Post-anoxic Comatose Patients Research Articles

Predicting neurological outcome after cardiac arrest by combining computational parameters extracted from standard and deviant responses from auditory evoked potentials.

Despite multimodal assessment (clinical examination, biology, brain MRI, electroencephalography, somatosensory evoked potentials, mismatch negativity at auditory evoked potentials), coma prognostic evaluation remains challenging. We present here a method to predict the return to consciousness and good neurological outcome based on classification of auditory evoked potentials obtained during an oddball paradigm. Data from event-related potentials (ERPs) were recorded noninvasively using four surface electroencephalography (EEG) electrodes in a cohort of 29 post-cardiac arrest comatose patients (between day 3 and day 6 following admission). We extracted retrospectively several EEG features (standard deviation and similarity for standard auditory stimulations and number of extrema and oscillations for deviant auditory stimulations) from the time responses in a window of few hundreds of milliseconds. The responses to the standard and the deviant auditory stimulations were thus considered independently. By combining these features, based on machine learning, we built a two-dimensional map to evaluate possible group clustering. Analysis in two-dimensions of the present data revealed two separated clusters of patients with good versus bad neurological outcome. When favoring the highest specificity of our mathematical algorithms (0.91), we found a sensitivity of 0.83 and an accuracy of 0.90, maintained when calculation was performed using data from only one central electrode. Using Gaussian, K-neighborhood and SVM classifiers, we could predict the neurological outcome of post-anoxic comatose patients, the validity of the method being tested by a cross-validation procedure. Moreover, the same results were obtained with one single electrode (Cz). statistics of standard and deviant responses considered separately provide complementary and confirmatory predictions of the outcome of anoxic comatose patients, better assessed when combining these features on a two-dimensional statistical map. The benefit of this method compared to classical EEG and ERP predictors should be tested in a large prospective cohort. If validated, this method could provide an alternative tool to intensivists, to better evaluate neurological outcome and improve patient management, without neurophysiologist assistance.

Assessment of a standardized EEG reactivity protocol after cardiac arrest

ObjectiveReactivity assessment during EEG might provide important prognostic information in post-anoxic coma. It is still unclear how best to perform reactivity testing and how it might be affected by hypothermia. Our primary aim was to determine and compare the effectiveness, inter-rater reliability and prognostic value of different types of stimulus for EEG reactivity testing, using a standardized stimulation protocol and standardized definitions. Our secondary aims were to assess the effect of hypothermia on these measures, and to determine the prognostic value of a simplified sequence with the three most efficient stimuli. MethodsProspective single-center cohort of post-anoxic comatose patients admitted to the intensive care unit of an academic medical center between January 1, 2016 and December 31, 2018 and receiving continuous EEG monitoring (CEEG). Reactivity was assessed using standardized definitions and standardized sequence of stimuli: auditory (mild noise and loud noise), tactile (shaking), nociceptive (nostril tickling, trapezius muscle squeezing, endotracheal tube suctioning), and visual (passive eye opening). Gwet’s AC1 and percent agreement (PA) were used to measure inter-rater agreement (IRA). Ability to predict favorable neurological outcome (defined as a Cerebral Performance Category of 1 to 2: no disability to moderate disability) was measured with sensitivity (Se), specificity (Sp), accuracy, and odds ratio [OR]. These were calculated for each stimulus type and at the level of the entire sequence comprising all the stimuli. ResultsOne-hundred and fifteen patients were included and 242 EEG epochs were analyzed. Loud noise, shaking and trapezius muscle squeezing most frequently elicited EEG reactivity (42%, 38% and 38%, respectively) but were all inferior to the entire sequence, which elicited reactivity in 58% cases. The IRA for reactivity to individual stimuli varied from moderate to good (AC1:58–69%; PA:56–68%) and was the highest for loud noise (AC1:69%; PA:68%), trapezius muscle squeezing (AC1:67%; PA:65%) and passive eye opening (AC1:68%; PA:64%). Mild (odds ratio [OR]:11.0; Se:70% and Sp:86%) and loud noises (OR:27.0; Se:73% and Sp:75%), and trapezius muscle squeezing (OR:15.3; Se:76% and Sp:83%) during hypothermia had the best predictive value for favorable neurological outcome, although each was inferior to the whole sequence (OR:60.2; Se:91% and Sp:73%). A simplified sequence of loud noise, shaking and trapezius muscle squeezing had the same performance for predicting neurological outcome as the entire sequence. Hypothermia did not significantly affect the effectiveness of stimulation, but IRA was slightly better during hypothermia, for all stimuli. Similarly, the predictive value was higher during hypothermia than during normothermia. ConclusionsDespite a standardized stimulation protocol and standardized definitions, the IRA of EEG reactivity testing in post-anoxic comatose patients was only good at best (AC1 < 70%), and its predictive value for neurological outcome remained imperfect, in particular with Sp values < 90%. While no single stimulus appeared superior to others, a full sequence using all stimuli or a simplified sequence comprising loud noise, shaking and trapezius muscle squeezing had the best combination of IRA and predictive value. SignificanceThis study stresses the necessity to use multiple stimulus types to improve the predictive value of reactivity testing in post-anoxic coma and confirms that it is not affected by hypothermia.

