Prediction Of Neurological Outcome Research Articles

Abstract 351: Predictors of Neurological Outcome After Out-of-Hospital Cardiac Arrest With Ventricular Fibrillation Witnessed by Emergency Medical Service P.ersonnel., JCS-ReSS Study

Background: Effective advanced life support is one of the important link in the chain of survival. In Japan, the emergency medical service (EMS) personnel can perform defibrillation, advanced airway management, intravenous access and administration of epinephrine as an advanced life support intervention for the treatment of out-of-hospital cardiac arrest (OHCA). However, whether these interventions performed by EMS improves neurological outcomes remains unclear. Objective: To evaluate predictors of favorable neurological outcome in patients suffering OHCA with ventricular fibrillation (VF) witnessed by an EMS personnel. Methods: The Fire and Disaster Management Agency (FDMA) of Japan developed a nationwide database of a prospective population-based cohort using an Utstein-style template for OHCA patients since January 2005. To evaluate data after the publication of Guideline2010, data from January 2011 to December 2015 of this database was used for the current analysis. A multivariate logistic-regression analysis was performed to assess factors associated with favorable neurological outcome (defined as Cerebral Performance Category 1 or 2) 1 month after cardiac arrest. Results: Of the 629,471 patients documented for the study period, 2,301 adult patients with an OHCA of cardiac origin and VF for the initial rhythm witnessed by an EMS personnel were included in the present analysis. The overall mortality was 49.6%. Rate of return of spontaneous circulation and favorable neurological outcome were 53.4% and 44.8%, respectively. High age (OR0.387, 95%CI0.316-0.472, p<0.001), delayed defibrillation (OR0.598, 95%CI0.493-0.723, p<0.001), advanced airway management (OR0.305, 95%CI0.223-0.413, p<0.001), administration of epinephrine (OR0.356, 95%CI0.213-0.585, p<0.001) and multiple attempts of defibrillation (OR0.484, 95%CI0.402-0.582, p<0.001) were negatively associated with favorable neurological outcome. Conclusion: In patients with VF witnessed by EMS personnel, resuscitation efforts should simply focus on early defibrillation and CPR without advanced interventions.

The revised Cerebral Recovery Index improves predictions of neurological outcome after cardiac arrest

ObjectiveAnalysis of the electroencephalogram (EEG) background pattern helps predicting neurological outcome of comatose patients after cardiac arrest (CA). Visual analysis may not extract all discriminative information. We present predictive values of the revised Cerebral Recovery Index (rCRI), based on continuous extraction and combination of a large set of evolving quantitative EEG (qEEG) features and machine learning techniques. MethodsWe included 551 subsequent patients from a prospective cohort study on continuous EEG after CA in two hospitals. Outcome at six months was classified as good (Cerebral Performance Category (CPC) 1-2) or poor (CPC 3-5). Forty-four qEEG features (from time, frequency and entropy domain) were selected by the least absolute shrinkage and selection operator (LASSO) method and used in a Random Forests classification system. We trained and evaluated the system with 10-fold cross validation. For poor outcome prediction, the sensitivity at 100% specificity (Se100) and the area under the receiver operator curve (AUC) were used as performance of the prediction model. For good outcome, we used the sensitivity at 95% specificity (Se95). ResultsTwo hundred fifty-six (47%) patients had a good outcome. The rCRI predicted poor outcome with AUC = 0.94 (95% CI: 0.83–0.91), Se100 = 0.66 (0.65–0.78), and AUC = 0.88 (0.78–0.93), Se100 = 0.60 (0.51–0.75) at 12 and 24 h after CA, respectively. The rCRI predicted good outcome with Se95 = 0.72 (0.61–0.85) and 0.40 (0.30–0.51) at 12 and 24 h after CA, respectively. ConclusionsResults obtained in this study suggest that with machine learning algorithms and large set of qEEG features, it is possible to efficiently monitor patient outcome after CA. We also demonstrate the importance of selection of optimal performance metric to train a classifier model for outcome prediction. SignificanceThe rCRI is a sensitive, reliable predictor of neurological outcome of comatose patients after CA.

