age and an oncologic history were associated with neurological deterioration while a delay in surgical treatment was associated with decreased odds of improvement. These predictors of outcome may be used to guide prognosis and treatment decisions.

Abstract 409: Predictive Value of ’OHCA’ and ’C-GRApH’ Score to Predict Neurological Outcome in Cardiac Arrest Patients Treated With Targeted Temperature Management

Introduction: Despite recent advances in critical care, out-of-hospital cardiac arrest (OHCA) patients still have a low probability of survival. For the purpose of an objective assessment of a patient’s risk of death or neurological deficits, several clinical tools have recently been developed. Hypothesis: The first hypothesis is that OHCA and C-GRApH score could predict neurologic outcome after OHCA patients treated with targeted temperature management (TTM). The second hypothesis is that adding neurologic examination to those scores could further improve outcome prediction after OHCA. Methods: This retrospective study included OHCA patients treated with TTM from 2009 to 2017 in a tertiary teaching hospital in Seoul, Korea. We calculated two cardiac arrest specific risk scores (OHCA and C-GRApH) at the time of admission. Initial neurologic examination (Full Outline of UnResponsiveness Brainstem reflexes (FOUR_B) score and Glasgow Coma Scale motor score (GCS_M)) was also evaluated. The primary outcome was neurological outcome at 6 months after CA. Results: Of 311 subjects, 100 (32.2%) had a good neurologic outcome at 6 months after CA. OHCA score had AUC of 0.843 (95% CI 0.797 - 0.888) and C-GRApH score had AUC of 0.774 (95% CI 0.717 - 0.830). Addition of FOUR_B or GCS_M to OHCA score improved prediction of poor neurologic outcome (AUC 0.891, p = 0.001 for FOUR_B and AUC 0.878, p=0.004 for GCS_M). Results were similar for C-GRApH score to predict poor neurologic outcome. Conclusions: This study confirms the good prognostic performance of cardiac arrest specific scores to predict neurological outcomes in OHCA patients treated with TTM. Addition of neurologic examination variables further improved prognostication for neurologic outcome.

Abstract 405: A Machine Learning-Based Prediction of Cardiac Arrest Outcome Using a Large Multi-Center Database

Background: Cardiac arrest (CA) poses a significant risk of death and long-term neurological disability yet there remains a lack of accurate and reliable methods to prognosticate post-CA outcome, indicating a major unmet need. Additionally, no existing CA outcome prediction model utilizes physiological time series (PTS) data, which captures transitions in a patient’s health state at high temporal resolution. Materials and Methods: We screened the Philips eICU database, which includes over 200,000 patients in 200 hospitals, extracting data on CA patients within 24 hours of ICU admission. We first extracted PTS and Electronic Health Record (HER) features and selected our features using nested Random Forest. The outcome labels were neurological state or mortality at ICU discharge. We tested various individual and ensemble machine learning algorithms (GLM, Random Forest, Gradient Boosting, Support Vector Machine, Neural Networks) and optimization techniques (hyperparameter tuning, model stacking, and transfer learning) to maximize the accuracy of outcome prediction. Results: For prediction of neurological outcome, our model combining EHR and PTS features achieved a higher sensitivity (0.78), specificity (0.88), and AUC (0.87±0.01) compared to the APACHE baseline standard model (AUC: 0.74±0.01, sensitivity: 0.77, specificity: 0.63). Also, for prediction of mortality our model (AUC: 0.81±0.01, sensitivity: 0.78, specificity: 0.71) outperformed the APACHE clinical baseline (AUC: 0.75±0.01, sensitivity: 0.86, specificity: 0.56) by 7%. The integration of PTS with EHR data increased mean AUC by 4% for neurological outcome and 2% for mortality. Conclusion: Results demonstrate that for both neurological outcome and mortality prediction, our ensemble model was significantly more effective compared to the baseline APACHE model. Additionally, we find that PTS data adds to the discriminative power of clinical models. With appropriate validation in prospective cohorts, these findings could be used as point-of-care references to aid ICU physicians in clinical decision-making.