Risks According to the Timing and Frequency of Hypotension Episodes in Postanoxic Comatose Patients.

The aim of this study was to assess the risk of unfavorable outcomes according to the timing of hypotension episodes in cardiac arrest patients. This prospectively conducted multicenter observational study included 1373 out-of-hospital cardiac arrest patients treated with 33 °C targeted temperature management (TTM). Unfavorable neurological outcome and the incidence of complications were analyzed according to the timing of hypotension. Compared with hypotension before TTM initiation (adjusted hazard ratio (aHR) 1.51), hypotension within 6 h after TTM initiation was associated with an increased risk of unfavorable neurologic outcome (aHR 1.693), and after 24 h of TTM, was connected with decreased risk (aHR 1.277). The risk of unfavorable neurological outcome was gradually reduced over time after TTM initiation. Hypotension, persisting both before and during TTM, demonstrated a greater risk (aHR 2) than transient hypotension (aHR 1.265). Hypotension was correlated with various complications. Differences in lactate levels were persistent, regardless of the initial fluid therapy (p < 0.001). Hypotension showed a strong correlation with unfavorable neurological outcome, especially in the early phase after TTM initiation, and complications. It is essential to manage hypotension that occurs at the beginning of TTM initiation to recover cerebral function in cardiac arrest patients.

O-46 EEG connectivity measures in prognostication of postanoxic coma patients

Early prognostication in postanoxic comatose patients remains a challenge. In this work, we investigate EEG functional connectivity (FC) measures as a contributor to prediction of outcome in these patients, as well as their additional value when combined with other validated qEEG measures. A retrospective study of prospectively collected data was performed. Outcome was assessed at 6 months and categorized as “good” (CPC 1–2) or “poor” (CPC 3–5). Coherence, corrected imaginary coherence, phase locking value, corrected imaginary phase locking value, and mutual information were calculated in EEGs recorded at 12, 24, and 48 h after cardiac arrest (CA). Sets of machine learning classification models were trained and validated with 3 different grops of parameters: FC metrics, an already validated set of conventional qEEG measures, and a combination of both. We included 594 patients, with 46% presenting good outcome. A sensitivity of 50.8% (48–52% CI) in predicting poor outcome was achieved by the best FC-based classifier at 12 h after CA, while the best conventional qEEG-based model presented a sensitivity of 32.6% (28–37% CI) using data from 12 and 48 h after CA. The best combined model achieved a sensitivity of 69.3% (64–74% CI) with the 12 and 48 h dataset. All sensitivities for poor outcome prediction are at 100% specificity (98–100% CI). FC parameters derived from EEG contribute to outcome prediction of postanoxic coma by themselves and are complementary to a validated model of classic EEG parameters, showing better performance than methods currently used in clinical practise and newly proposed.

