"Alpha-pattern coma" in high voltage electrical injury.

Two cases are reported in which reversible deep coma subsequent to high voltage electrical injury occurred in association with alpha frequencies in the EEG. The EEG pattern differs from the alpha rhythm of the normal awake patient by its diffuse distribution and unresponsiveness to a variety of stimulation. The term "alpha-pattern coma" is introduced to designate the occurrence of this pattern in comatose patients. The EEG in the cases described initially demonstrated activity in the alpha frequency which occurred in a generalized distribution and was unresponsive to stimulation. During the early stages of recovery an increased incidence of theta and delta activity was observed. The recovery records contained a low voltage alpha rhythm and responded to photic stimulation. The literature on this subject is reviewed and the possible modes of pathogenesis are discussed. The authors conclude that such examples of alpha-pattern coma are the result of diffuse cerebral damage and might be detected more frequently in comatose patients who survive if these patients are studied earlier in their clinical course with EEGs.     

Are neurophysiologic tests reliable,ultra-early prognostic indices after cardiac arrest?

ObjectivesDetermining early and reliable prognosis in comatose subjects after cardiac arrest is a central component of post–cardiac arrest care both for developing realistic prognostic expectations for families, and for better determining which resources are mobilized or withheld for individual patients. The aim of the study was to evaluate the prognostic accuracy of EEG and SEP patterns during the very early period (within the first 6 h) after cardiac arrest.MethodsWe retrospectively analysed comatose patients after CA, either inside or outside the hospital, in which prognostic evaluation was made during the first 6 h from CA. Prognostic evaluation comprised clinical evaluation (GCS and pupillary light reflex) and neurophysiological (electroencephalography (EEG) and somatosensory evoked potentials (SEP)) studies. Prognosis was evaluated with regards to likelihood of recovery of consciousness and also likelihood of failure to regain consciousness.ResultsForty-one comatose patients after cardiac arrest were included. All patients with continuous and nearly continuous EEG recovered consciousness. Isoelectric EEG was always associated with poor outcome. Burst-suppression, suppression and discontinuous patterns were usually associated with poor outcome although some consciousness recovery was observed. Bilaterally absent SEP responses were always associated with poor outcome. Continuous and nearly continuous EEG patterns were never associated with bilaterally absent SEP.ConclusionsDuring the very early period following cardiac arrest (first 6 h), EEG and SEP maintain their high predictive value to predict respectively recovery and failure of recovery of consciousness. A very early EEG exam allows identification of patients with very high probability of a good outcome, allowing rapid use of the most appropriate therapeutic procedures.     

Association between somatosensory evoked potentials and EEG in comatose patients after cardiac arrest

ObjectiveTo analyze the association between SSEP results and EEG results in comatose patients after cardiac arrest, including the added value of repeated SSEP measurements.MethodsContinuous EEG was measured in 619 patients during the first 3–5 days after cardiac arrest. SSEPs were recorded daily in the first 55 patients, and on indication in later patients. EEGs were visually classified at 12, 24, 48, and 72 h after cardiac arrest, and at the time of SSEP. Outcome at 6 m was dichotomized as good (Cerebral Performance Category 1–2) or poor (CPC 3–5). SSEP and EEG results were related to outcome. Additionally, SSEP results were related to the EEG patterns at the time of SSEP.ResultsAbsent SSEP responses and suppressed or synchronous EEG on suppressed background ≥24 h after cardiac arrest were invariably associated with poor outcome. SSEP and EEG identified different patients with poor outcome (joint sensitivity 39% at specificity 100%). N20 responses were always preserved in continuous traces at >8 Hz. Absent SSEPs did not re-emerge during the first five days.ConclusionsSSEP and EEG results may diverge after cardiac arrest.SignificanceSSEP and EEG together identify more patients without chance of recovery than one of these alone.     

"Alpha-like" rhythms in electroencephalograms in coma after cariac arrest.