Prediction of Neurological Outcome of Children After a Traumatic Brain Injury Based on an Integrated Predictive Model

Prediction of Neurological Outcome of Children After a Traumatic Brain Injury Based on an Integrated Predictive Model

Growth differentiation factor 15 and early prognosis after out-of-hospital cardiac arrest

BackgroundGrowth differentiation factor 15 (GDF-15) is an inflammatory cytokine released in response to tissue injury. It has prognostic value in cardiovascular diseases and other acute and chronic conditions. Here, we explored the value of GDF-15 as an early predictor of neurologic outcome after an out-of-hospital cardiac arrest (OHCA).MethodsProspective registry study of patients in coma after an OHCA, admitted in the intensive cardiac care unit from a single university center. Serum levels of GDF-15 were measured on admission. Neurologic status was evaluated according to the cerebral performance category (CPC) scale. The relationship between GDF-15 levels and poor neurologic outcome at 6 months was analyzed.ResultsAmong 62 patients included, 32 (51.6%) presented poor outcome (CPC 3–5). Patients with CPC 3–5 exhibited significantly higher GDF-15 levels (median, 17.1 [IQR, 11.1–20.4] ng/mL) compared to those with CPC 1–2 (7.6 [IQR, 4.1–13.1] ng/mL; p = 0.004). Multivariable logistic regression analyses showed that age (OR, 1.09; 95% CI 1.01–1.17; p = 0.020), home setting arrest (OR, 8.07; 95% CI 1.61–40.42; p = 0.011), no bystander cardiopulmonary resuscitation (OR, 7.91; 95% CI 1.84–34.01; p = 0.005), and GDF-15 levels (OR, 3.74; 95% CI 1.32–10.60; p = 0.013) were independent predictors of poor outcome. The addition of GDF-15 in a dichotomous manner (≥ 10.8 vs. < 10.8 ng/mL) to the resulting clinical model improved discrimination; it increased the area under the curve from 0.867 to 0.917, and the associated continuous net reclassification improvement was 0.90 (95% CI 0.48–1.44), which allowed reclassification of 37.1% of patients.ConclusionsAfter an OHCA, increased GDF-15 levels were an independent, early predictor of poor neurologic outcome. Furthermore, when added to the most common clinical factors, GDF-15 improved discrimination and allowed patient reclassification.

Long-term Outcomes After Intraprocedural Aneurysm Rupture During Coil Embolization of Unruptured Intracranial Aneurysms

The long-term outcomes of patients with intraprocedural aneurysm rupture (IPR) during endovascular coiling of unruptured intracranial aneurysms (UIAs) remain unclear. We investigated the long-term outcomes and predictors of neurological outcomes in patients who sustained IPR during coil embolization of UIAs. We retrospectively analyzed the medical record of 312 untreated UIAs in 284 patients who underwent endovascular coiling between April 2013 and July2018. The mean follow-up period for the entire cohort was 25.6 months. Twelve patients (3.8%) experienced IPR. The mean aneurysm size in the IPR cohort was significantly smaller than that in the no-IPR cohort (P= 0.045). The IPR cohort had a higher percentage of earlier subarachnoid hemorrhage from another aneurysm (P= 0.019), anterior communicating artery (AComA) aneurysm (P < 0.001), and basilar artery (BA) aneurysm (P= 0.022) than the no-IPR cohort. Neurologic deterioration was observed in 3 patients. The morbidity and mortality rates of the IPR cohort were 25% and 8.3%, respectively. Patients with IPR during coil embolization for AComA aneurysm did not develop neurological deterioration. Two of the 3 patients (66.7%) with a BA aneurysm had neurological deterioration. The proportion of patients with an mRS score of 0-2 at the last follow-up did not differ between the 2 cohorts (P= 0.608). The proportion of functionally independent patients did not differ between patients with and without IPR. Patients with BA aneurysms who developed an IPR tended to exhibit more unfavorable clinical courses than patients with AcomA aneurysms.