Giant somatosensory evoked potentials are uncommon in patients with post-anoxic coma and paroxysmal electroencephalographic activity

Objectives Post-anoxic encephalopathy (PAE) is a severe neurological condition associated with poor outcome. As part of a multi-modal evaluation, electrophysiological investigations such as electroencephalography (EEG) and somatosensory evoked potentials (SSEPs) have been shown to be reliable outcome predictors in the assessment of comatose survivors, particularly with PAE [3] . The aim of the study was firstly to evaluate the feasibility of performing SSEPs in post-anoxic comatose patients with paroxysmal activity on EEG and secondly to assess the relationship between EEG cortical hyperexcitability and giant cortical N20 SSEPs responses. Methods In this retrospective study between 2016 and 2018, patients with PAE, paroxysmal activity on EEG and available median nerve SSEPs data were included in the analysis. Paroxysmal activity was identified on the EEG performed in the last 48 h preceding SSEPs. We evaluated the N20 amplitude from baseline, and P14-N20 and N20-P24 peak to peak amplitudes. Giant SSEPs were defined as a N20 exceeding 2.7 μV or N20–N24 exceeding 5.5 μV [2] or a late giant component exceeding 5 μV [1] . Results Twenty-one patients were included; 14 men (67%) mean age 66 ± 18 years. A total of 62% of PAE cases were due to cardiac arrest. Nineteen patients died following withdrawal of life support, one died spontaneously and one patient survived. Three patterns of EEG paroxysmal activity were identified: continuous rhythmic activity (n = 3), periodic generalized discharges (GPDs) on a low frequencies background (n = 12) and GPDs on a flat background (burst-suppression) (n = 6). SSEPs were giant in 3 patients (14%), normal in 7 patients (34%), reduced in 3 patients (14%) and absent bilaterally in 8 (38%). Conclusions Our study shows that performing SSEPs is feasible in PAE patients with EEG paroxysmal activity. Giant SSEPs are uncommon in these patients. The EEG cortical hyperexcitability reflects different stages of brain injury, as it can be associated with preserved (even giant), or absent SSEPs.

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.

48. Does it exist an interobserver variability in the interpretation of SSEPs in comatose patients after cardiac arrest? An answer from the Italian Multicentric study ProNeCA

Evaluate inter-observer variability reading of SSEPs in post-anoxic comatose patients included in ProNeCa. 3 readers and a “Gold Standard”, central coordinatior of Italian study, decided to interpretate independently 13 SSEPs. SEPs evaluation was splited into “Absent” (A), “Present” (P) and Not Valutable (NV). The degree of interobserver agreement was calculated using Overall Agreement, Kappa Coefficients and Intraclass Correlation Coefficient (ICC). Overal Agreement between raters (69.2%; 95%CI 38.6–90.9) and agreement of each rater vs. GS was good (from Rater1 = 84.6% to Rater3 = 92.3%). Interrater Agreement was substantial, Exact kappa = 0.64. For category A was 0.58 (moderete agreement), NV 0.62 (substantial agreement) and Present 0.77 (good). Single raters were in good agreement vs. GS (two had a weighted κ⩾0.800), higher than K for bivariate comparison among raters (weighted κ from 0.68 to 0.87). ICC yielded a good 0.747 [0.49–0.91] P = 0.0287. Interobserver agreement for A in accord with lecterature was moderate, with quite wide confidence intervals. Each rater is from fair to good agreement with the GS. To reach a more reliable agreement and reduce CI we decided to increse the sample size: 32 SSEP have been reed but not yet included in this analysis.

O80 Neurophysiological prognosis in comatose patients after cardiac arrest: The italian multicentric study (PRONECA) – preliminary data-

Objective To evaluate the prognostic value of EEG and SEPs association in post-anoxic comatose patients at different recording time from cardiac arrest (CA) a italian multicentric study. Methods Comatose patients after CA were included.EEG and SEPs were recorded within 12 h and at 72 h after CA. EEG was classified into “non-continuous” (low voltage, isoelectric, burst-suppression) and “continuous” (other patterns except epileptiform). SEPs were dichotomized into “bilaterally absent” (BA) and “present”. Outcome was evaluated at 6 months by GOS. “Recovery of consciousness” was considered good outcome. Results At the moment four center took part to the study and 230 patients were included. EEG and SEPs were recorded in 92 within 12 h in 102 at 72 h. “Continuous” EEG pattern at 12 h always predicted good outcome, “non-continuous” pattern at 72 h always predicted poor outcome. BA SEPs always predicted poor outcome. Early “continuous” EEG pattern was always associated with present SEPs. Conclusion EEG is a reliable time-dependent predictor of good outcome (within 12 h) and poor outcome (after 72 h). SEP is time-independent predictor of poor outcome. Early “continuous” EEG and BA SEPs are never associated together. Significance The combination of EEG/SEP findings allows prediction of good and poor outcome (within 12 h after CA) and of poor outcome (after 48–72 h). Recording of EEG and SEPs in the same patients allows always an increase in the number of cases correctly classified and an increase of the reliability of prognostication in a single patient due to concordance of patterns.