Prediction of neurological outcomes following the return of spontaneous circulation in patients with out-of-hospital cardiac arrest: Retrospective fast-and-frugal tree analysis

AimAlthough various quantitative methods have been developed for predicting neurological prognosis in patients with out-of-hospital cardiac arrest (OHCA), they are too complex for use in clinical practice. We aimed to develop a simple decision rule for predicting neurological outcomes following the return of spontaneous circulation (ROSC) in patients with OHCA using fast-and-frugal tree (FFT) analysis. MethodsWe performed a retrospective analysis of prospectively collected data archived in a multi-centre registry. Good neurological outcomes were defined as cerebral performance category (CPC) values of 1 or 2 at 28-day. Variables used for FFT analysis included age, sex, witnessed cardiac arrest, bystander cardiopulmonary resuscitation, initial shockable rhythm, prehospital defibrillation, prehospital ROSC, no flow time, low flow time, cause of arrest (cardiac or non-cardiac), pupillary light reflex, and Glasgow Coma Scale score after ROSC. ResultsAmong the 456 patients enrolled, 86 (18.9%) experienced good neurological outcomes. Prehospital ROSC (true = good), prompt or sluggish light reflex response after ROSC (true = good), and presumed cardiac cause (true = good, false = poor) were selected as nodes for the decision tree. Sensitivity, specificity, positive predictive value, and negative predictive value of the decision tree for predicting good neurological outcomes were 100% (42/42), 64.0% (119/186), 38.5% (42/109), and 100% (119/119) in the training set and 95.5% (42/44), 57.6% (106/184), 35.0% (42/120), and 98.1% (106/108) in the test set, respectively. ConclusionA simple decision rule developed via FFT analysis can aid clinicians in predicting neurological outcomes following ROSC in patients with OHCA.

Blood Lactate or Lactate Clearance: Which Is Robust to Predict the Neurological Outcomes after Cardiac Arrest? A Systematic Review and Meta-Analysis.

Aims Lactate and lactate clearance were supposed to be associated with cardiac arrest outcomes, but studies obtained different results. Thus, we conducted this meta-analysis to investigate the association between lactate or lactate clearance and neurological outcomes and their usefulness for prediction of neurological outcomes. Methods We conducted a systematic search in PubMed, Web of science, EMBASE, Medline, and Google Scholar until May 1, 2018, for relevant studies. Studies reporting lactate, lactate clearance on admission, or other time points after admission associated with neurological outcomes were included in our analysis. Pooled effect date was shown as weighed mean difference (WMD) and 95% confidence interval (CI). To measure the usefulness of lactate on admission to predict neurological outcomes, we also pooled the data of diagnostic test. Results 23 studies involving 6720 cardiac arrest (CA) patients were included. Results from our analysis indicated that patients with good neurological outcomes tended to have a lower lactate level on admission (WMD: -2.66 mmol/L, 95%CI: -3.39 to -1.93) and 12h, 24h, and 48h after admission (P<0.001). Furthermore, the pooled AUC for lactate level on admission to predict neurological outcomes was 0.77 (95%CI: 0.73-0.80). However, a significant association between lactate clearance and neurological outcomes was only found in 24h but not 12h lactate clearance rate. Conclusions Lactate levels on admission and all time points up to 48h were associated with neurological outcomes after CA, whereas the association between lactate clearance and neurological outcomes was not so stable. Lactate was a more robust surrogate marker than lactate clearance to predict neurological outcomes after CA.

Cushing response-based warning system for intensive care of brain-injured patients

ObjectiveCushing response (CR) is categorized. Wavelet transform (WT) and decision tree (DT) are utilized to analyze physiological signals from neurocritical patients. A warning model is built for recognition of CR, real-time evaluation of intracranial condition and prediction of neurological outcome. MethodsPhysiological signals of neurocritical patients are preprocessed by WT and compressed by linear regression. An algorithm labels each segment as pathological, physiological, negative or uncertain CR. The DT identifies CR. Continuous data input to the established DT predicts condition at that moment and following outcome. ResultsFrom 33 neurocritical patients, 422,524 sets of physiological signals were collected. The cross-validation scores of DT ranged from 0.562 to 0.579 with averaged accuracy rate 60.6% (3.5–98.1%). The model correctly predicted the outcome of the training group, 87.9% in accuracy. The ratios of pathological CR were 9.3 ± 16.6%, 74.2 ± 29.7% and 99.7 ± 0.3% in patients of good, coma and death groups, respectively. The prediction accuracy for a test set of 103 patients reached 81.6%. ConclusionsCushing response categorization helps in identifying critical conditions and predicting outcome. SignificanceA novel concept of four categories of Cushing response is proposed to represent broader ranges of intracranial change.