Electroencephalograms (EEGs) of 12 comatose patients showed "alpha-like" rhythms after cardiac arrest. Four patients revealed a stage II sleep pattern and two patients showed signs of reactivity in their EEGs. One patient recovered with minimal impairment of memory, one patient lived for 3 months, and 10 died 3 ot 30 days after cardiac arrest. Examination of the brain demonstrated the usual anoxic lesions in three patients and "respirator brain" in one. In three patients with ventral pontine syndrome, a somewhat similar EEG pattern, but with distinct differences in topography and reactivity, was observed. In order to recognize alpha-like rhythms in comatose patients after cardiac arrest, EEGs should be recorded daily for several days.     

Burst-suppression with identical bursts: A distinct EEG pattern with poor outcome in postanoxic coma

ObjectiveTo assess the incidence, quantified EEG characteristics, and prognostic significance of “burst-suppression with identical bursts” and to discuss potential pathophysiological mechanisms.MethodsBurst-suppression EEGs were identified from a cohort of 101 comatose patients after cardiac arrest, and from our complete database of 9600 EEGs, since 2005. Patterns with and without identical bursts were classified visually by two observers. Of patients after cardiac arrest, outcomes were assessed at three and six months. Identical and non-identical burst-suppression patterns were compared for quantified EEG characteristics and clinical outcome. Cross correlation of burstshape was applied to the first 500 ms of each burst.ResultsOf 9701 EEGs, 240 showed burst-suppression, 22 with identical bursts. Identical bursts were observed in twenty (20%) of 101 comatose patients after cardiac arrest between a median of 12 and 36 h after the arrest, but not in the six patients with other pathology than cerebral ischemia, or the 183 with anesthesia induced burst suppression. Inter-observer agreement was 0.8 and disagreement always resulted from sampling error. Burst-suppression with identical bursts was always bilateral synchronous, amplitudes were higher (128 vs. 25 μV, p = 0.0001) and correlation coefficients of burstshapes were higher (95% >0.75 vs. 0% >0.75, p < 0.0001) than in burst-suppression without identical bursts. All twenty patients with identical bursts after cardiac arrest had a poor outcome versus 10 (36%) without identical bursts.Conclusion“Burst-suppression with identical bursts” is a distinct pathological EEG pattern, which in this series only occurred after diffuse cerebral ischemia and was invariably associated with poor outcome.SignificanceIn comatose patients after cardiac arrest, “burst-suppression with identical bursts” predicts a poor outcome with a high specificity.     

Post-cardiorespiratory arrest beta-alpha coma: an unusual electroencephalographic phenomenon

The presence of frontally-dominant alpha pattern in the EEG is common in patients with coma due to trauma, toxic-metabolic causes and following cardiorespiratory arrest. Diffuse beta activity following resuscitation after a cardiac arrest is not well recognized. We report a case of coma in a 3-year-old girl who had a cardiac arrest from which she was revived. Initial EEG showed diffuse beta activity, which later evolved to predominantly alpha activity. The possible mechanisms involved in the generation of such rhythms are discussed. Transition of EEG activity from faster to slower frequencies is suggested as an adverse prognostic factor in post-cardiorespiratory arrest coma.     

Dynamic functional connectivity of the EEG in relation to outcome of postanoxic coma