Auditory discrimination improvement predicts awakening of postanoxic comatose patients treated with targeted temperature management at 36 °C

BackgroundOutcome prognostication in postanoxic comatose patients is more accurate in predicting poor than good recovery. Using electroencephalography recordings in patients treated with targeted temperature management at 33°C (TTM 33), we have previously shown that improvement in auditory discrimination over the first days of coma predicted awakening. Given the increased application of a 36°C temperature target (TTM 36), here we aimed at validating the predictive value of auditory discrimination in the TTM 36 setting. MethodsIn this prospective multicenter study, we analyzed the EEG responses to auditory stimuli from 60 consecutive patients from the first and second coma day. A semiautomatic decoding analysis was applied to single patient data to quantify discrimination performance between frequently repeated and deviant sounds. The decoding change from the first to second day was used for predicting patient outcome. ResultsWe observed an increase in auditory discrimination in 25 out of 60 patients. Among them, 17 awoke from coma (68% positive predictive value; 95% confidence interval: 0.46–0.85). By excluding patients with electroencephalographic epileptiform features, 15 of 18 exhibited improvement in auditory discrimination (83% positive predictive value; 95% confidence interval: 0.59–0.96). Specificity of good outcome prediction increased after adding auditory discrimination to EEG reactivity. ConclusionThese results suggest that tracking of auditory discrimination over time is informative of good recovery independent of the temperature target. This quantitative test provides complementary information to existing clinical tools by identifying patients with high chances of recovery and encouraging the maintenance of life support.

Accuracy of Limited-Montage Electroencephalography in Monitoring Postanoxic Comatose Patients.

Continuous EEG (cEEG) monitoring may help to identify the small percentage of adults with hypoxic-ischemic encephalopathy (HIE) who will regain consciousness if allowed sufficient time. However, the limited yield in this population has led some to question the cost-effectiveness cEEG monitoring in this population. We hypothesized that limited-montage cEEG could provide essentially the same neurophysiologic information at lower cost. In this proof of concept study, we aim to demonstrate the potentials of limited channel EEG in prognostication in postanoxic patients. We retrospectively reviewed cEEG data from cases monitored at our institution with conventional 21-channel EEG over a 6-month period. Twenty-eight cases were identified in which patients with HIE underwent cEEG for at least 24 hours. Gold-standard findings were determined by conventional visual analysis of the full cEEG, and 2 independent electroencephalographers scored the same data using only limited-montage (4-channel) views. The sensitivity and specificity of limited-montage cEEG review were compared with conventional analysis. We also compared the relative costs of conventional and limited-montage EEG. Using 4-channel limited montage cEEG, reviewers were able to classify accurately background continuity (in 88%), background amplitude (in 81%), maximum background frequency (in 70%), periodic epileptiform discharges, including a seizure (in 92%) and sporadic discharges (in 91%). All epileptiform features were detected with greater than 90% sensitivity and specificity. Eye movement artifact seen over bifrontal electrodes gave false positive detections of periodic epileptiform discharges in 31% of cases. Limited-channel continuous EEG monitoring can provide meaningful electrophysiological data that can be used for prognostication in postanoxic comatose patients. Limited channel EEG can be a cost-effective alternative to conventional EEG monitoring in post-anoxic comatose patients.