Variation in Candidate Traumatic Brain Injury Biomarker Genes Are Associated with Gross Neurological Outcomes after Severe Traumatic Brain Injury.

Diagnostic and prognostic biomarkers of traumatic brain injury (TBI) are actively being pursued; potential candidates include glial fibrillary acid protein (GFAP), S100 calcium-binding protein B (S100B), and ubiquitin C-terminal hydrolase L1 (UCHL1), two of which the United States Food and Drug Administration (FDA) recently approved for marketing of blood tests for adult concussion. The relationship between biomarker-encoding genes and TBI outcomes remains unknown. This pilot study explores variation in 18 single nucleotide polymorphisms (SNPs) in biomarker-encoding genes as predictors of neurological outcome in a population of adults with severe TBI. Participants (n = 305) were assessed using the Glasgow Outcome Scale (GOS) at 3, 6, 12, and 24 months post-injury. Multivariate logistical regression was used to calculate the odds ratio (OR) and determine the odds of having a lower score on the GOS ( = 1-2 vs. 3-5) based on variant allele presence, while controlling for confounders. Possession of the variant allele of one S100B SNP (rs1051169) was associated with higher scores on the GOS at 3 months (OR = 0.39; p = 0.04), 6 months (OR = 0.34; p = 0.02), 12 months (OR = 0.32; p = 0.02), and 24 months (OR = 0.30; p = 0.02) post-severe TBI. The relationship among these polymorphisms, protein levels, and biomarker utility, merits examination. These findings represent a novel contribution to the evidence that can inform future studies aimed at enhancing interpretation of biomarker data, identifying novel biomarkers, and ultimately harnessing this information to improve clinical outcomes and personalize care.

Initial blood pH as an independent predictor of neurological outcome in patients with out-of-hospital cardiac arrest

Initial blood pH as an independent predictor of neurological outcome in patients with out-of-hospital cardiac arrest

MRI for early prediction of outcome in preterm infants: Which items?

Objectives Early prediction of neurologic outcome of preterm infants is challenging. MRI provides interesting insights. Usual MRI interpretation looking for lesions (hemorrhage, cystic lesions, infarction, or “qualitative abnormalities”) has good predictive value for severe motor disabilities. Conversely those standard items are poor predictors of later, cognitive impairments. For this purpose, measuring volume of brain structures and cerebral growth is promising. In a prospective cohort study, we assessed global and regional cerebral growth, compared to outcome. Methods Infants born before 30 gestation weeks underwent serial MRI (between 25 and 28 weeks of gestation, then every three weeks until term). Cerebrum, cerebellum, brainstem, fluid spaces were estimated through twenty-five 2D measurements. Outcome was assessed with Bayley scale at two years of age. Results Hundred and eight preterm infants were included and 266 MRI performed. Main qualitative abnormalities were low-grade IVH (22%), severe IVH (6%), severe white matter injuries (21%), Cerebellar injuries (19%). Brain/Bone biparietal diameter, which has previously been strongly correlated with global cerebral volume, was significantly lower, as cerebellum and brainstem measurements. Impairment of regional brain growth is correlated with 2 years outcome. Conclusion We need to further search for correlation with later outcome at five and eight years. Brain MRI is a promising tool for early prognosis, but standard interpretation might include volume and cerebral growth assessments.