ObjectiveEarly EEG contains reliable information for outcome prediction of comatose patients after cardiac arrest. We introduce dynamic functional connectivity measures and estimate additional predictive values.MethodsWe performed a prospective multicenter cohort study on continuous EEG for outcome prediction of comatose patients after cardiac arrest. We calculated Link Rates (LR) and Link Durations (LD) in the α, δ, and θ band, based on similarity of instantaneous frequencies in five-minute EEG epochs, hourly, during 3 days after cardiac arrest. We studied associations of LR and LD with good (Cerebral Performance Category (CPC) 1–2) or poor outcome (CPC 3–5) with univariate analyses. With random forest classification, we established EEG-based predictive models. We used receiver operating characteristics to estimate additional values of dynamic connectivity measures for outcome prediction.ResultsOf 683 patients, 369 (54%) had poor outcome. Patients with poor outcome had significantly lower LR and longer LD, with largest differences 12 h after cardiac arrest (LR_θ 1.87 vs. 1.95 Hz and LD_α 91 vs. 82 ms). Adding these measures to a model with classical EEG features increased sensitivity for reliable prediction of poor outcome from 34% to 38% at 12 h after cardiac arrest.ConclusionPoor outcome is associated with lower dynamics of connectivity after cardiac arrest.SignificanceDynamic functional connectivity analysis may improve EEG based outcome prediction.     

Hanging survivor showing alpha coma--a case report

A case of a survivor who showed alpha coma after an attempted suicide by hanging was reported. A 19 years old woman was admitted to the hospital because of respiratory arrest following a hanging attempt on October 10, 1987. She was found pendent completely. On admission she was comatose and the pupils were not reactive to light. The systolic blood pressure was 60 mmHg and immediately an endotracheal intubation was instituted. After six hours from the onset, the spontaneous respiration was restored and the pupils reacted briskly to light. At 48 hours later she was still comatose, presenting flaccid quadriplegia with no responses to stimulations. An EEG showed a moderate amount of regular, 8 approximately 10 Hz, 10 approximately 50 microV potentials distributed predominantly on the centro-parieto-occipital regions. This alpha rhythm had persisted until 72 hours from the onset, and subsequently diffuse 5 approximately 7Hz, 10 approximately 40 microV slow activity replaced the alpha frequency at 120 hours after the attempt. On the 5th hospital day the hyperbaric oxygen therapy was given and on the 7th day she had become conscious, but showed the apallic syndrome. The both auditory and somatosensory evoked potentials were normal. On the 45th day the brain MRI revealed diffuse cerebral cortical atrophy, although no lesions were visualized in the brain stem. She showed gradual progress towards neurologic recovery. This is the first presentation of a survivor from alpha coma caused by anoxic encephalopathy following a hanging attempt.     

Clinical neurophysiologic monitoring and brain injury from cardiac arrest

Electrophysiologic testing continues to play an important role in injury stratification and prognostication in patients who are comatose after cardiac arrest. As discussed previously, however, the adage about treating whole patients, not just the numbers, is relevant in this situation. EEG and SSEP can offer high specificity for discerning poor prognosis as long as they are applied to appropriate patient populations. As discussed previously, EEG and SSEP patterns change during the first hours to days after cardiac arrest and negative prognostic information should not be based solely on studies performed during the first 24 hours. Both electrophysiologic techniques also are susceptible to artifacts that may worsen the electrical patterns artificially and suggest a falsely poor prognosis. EEG is suppressed by anesthetic agents and hypothermia, both of which may produce ECS and burst suppression. Patients who experience respiratory arrest from a toxic ingestion of narcotics or barbiturates, in particular, may present with high-grade EEG patterns initially. Many patients also receive anesthetic medications at the time of tracheal intubation, which may linger beyond their normal half-life in patients who have hepatic or renal insufficiency or concurrent use of interacting medications. SSEP is much less susceptible to sedative anesthetic agents, but hypothermia is demonstrated to prolong evoked potential latencies. As therapeutic hypothermia becomes more common after cardiac arrest, the effect of temperature on electrophysiologic testing needs to be taken into account. The publications discussed previously also emphasize the need to adjust the prognostic value of electro-physiologic tests to the pretest probability of meaningful neurologic recovery in individual patients. Clearly, grade I EEG patterns and normal N20 potentials indicate a much better prognosis in patients who have a short du-ration of cardiac arrest, short duration of coma after resuscitation, and when the studies are performed within the first few days. In patients who remain in coma days after resuscitation and lack appropriate brainstem reflexes, however, even the most normal appearing electrophysiologic patterns do little to change the overall prognosis. Aside from prognostication, electrophysiologic testing holds great promise in defining the basic anatomy and physiology of coma emergence after cardiac arrest. In addition, quantitative EEG and automated evoked potentials have the potential to render these tools less subjective and arcane and more applicable for monitoring patients in the period during and immediately after resuscitation. Quantitative EEG also has great potential asa tool to define the time window for neuroprotective intervention and the means to track the response to such therapies in real time.     