11. Post-anoxic status epilepticus: The impact of medical treatment on outcome. A single center experience

In post-anoxic comatose patients, SE is used to be considered a strong poor outcome predictor. The aim of our study was to assess, retrospectively, the outcome of SE after pharmacological treatment with antiepileptic (AEDs) and/or anesthetic drugs in a series of post-anoxic comatose patients and to verify any correlation with other outcome predictors. We retrospectively analyzed data collected from 60 patients affected by hypoxic encephalopathy. Demographic data, SE subtype and duration, coma scale scores (FOUR scale), time of return of spontaneous circulation (ROSC), presence of cortical SSEP (N20), presence of pupillary light reflex, pharmacological treatment and clinical outcome according to Glasgow Outcome Scale (GOS) were evaluated. Finally we performed a statistical analysis by means of a logistic regression. A total of 17 patients showed an EEG pattern consistent to SE. Of them, 12 patients were treated with antiepileptic/anesthetic drugs: 7 patients showed a good outcome (GOS > 2). We found a statistically significant correlation with preserved N20 and anesthetic drugs. Based on our results, we can argue that in post-anoxic encephalopathy, SE doesn’t always correlate with poor outcome especially when other more robust prognostic factors, such as cortical SSEP, are preserved. In such patients, an aggressive antiepileptic treatment could modify prognosis.

12. Outcome prediction in comatose patients after cardiac arrest, the utility of early EEG/SEP recordings during therapeutic hypothermia: The italian multicentric study (PRONECA) preliminary data

Somatosensory evoked potentials(SEPs) and EEG are reliable outcome predictors of coma after cardiac arrest (CA). Nevertheless, only few multicentric studies are available. Aim of the study was to evaluate the prognostic value of EEG and SEPs association in post-anoxic comatose patients at different recording time from cardiac arrest (CA) in an Italian multicentric study. Comatose patients after CA treated with TH were included. EEG and SEPs were recorded within 12 h and at 72 h after CA. EEG was classified into “non-continuous” and “continuous”. SEPs were dichotomized into “bilaterally absent” (BA) and “present”. Neurologic outcome was evaluated at 6 months by GOS: “awakening”(GOS 3–5) was considered good outcome. 83 patients were included to date. “Continuous” EEG pattern at 12 h always predicted good outcome, “non-continuous” pattern at 72 h always predicted poor outcome. BA SEPs always predicted poor outcome. Early “continuous” EEG pattern was always associated with present SEPs. SEPs provide a specific and time-independent predictor of poor outcome. EEG provide a specific and time-dependent predictor of good outcome (at

Evidence of trace conditioning in comatose patients revealed by the reactivation of EEG responses to alerting sounds

Trace conditioning refers to a learning process occurring after repeated presentation of a neutral conditioned stimulus (CS+) and a salient unconditioned stimulus (UCS) separated by a temporal gap. Recent studies have reported that trace conditioning can occur in humans in reduced levels of consciousness by showing a transfer of the unconditioned autonomic response to the CS+ in healthy sleeping individuals and in vegetative state patients. However, no previous studies have investigated the neural underpinning of trace conditioning in the absence of consciousness in humans.In the present study, we recorded the EEG activity of 29 post-anoxic comatose patients while presenting a trace conditioning paradigm using neutral tones as CS+ and alerting sounds as UCS. Most patients received therapeutic hypothermia and all were deeply unconscious according to standardized clinical scales. After repeated presentation of the CS+ and UCS couple, learning was assessed by measuring the EEG activity during the period where the UCS is omitted after CS+ presentation. Specifically we assessed the ‘reactivation’ of the neural response to UCS omission by applying a decoding algorithm derived from the statistical model of the EEG activity in response to the UCS presentation. The same procedure was used in a group of 12 awake healthy controls.We found a reactivation of the UCS response in absence of stimulation in eight patients (five under therapeutic hypothermia) and four healthy controls. Additionally, the reactivation effect was temporally specific within trials since it manifested primarily at the specific latency of UCS presentation and significantly less before or after this period. Our results show for the first time that trace conditioning may manifest as a reactivation of the EEG activity related to the UCS and even in the absence of consciousness.