Serum lactate as a predictor of neurologic outcome in ED patients with acute carbon monoxide poisoning

BackgroundThis study was conducted to assess and clarify the predictive risk factor of neurologic outcome in patients with acute carbon monoxide (CO) poisoning. MethodsA total of 453 patients with acute CO poisoning were admitted to the emergency department of Samsung Changwon Hospital from January 2010 to June 2017. Patients with acute CO poisoning who were followed for >6 months were studied. Initial Glasgow Coma Score (GCS), serum neuron-specific enolase (NSE), and lactate were measured after emergency department arrival. Patients were divided into two groups (good vs poor neurologic outcome). ResultsA total of 432 patients (median age: 55 years, range: 17–91 years) were enrolled. There was a statistical difference between the good neurologic outcome group and the poor neurologic outcome group in terms of Exposure time, WBC, aspartate aminotransferase (AST), CK-MB, Troponin-I, creatinine kinase, NSE, lactate, CO-Hb, and GCS. NSE, lactate, and GCS were the early predictors of development of poor neurologic outcome. The areas under the curve in the ROC curve analysis for the GCS, NSE, and lactate were 0.842, 0.795, and 0.894, respectively. ConclusionInitial serum lactate level may correlate with the patient neurologic outcomes and prove to be a useful prognostic factor. Also NSE, and GCS might be a useful additional parameters that could predict the neurologic outcome on acute CO poisoned patients.

The impact of diastolic blood pressure values on the neurological outcome of cardiac arrest patients

AimWhich haemodynamic variable is the best predictor of neurological outcome remains unclear. We investigated the association of several haemodynamic variables with neurological outcome in CA patients. MethodsRetrospective analysis of adult comatose survivors of CA admitted to the intensive care unit (ICU) of a University Hospital. Exclusion criteria were early death due to withdrawal of care, missing haemodynamic data and use of intra-aortic balloon pump or extracorporeal membrane oxygenation. We retrieved CA characteristics; lactate concentration and cardiovascular sequential organ failure assessment (cSOFA) score on admission; systolic (SAP), diastolic (DAP), mean arterial pressure (MAP), and the use of vasopressors and inotropic agents during the first 6 h of ICU stay. Unfavourable neurological outcome (UO) was defined as a 3-month cerebral performance category score of 3–5. ResultsAmong the 170 patients (median age 63 years, 67% male, 60% out-of-hospital CA), 106 (63%) had UO. Admission lactate was higher in patients with UO than in those with favourable neurological outcome (4.0[2.4–7.3] vs. 2.5[1.4–6.0] mEq/L; p = 0.003) as was the cSOFA (3 [1–4] vs. 2[0–3]; p = 0.007). The lowest DAP during the first 6 h after ICU admission was significantly lower in patients with unfavourable neurological outcome, notably in patients with high cSOFA scores. In multivariable analysis, high adrenaline doses and the lowest value of DAP during the first 6 h after ICU admission was significantly associated with unfavourable neurological outcome. ConclusionsIn CA patients admitted to the ICU, low DAP during the first 6 h is an independent predictor of unfavourable neurological outcome at 3 months.

Molecular Biomarkers for Prediction of Neurological Outcome after Sudden Circulatory Arrest (Review)

The purpose of this review of the 81 publications is to discuss the current national and international data on the prediction of neurological outcomes after sudden circulatory arrest (SCA) using molecular biomarkers. The review discusses the current state of the problem of neurological outcomes after a sudden circulatory arrest, the principal therapeutic measures to improve these outcomes and currently available clinical, laboratory, and instrumental methods of diagnosis and prediction of neurological outcomes after a sudden circulatory arrest.

Heat Production After Cardiac Arrest: Predictor of Neurologic Outcome?*

Heat Production After Cardiac Arrest: Predictor of Neurologic Outcome?*

Imaging-based outcome prediction in patients with intracerebral hemorrhage.

Besides the established spot sign in computed tomography angiography (CTA), recently investigated imaging predictors of hematoma growth in noncontrast computed tomography (NCCT) suggest great potential for outcome prediction in patients with intracerebral hemorrhage (ICH). Secondary hematoma growth is an appealing target for therapeutic interventions because in contrast to other determined factors, it is potentially modifiable. Even more initial therapy studies failed to demonstrate clear therapeutic benefits, there is a need for an effective patient selection using imaging markers to identify patients at risk for poor outcome and thereby tailor individual treatments for every patient. Hence, this review gives an overview about the current literature on NCCT imaging markers for neurological outcome prediction and aims to clarify the association with the established spot sign. Moreover, it demonstrates the clinical impact of these parameters and gives a roadmap for future imaging research in patients with intracerebral hemorrhage.

Perinatal prediction model for severe intraventricular hemorrhage and the effect of early postnatal acidosis.