Prognostic value of 18F-FDG brain PET as an early indicator of neurological outcomes in a rat model of post-cardiac arrest syndrome

Predicting neurological outcomes in patients with post-cardiac arrest syndrome (PCAS) is crucial for identifying those who will benefit from intensive care. We evaluated the predictive value of 18F-FDG PET. PCAS was induced in Sprague Dawley rats. Baseline and post-3-hour images were acquired. Standardized uptake value (SUV) changes before and after PCAS induction (SUVdelta) and SUV ratios (SUVR) of regional SUV normalized to the whole brain SUV were obtained. The Morris water maze (MWM) test was performed after 2 weeks to evaluate neurological outcomes and rats were classified into two groups based on the result. Of 18 PCAS rats, 8 were classified into the good outcome group. The SUVdelta of forebrain regions were significantly decreased in good outcome group (p < 0.05), while the SUVdelta of hindbrain regions were not significantly different according to outcomes. The SUVR of forebrain regions were significantly higher and the SUVR of hindbrain regions were significantly lower in good outcome group (p < 0.05). Forebrain-to-hindbrain ratio predicted a good neurological outcome with a sensitivity of 90% and specificity of 100% using an optimal cutoff value of 1.22 (AUC 0.969, p < 0.05). These results suggest the potential utility of 18F-FDG PET in the early prediction of neurological outcomes in PCAS.

How can neurological outcomes be predicted in comatose pediatric patients after out-of-hospital cardiac arrest?

The prognosis of patients who are comatose after resuscitation remains uncertain. The accurate prediction of neurological outcome is important for management decisions and counseling. A neurological examination is an important factor for prognostication, but widely used sedatives alter the neurological examination and delay the response recovery. Additional studies including electroencephalography, somatosensory-evoked potentials, brain imaging, and blood biomarkers are useful for evaluating the extent of brain injury. This review aimed to assess the usefulness of and provide practical prognostic strategy for pediatric postresuscitation patients. The principles of prognostication are that the assessment should be delayed until at least 72 hours after cardiac arrest and the assessment should be multimodal. Furthermore, multiple factors including unmeasured confounders in individual patients should be considered when applying the prognostication strategy.

The influence of neurological examination timing within hours after acute traumatic spinal cord injuries: an observational study.

Cohort study. It is widely accepted that the prediction of long-term neurologic outcome after traumatic spinal cord injury (SCI) can be done more accurately with neurological examinations conducted days to weeks post injury. However, modern clinical trials of neuroprotective interventions often require patients be examined and enrolled within hours. Our objective was to determine whether variability in timing of neurological examinations within 48 h after SCI is associated with differences in observations of follow-up neurologic recovery. Level I trauma hospital. An observational analysis testing for differences in AIS conversion rates and changes in total motor scores by neurological examination timing, controlling for potential confounders with multivariate stepwise regression. We included 85 patients, whose mean times from injury to baseline and follow-up examinations were 11.8 h (SD 9.8) and 208.2 days (SD 75.2), respectively. AIS conversion by 1+ grade was significantly more likely in patients examined at ≤4 h in comparison with later examination (78% versus 47%, RR = 1.66, p = 0.04), even after controlling for timing of surgery, age, and sex (OR 5.0, 95% CI 1.1-10, p = 0.04). We failed to identify any statistically significant associations for total motor score recovery in unadjusted or adjusted analyses. AIS grade conversion was significantly more likely in those examined ≤4 h of injury; the effect of timing on motor scores remains uncertain. Variability in neurological examination timing within hours after acute traumatic SCI may influence observations of long-term neurological recovery, which could introduce bias or lead to errors in interpretation of studies of therapeutic interventions.