Prediction of cognitive outcome based on the progression of auditory discrimination during coma

AimTo date, no clinical test is able to predict cognitive and functional outcome of cardiac arrest survivors. Improvement of auditory discrimination in acute coma indicates survival with high specificity. Whether the degree of this improvement is indicative of recovery remains unknown. Here we investigated if progression of auditory discrimination can predict cognitive and functional outcome. MethodsWe prospectively recorded electroencephalography responses to auditory stimuli of post-anoxic comatose patients on the first and second day after admission. For each recording, auditory discrimination was quantified and its evolution over the two recordings was used to classify survivors as “predicted” when it increased vs. “other” if not. Cognitive functions were tested on awakening and functional outcome was assessed at 3 months using the Cerebral Performance Categories (CPC) scale. ResultsThirty-two patients were included, 14 “predicted survivors” and 18 “other survivors”. “Predicted survivors” were more likely to recover basic cognitive functions shortly after awakening (ability to follow a standardized neuropsychological battery: 86% vs. 44%; p=0.03 (Fisher)) and to show a very good functional outcome at 3 months (CPC 1: 86% vs. 33%; p=0.004 (Fisher)). Moreover, progression of auditory discrimination during coma was strongly correlated with cognitive performance on awakening (phonemic verbal fluency: rs=0.48; p=0.009 (Spearman)). ConclusionsProgression of auditory discrimination during coma provides early indication of future recovery of cognitive functions. The degree of improvement is informative of the degree of functional impairment. If confirmed in a larger cohort, this test would be the first to predict detailed outcome at the single-patient level.

80. EEG is a time-dependent reliable indicator of good or poor outcome in comatose patients after cardiac arrest

The prognostic role of EEG during early phase after cardiac arrest (CA) has been recently emphasized, but different classifications and definitions have been employed among studies. A standardized terminology for ICU patients has been recently proposed by American Clinical Neurophysiology Society (ACNS). We retrospectively evaluated the prognostic value of EEG according to different times of recording in postanoxic comatose patients, classifying EEGs according to the ACNS terminology with a main focus on background continuity. The study included EEG of 211 patients, recorded at 12, 24, 48 and 72 h. At each timing we observed at least one EEG pattern with specificity of 100% for poor or good outcome. At 12 h “continuous” and “nearly continuous” EEGs were always associated to good outcome, whereas isoelectric EEG and “burst-suppression with highly epileptiform discharges” were always associated to poor outcome. At 24 h isoelectric and all “burst-suppression” EEGs were always associated to poor outcome. At 48 h and 72 h isoelectric, “burst-suppression” and “suppressed” (

Prognostic value of somatosensory-evoked potentials in neurology: A critical review in hypoxic encephalopathy.

Prediction of prognosis in comatose patients surviving a cardiac arrest is still one of the intractable problems in critical care neurology because of lack of fool-proof ways to assess the outcome. Of all these measures, somatosensory-evoked potential (SSEP) has been perhaps the most evaluated and heavily relied-upon tool over the past several decades for assessing coma. Recent studies have given rise to concerns regarding the "absoluteness" of SSEP signals for the prognostic evaluation of coma. In this critical review, we searched the literature to focus on studies conducted so far on the prognostic evaluation of postanoxic coma using SSEPs. All those studies published on the use of SSEP as a prognostication tool in postanoxic coma were reviewed. A narrative review was created that included the strengths as well as limitations of the use of SSEP in postanoxic coma. The use of SSEP in coma has been universal for the purpose of prognostication. However, it has its own advantages as well as limitations. The limitations include challenges in performing and getting SSEP signals during coma as well as the challenges involved in reading and interpreting the signals. The recent usage of therapeutic hypothermia has become another factor that often interferes with the SSEP recording. Finally, based on these study results, some recommendations are generated for the effective use of SSEPs in comatose patients for further prognostication. We advocate that SSEP should be an integral component for the assessment of postanoxic comatose patients due to its several advantages over other assessment tools. However, SSEP recordings should follow certain standards. One should be aware that its interpretation may be biased by several factors. The bias created by the concept of "self-fulfilling hypothesis" should always be borne in mind before discontinuation of life support systems in terminal patients.