Severe acidosis is one of the strongest predictors of neurologic outcomes in full-term infants with suspected hypoxic-ischemic encephalopathy. However, the relative importance of acidosis as a predictor of outcomes in preterm infants is much less clear. The goals of the present study were to examine the association between postnatal acidosis and severe intraventricular hemorrhage (IVH) and to establish a new score model including acid-base status after birth for predicting the risk of this morbidity. The study sample was very low birth weight (VLBW) infants in the Korean Neonatal Network (KNN) cohort registry, collected prospectively from January 2013 to December 2014. Infants with blood pH and base deficit (BD) values collected within the first hour after birth, and documentation of severe IVH, were included. Multivariate stepwise logistic regression analysis was used to determine the contribution of postnatal acidosis to predicting severe IVH in VLBW infants. In addition, a prediction model was developed. Data from 2518 VLBW infants were analyzed. Infants with postnatal acidosis had a higher incidence of severe IVH. The clinical model plus blood BD values improved predictive performance, compared with models using only perinatal data or blood pH. A prediction model for severe IVH was developed using the KNN registry of VLBW infants. Immediate postnatal acidosis, defined based on blood BD, was associated with a higher-risk-adjusted incidence of severe IVH.

Natural History, Predictors of Outcome, and Effects of Treatment in Thoracic Spinal Cord Injury: A Multi-Center Cohort Study from the North American Clinical Trials Network

The course, treatment response, and recovery potential after acute traumatic spinal cord injury (SCI) have been shown to differ depending on the neurological level of injury. There are limited data focused on thoracic-level injuries, however. A cohort of 86 patients from the prospectively maintained North American Clinical Trials Network SCI registry were identified and studied to characterize the patterns of neurological recovery and to determine rates of acute hospital death and pulmonary complications. Regression analyses were used to examine the relationship between timing of surgery and administration of methylprednisolone on neurologic and clinical outcomes. Neurological conversion (≥1 American Spinal Injury Association Impairment Scale [AIS] grade improvement) was poorest for AIS grade A patients; 14.3% converted at last available follow-up (mean eight months). While rates of conversion were more optimistic for AIS-B patients (54.5%) and AIS C injuries (77.8%) at the same time point, none of the AIS grade D patients converted to AIS E. At last available follow-up (mean eight months), the magnitudes of lower motor extremity score (LEMS) change were highest for AIS C injuries (21.9 points), then AIS B (17.7 points), AIS D (16.4 points), and finally AIS A (2.5 points) (p < 0.05). Early surgical intervention (<24 h post-injury) was independently associated with an additional seven points in motor recovery and a 60% decreased incidence of pulmonary events (p < 0.05). Methylprednisolone administration was not an independent predictor of neurological outcome or pulmonary complications. Evaluation of this cohort obtained from a modern multi-center SCI registry provides an update on the natural history, acute death, and incidence of pulmonary complications after traumatic thoracic SCI. Although small sample size limited the extent of analyses possible, early surgical treatment was associated with significantly larger motor recovery and lower rates of pulmonary complications.

Encephaloduroarteriosynangiosis for pediatric moyamoya disease: long-term follow-up of 100 cases at a single center.

OBJECTIVE The object of this study was to summarize the long-term effect of encephaloduroarteriosynangiosis (EDAS) for the treatment of pediatric moyamoya disease (MMD) and to investigate factors influencing the clinical outcomes of EDAS. METHODS Clinical features, angiographic findings, and clinical outcomes were analyzed among MMD patients younger than 18 years who had been treated with EDAS between 2002 and 2007 at the authors' institution. The Kaplan-Meier method was used to estimate stroke risk after EDAS. Predictors of neurological outcome were assessed. RESULTS One hundred fifteen patients were identified. The mean age at symptom onset was 7.3 ± 4.0 years. The incidence of familial MMD was 11.3%. The female/male ratio was 1:1.16. A total of 232 EDAS procedures were performed, and the incidence of postoperative complications was 3%. Postoperative digital subtraction angiography was performed in 54% of the patients, and about 80% of the hemispheres showed good or excellent results. Neovascularization showed significant correlations with delay time (from symptom onset to first operation), Suzuki stage, and preoperative stroke (all p < 0.05). Clinical follow-up was available in 100 patients with a mean follow-up of 124.4 ± 10.5 months. Ten-year cumulative survival was 96.5% after surgery, and the risk of stroke was 0.33%/person-year. An independent life with no significant disability was reported by 92% of the patients. A good outcome correlated with a low Suzuki stage (p = 0.001). Older children and those without preoperative stroke had better clinical outcomes (p < 0.05). CONCLUSIONS On the basis of long-term follow-up data, the authors concluded that EDAS is a safe and effective treatment for pediatric MMD, can reduce the risk of subsequent neurological events, and can improve quality of life. The risk of ischemia-related complications was higher in younger patients, and older children showed better outcomes. Compensation was greater with more prominent cerebral ischemia. The long-term clinical outcome largely depended on the presence and extent of preoperative stroke.