3 A High Los Angeles Motor Scale Score is an Effective Tool for Triaging Stroke Patients in the Out-of-Hospital Setting

To evaluate the ability of the Los Angeles Motor Scale (LAMS) score in identifying large vessel occlusions (LVOs) in the field, and correlating the score to hospital interventions for acute stroke. This Institutional Review Board (IRB)-approved prospective study included all patients (n=2464) transported for stroke by our county Emergency Medical Services (EMS) system from January 2016-March 2019 to one of our eight receiving hospitals. Paramedics administered the LAMS prior to hospital arrival. Our EMS system has agreements with our receiving hospitals to provide hospital discharge outcomes on all patients transported to a given facility for stroke, including NIHSS at hospital arrival and discharge, hospital length of stay, and the ultimate disposition of the patient. For the purposes of this study, patients were split into two groups: high LAMS (4-5), or low LAMS (0-3). Statistical analysis was performed using JMP Pro 14 for Windows. The median age was 71.5, with an interquartile range (IQR) of 60-81 and a range of 13-108. Our cohort was 52% female. The median scene time was 15 minutes, with an IQR of 12-19 minutes and a range of 1-74 minutes. The LAMS score breakdown (n=2206) was as follows:LAMS 0: 19%LAMS 1: 14%LAMS 2: 13%LAMS 3: 17%LAMS 4: 16%LAMS 5: 21% For the patients which there was data, 40% received computed tomography (CT) perfusion imaging, 12% received tissue plasminogen activator (tPA), and 14% received mechanical intervention. 10% of strokes were hemorrhagic, 45% were ischemic, and 10% were transient ischemic attacks (TIA). The median National Institute of Health Stroke Scale (NIHSS) at hospital arrival was 6, with an IQR of 2-13 and a range of 0-40. 49% of patients were discharged home, 19% were sent to a skilled nursing facility, 13% were discharged to rehab, and 7% expired. Table 1 summarizes the relative risk of various outcomes associated with a high LAMS score.Table 1Relative risk of outcomes associated with LAMS of 4-5.Relative Risk (95% CI)p-valueMechanical Intervention3.61 (2.67-4.87)<.0001In-hospital death3.15 (2.21-4.52)<.0001CT perfusion imaging2.11 (1.84-2.41)<.0001Receiving tPA2.07 (1.64-2.62)<.0001Ischemic stroke1.45 (1.32-1.60)<.0001Not being discharged home1.36 (1.24-1.49)<.0001 Open table in a new tab The median NIHSS for low LAMS was 4 (IQR 1-8), whereas for high LAMS it was 13 (IQR 7-21). Using Wilcoxon’s rank-sum test, the high LAMS group had a significantly higher NIHSS (p < .0001). The median hospital length of stay for low LAMS was 3 (IQR 1-5), whereas for high LAMS it was 5 (IQR 2-9). Using Wilcoxon’s rank-sum test, the high LAMS group had a significantly longer hospital stay (p < .0001). There was no significant association between LAMS score and age, sex, or EMS Rankin score. The LAMS is a powerful out-of-hospital tool for prediction of intervention and neurological outcomes after acute stroke.

Usefulness of Intracranial Pressure and Mean Arterial Pressure for Predicting Neurological Prognosis in Cardiac Arrest Survivors Who Undergo Target Temperature Management.

We aimed to compare the relationship of mean arterial pressure (MAP) and intracranial pressure (ICP) to predict the neurological prognosis in cardiac arrest (CA) survivors. We retrospectively examined out-of-hospital CA patients treated with targeted temperature management. ICP was measured using cerebrospinal fluid (CSF) pressure, whereas MAP was measured as blood pressure monitored through the radial or femoral artery during CSF pressure measurement. Primary outcome was 6-month neurological outcome. Of 92 enrolled patients, the favorable outcome group comprised 31 (34%) patients. The median and interquartile range of MAP were significantly higher and ICP was significantly lower in patients with favorable neurological outcomes than in those with unfavorable neurological outcomes (94.3 mmHg [80.0-105.3] vs. 82.0 mmHg [65.3-96.3], p = 0.021 and 9.4 mmHg [10.8-8.7] vs. 18.8 mmHg [20.0-15.7], p < 0.001, respectively). ICP showed the higher area under the receiver operating characteristic curve (area under curve [AUC] = 0.953, 95% confidence interval [CI] = 0.888-0.986) for neurological outcome prediction. MAP showed the lower AUC (0.648, 95% CI = 0.541-0.744). Higher accurate prognosis was predicted by ICP than MAP, and the prognostic performance was good. Prospective multicenter studies are required to confirm these results.