10. Prediction of good and poor outcome in comatose patients after cardiac arrest: The utility of early EEG/SEP recordings during therapeutic hypothermia

To evaluate the prognostic value of EEG and SEPs in post-anoxic comatose patients at 12 h, 24 h and 72 h from cardiac arrest (CA). Comatose patients after CA treated with TH were included. EEG and SEPs were recorded within 12 h, 24 h and 72 h after CA. EEG was classified into “non-continuous” (low voltage, isoelectric, burst-suppression) and “continuous” (other patterns except epileptiform). SEPs were dichotomized into “bilaterally absent” (BA) and “present”. Neurologic outcome was evaluated at 6 months by GOS: “awakening” (GOS 3–5) was considered good outcome. EEG and SEPs were recorded in 147 patients, 33 of whom within 12 h. “Continuous” EEG pattern at 12 h always predicted good outcome, “non-continuous” pattern at 72 h always predicted poor outcome. BA SEPs always predicted poor outcome. Early “continuous” EEG pattern was always associated with present SEPs. SEPs provide a specific and time-independent predictor of poor outcome (bilateral absence). EEG provide a specific and time-dependent predictor of good outcome (“continuous” pattern at <12 h) and poor outcome (“non-continuous” pattern at 48–72 h). Early “continuous” EEG and BA SEPs are never associated together. Combined EEG/SEPs recordings are a useful tool for reliable prognostication both of good and poor outcome in comatose patients treated with TH.

Clinical evolution after a non-reactive hypothermic EEG following cardiac arrest.

Lack of electroencephalography (EEG) background reactivity during therapeutic hypothermia (TH) has been associated with poor outcome in post-anoxic comatose patients. However, decision on intensive care withdrawal is based on normothermic (NT) evaluations. This study aims at exploring whether patients showing recovery of EEG reactivity in NT after a non-reactive EEG in TH differ from those remaining non-reactive. Patients with non-reactive EEG during TH were identified from our prospective registry of consecutive comatose adults admitted after successful resuscitation from CA between April 2009 and June 2014. Variables including neurological examination, serum neuron-specific enolase (NSE), procalcitonin, and EEG features were compared regarding impact on functional outcome at 3 months. Seventy-two of 197 patients (37 %) had a non-reactive EEG background during TH with thirteen (18 %) evolving towards reactivity in NT. Compared to those remaining non-reactive (n = 59), they showed significantly better recovery of brainstem reflexes (p < 0.001), better motor responses (p < 0.001), transitory consciousness improvement (p = 0.008), and a tendency toward lower NSE (p = 0.067). One patient recovering EEG reactivity survived with good functional outcome at 3 months. Recovery of EEG reactivity from TH to NT seems to distinguish two patients' subgroups regarding early neurological assessment and transitory consciousness improvement, corroborating the role of EEG in providing information about cerebral functions. Understanding these dynamic changes encourages maintenance of intensive support in selected patients even after a non-reactive EEG background in TH, as a small subgroup may indeed recover with good functional outcome.

RETRACTED: P02. Predicting the outcome of post-anoxic comatose patients based on single-trial EEG analysis

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This Abstract has been retracted at the request of the co-authors due to the fact that the Abstract was prepared and submitted by a single author, without the agreement of other co-authors, includes several mistakes and potentially conflicts with another publication.

P478: Prediction of good and poor outcome in comatose patients after cardiac arrest: the utility of early EEG/SEP recordings during therapeutic hypothermia

To evaluate the prognostic value of EEG and SEPs in post-anoxic comatose patients at 12 h, 24 h and 72 h from cardiac arrest (CA). Comatose patients after CA treated with TH were included. EEG and SEPs were recorded within 12 h, 24 h and 72 h after CA. EEG was classified into “non-continuous” (low voltage, isoelectric, burst-suppression) and “continuous” (other patterns except epileptiform). SEPs were dichotomized into “bilaterally absent” (BA) and “present”. Neurologic outcome was evaluated at 6 months by GOS: “awakening” (GOS 3–5) was considered good outcome. EEG and SEPs were recorded in 147 patients, 33 of whom within 12 h. “Continuous” EEG pattern at 12 h always predicted good outcome, “non-continuous” pattern at 72 h always predicted poor outcome. BA SEPs always predicted poor outcome. Early “continuous” EEG pattern was always associated with present SEPs. SEPs provide a specific and time-independent predictor of poor outcome (bilateral absence). EEG provide a specific and time-dependent predictor of good outcome (“continuous” pattern at