F108. The prognostic value of median nerve SSEP after cardiac arrest: Evaluation of severity of hypoxic-ischemic encephalopathy by brain autopsies

Introduction The severity of hypoxic-ischemic encephalopathy (HIE) strongly determines outcome after cardiac arrest (CA). Bilaterally absent cortical median nerve somatosensory evoked potentials (SSEPs) have been shown to accurately predict poor prognosis. However, self-fulfilling prophecy due to withdrawal of life-sustaining therapy is an important bias in prognostication studies on CA patients. Brain autopsies in patients who died after CA provide a unique opportunity to verify prognostic parameters such as SSEPs. Methods We retrospectively identified CA patients from university hospitals in Berlin, Germany, Lund, Sweden and Arhus, Denmark, who died after initially successful resuscitation and for whom SSEPs for neuro-prognostication and brain autopsy were available. We blindly determined presence/absence and, if applicable, cortical peak-to-peak SSEP amplitudes from original recordings. Severity of HIE was quantified histopathologically according to the selective eosinophilic neuronal death (SEND) score. Results We identified 58 CA autopsy patients who had been investigated with SSEP. All 21 patients with bilaterally absent SSEP and all 5 with cortical SSEP amplitudes below 0.5 μV had severe HIE (SEND 2–4 in cortical regions). The highest cortical SSEP amplitude in a patient with severe HIE was 2.7 μV, all 11 patients with higher amplitudes had no/moderate HIE (SEND 0–1 in cortical regions). Conclusion We did not find evidence for a self-fulfilling prophecy in the prediction of poor neurological outcome by SSEP after cardiac arrest. Bilaterally absent cortical SSEP and very low SSEP amplitudes indicated histopathologically severe HIE whereas cortical SSEP amplitudes above 2.7 μV indicated absence of severe HIE.

T114. Predicting coma outcome using resting-state fMRI and machine learning

Introduction Early prediction of neurological outcome of post-anoxic comatose patients after cardiac arrest(CA) is challenging. Prognosis of comatose patient relies on multimodal testing: clinical examination, electrophysiological testing and structural neuroimaging (mainly diffusion MRI DWI). This multimodal prognostication is accurate for predicting poor outcome(i.e.death) but not sensitive for identifying patients with good outcome (i.e. consciousness recovery). Resting state functional MRI (rs-fMRI) is a powerful tool for mapping functional connectivity, especially in patients with low collaboration. Several studies showed that rs-fMRI can differentiate states of consciousness in chronically brain damaged patients. A recent study also showed that fMRI can detect early signs of consciousness in patient with acute traumatic brain injury. However, rs-fMRI has not been systematically assessed for the early prognositcation of post-anoxic comatose patient. Methods We assessed whole brain functional connectivity (FC) of 17 post-anoxic comatose patients early after CA using rs-fMRI. Nine patients recovered consciousness(good outcome) while eight died(poor outcome). We estimated FC for each patient following a standard procedure described by Leonardi and Richiardi et al. We statistically compared whole brain FC between good and poor outcome group, to assess which brain connections differed between them. Then, we trained a machine learning classifier(a Support Vector Machine classifier, SVM) using a Leave-One-Out Cross-Validation method, to automatically predict coma outcome (good/poor) based on whole-brain FC of comatose patients. Finally, we compared this outcome-prognostication based on fMRI to those using standard structural DWI. Results Good and poor coma outcome groups were similar in terms of demographics, except for time to ROSC. Good outcome group showed significant increase in whole-brain FC between most cortical brain regions, with the strongest changes occuring within and between occipital and parietal, temporal and frontal regions. Using whole-brain FC and a SVM classifier to predict coma outcome yielded to an overall prediction accuracy of 94.4% (AUC 0.94). Interestingly, automatic outcome prognostication using functional neuroimaging achieved better results that state-of the-art structural neuroimaging methods like DWI (accuracy 70.6%). Conclusion We used rs-fMRI to predict coma outcome in a cohort of post-anoxic comatose patients early after CA. We deliberately chose to include only patients with indeterminate prognosis after standard multimodal testing, in order to assess the contribution of rs-fMRI in the early prognostication of coma outcome. We found that automatic prediction based on fMRI yielded much better results than current diffusion neuroimaging methods, notably for identifying patients who recovered consciousness.