Magnetic Resonance Imaging Evidence of Therapeutic Efficacy of Timing of Decompression in American Spinal Injury Association Impairment Scale Grades A to C Cervical Spinal Cord Injury Patients

Abstract INTRODUCTION In traumatic cervical spinal cord injury (SCI), the therapeutic effect of surgery and its timing as neuroprotective measures remain uncertain. Additionally, the relationship between timing of decompression, extent of decompression, imaging biomarkers evidence of injury severity, and outcome are incompletely understood. METHODS We investigated the effect of timing of decompression and long-term neurological outcome in patients with postoperatively confirmed decompression using computed tomography (CT) and magnetic resonance imaging (MRI) studies. A total of 6 mo after cervical SCI, American Spinal Injury Association Impairment Scale (AIS) grade conversion was determined in 72 AIS grades A, B, and C patients whose postoperative CT and MRI confirmed spinal cord decompression. A total of 32 patients underwent decompressive surgery less than 12 hr from injury, 25 within 12 to 24 hr, and 15 more than 24 hr after trauma. RESULTS Age, gender, injury mechanism, intramedullary lesion length (IMLL) on MRI, admission American Spinal Injury Association (ASIA) motor score, and surgical technique were not statistically different in-between groups. Motor complete patients (P = .009) and those with fracture dislocations (P = .01) tended to be operated earlier. One or more grade improvement was 55.6% in AIS grade A, 60.9% in AIS grade B, and 86.4% in AIS grade C patients. Admission AIS motor score (P = .0004) and preoperative IMLL (P = 0001) were the strongest predictors of neurological outcome. AIS grade improvement was 65.6% in patients undergoing decompressive surgery within 12 hr after trauma, 60% in patients undergoing surgery within 12 to 24 hr, and 80% when decompression was performed more than 24 hr after injury (P = .424). Multiple regression analysis of all significant and marginally significant variables revealed that the only significant variable predictive of AIS grade conversion to a better grade was IMLL (odds ratio 133.51, CI 11.68-1525.71, P &lt; .0001). CONCLUSION In patients with postoperative CT and MRI confirmation of decompression following traumatic cervical SCI, preoperative IMLL and not the timing of surgery appears to determine long-term neurological outcome.

Artificial Intelligence Analysis of Initial Scan Evolution of Traumatic Brain Injured Patient to Predict Neurological Outcome

Artificial Intelligence Analysis of Initial Scan Evolution of Traumatic Brain Injured Patient to Predict Neurological Outcome

Prognostic value of post-acute EEG in severe disorders of consciousness, using American Clinical Neurophysiology Society terminology

To evaluate whether electroencephalographic (EEG) features recorded during the post-acute stage in patients with severe disorders of consciousness (DoC) after acute brain injury (ABI), contribute to neurological outcome prediction of these patients at discharge from the intensive rehabilitation unit (IRU). We retrospectively evaluated all patients consecutively admitted to the IRU from August 2012 to December 2016. Inclusion criteria were: 1) age >18years, 2) patients with unresponsive wakefulness syndrome (UWS) or in a minimally conscious state (MCS), and 3) EEG and a coma recovery scale-revised (CRS-R) score available within the first week after admission. Clinical evaluation was performed using the Italian version of the CRS-R score. EEGs were classified according to American Clinical Neurophysiology Society (ACNS) terminology. Clinical state at final discharge was evaluated using the CRS-R score. In total, 102 patients were included in the analysis. After a mean of five months of IRU stay, among the 61 UWS subjects, 19 transitioned to MCS and 11 recovered to exit-MCS (E-MCS); twenty-three of the 41 subjects in MCS progressed to E-MCS. Using logistic regression, consciousness level (UWS/MCS-OR=13.4), CRS-R score at admission (OR=1.33) and use of activating drugs (OR=4.7) were significant predictors of clinical improvement. Multivariable analysis showed that specific EEG patterns were independent predictors of improved consciousness at discharge in UWS patients. EEG performed within the first week after IRU admission, classified according to ACNS-terminology in patients with UWS at admission, can provide useful prognostic contribution.