Combining early post-resuscitation EEG and HRV features improves the prognostic performance in cardiac arrest model of rats

ObjectiveEarly and reliable prediction of neurological outcome remains a challenge for comatose survivors of cardiac arrest (CA). The purpose of this study was to evaluate the predictive ability of EEG, heart rate variability (HRV) features and the combination of them for outcome prognostication in CA model of rats. MethodsForty-eight male Sprague-Dawley rats were randomized into 6 groups (n=8 each) with different cause and duration of untreated arrest. Cardiopulmonary resuscitation was initiated after 5, 6 and 7min of ventricular fibrillation or 4, 6 and 8min of asphyxia. EEG and ECG were continuously recorded for 4h under normothermia after resuscitation. The relationships between features of early post-resuscitation EEG, HRV and 96-hour outcome were investigated. Prognostic performances were evaluated using the area under receiver operating characteristic curve (AUC). ResultsAll of the animals were successfully resuscitated and 27 of them survived to 96h. Weighted-permutation entropy (WPE) and normalized high frequency (nHF) outperformed other EEG and HRV features for the prediction of survival. The AUC of WPE was markedly higher than that of nHF (0.892 vs. 0.759, p<0.001). The AUC was 0.954 when WPE and nHF were combined using a logistic regression model, which was significantly higher than the individual EEG (p=0.018) and HRV (p<0.001) features. ConclusionsEarlier post-resuscitation HRV provided prognostic information complementary to quantitative EEG in the CA model of rats. The combination of EEG and HRV features leads to improving performance of outcome prognostication compared to either EEG or HRV based features alone.

Value of neurophysiologic monitoring in confirming indirect decompression of severe pediatric non-traumatic C1–C2 subluxation. A case report

Abstract Spinal cord compression from severe C1–C2 subluxation is a complex and challenging neurosurgical problem. A combination of surgical approaches may be required to decompress the spinal cord, including anterior transoral odontoidectomy, posterior cervical laminectomy, or indirect decompression by subluxation reduction. After decompression, an instrumented posterior fusion is then required to stabilize the spine. We report a case of a 13-year-old-girl who presented with spastic quadriparesis secondary to severe atlantoaxial subluxation, where intraoperative neurophysiologic monitoring (IOM) guided surgical decision making. The patient had congenital osseous abnormalities, including incomplete segmentation of C2 on C3, predisposing her to atlantoaxial dislocation. She underwent open surgical reduction of the C1–C2 subluxation with multi-modal intraoperative neurophysiologic guidance. Translaminar C2 screws and C1 lateral mass screws were placed bilaterally. Using a previously described distraction technique, we performed ventral translation of C2 relative to C1, thereby reducing the subluxation. Intraoperative radiographic images and neurophysiologic monitoring revealed significant improvements, confirming that adequate indirect decompression had been achieved. After subluxation reduction with intraoperative monitoring (IOM) improvements, we decided to proceed with a C1–C2 posterior fusion and avoid a cervical laminectomy and more extensive occipital cervical fusion procedure. After one year, the girl made a complete neurologic recovery and remains symptom-free 3 years post-surgery. Fusion to the occiput would have potentially caused greater morbidity in this patient. The neurophysiologic monitoring confirmed indirect decompression and served as a critical tool for the prediction of favorable neurologic outcome.