Quantitative EEG reactivity and machine learning for prognostication in hypoxic-ischemic brain injury

ObjectiveElectroencephalogram (EEG) reactivity is a robust predictor of neurological recovery after cardiac arrest, however interrater-agreement among electroencephalographers is limited. We sought to evaluate the performance of machine learning methods using EEG reactivity data to predict good long-term outcomes in hypoxic-ischemic brain injury.MethodsWe retrospectively reviewed clinical and EEG data of comatose cardiac arrest subjects. Electroencephalogram reactivity was tested within 72 h from cardiac arrest using sound and pain stimuli. A Quantitative EEG (QEEG) reactivity method evaluated changes in QEEG features (EEG spectra, entropy, and frequency features) during the 10 s before and after each stimulation. Good outcome was defined as Cerebral Performance Category of 1–2 at six months. Performance of a random forest classifier was compared against a penalized general linear model (GLM) and expert electroencephalographer review.ResultsFifty subjects were included and sixteen (32%) had good outcome. Both QEEG reactivity methods had comparable performance to expert EEG reactivity assessment for good outcome prediction (mean AUC 0.8 for random forest vs. 0.69 for GLM vs. 0.69 for expert review, respectively; p non-significant).ConclusionsMachine-learning models utilizing quantitative EEG reactivity data can predict long-term outcome after cardiac arrest.SignificanceA quantitative approach to EEG reactivity assessment may support prognostication in cardiac arrest.     

EEG‐based outcome prediction after cardiac arrest with convolutional neural networks: Performance and visualization of discriminative features

Prognostication for comatose patients after cardiac arrest is a difficult but essential task. Currently, visual interpretation of electroencephalogram (EEG) is one of the main modality used in outcome prediction. There is a growing interest in computer‐assisted EEG interpretation, either to overcome the possible subjectivity of visual interpretation, or to identify complex features of the EEG signal. We used a one‐dimensional convolutional neural network (CNN) to predict functional outcome based on 19‐channel‐EEG recorded from 267 adult comatose patients during targeted temperature management after CA. The area under the receiver operating characteristic curve (AUC) on the test set was 0.885. Interestingly, model architecture and fine‐tuning only played a marginal role in classification performance. We then used gradient‐weighted class activation mapping (Grad‐CAM) as visualization technique to identify which EEG features were used by the network to classify an EEG epoch as favorable or unfavorable outcome, and also to understand failures of the network. Grad‐CAM showed that the network relied on similar features than classical visual analysis for predicting unfavorable outcome (suppressed background, epileptiform transients). This study confirms that CNNs are promising models for EEG‐based prognostication in comatose patients, and that Grad‐CAM can provide explanation for the models' decision‐making, which is of utmost importance for future use of deep learning models in a clinical setting.     

Physiologic and prognostic significance of "alpha coma".

A patient with posthypoxic "alpha coma" is described whose EEGs were recorded before coma, within two hours following the onset of coma and after recovery. The differences observed between the alpha activity during coma and that seen before and after suggest that the alpha activity during coma and the physiologic alpha rhythm are different phenomena. This case, as well as others reported, also suggests that "alpha coma" resolving in the first 24 hours following hypoxia may have a better prognosis than "alpha coma" detected after the first day, and stresses the need for EEG monitoring begun in the immediate period following hypoxia in order to assess accurately the prognostic significance of this EEG pattern in the early stages of postanoxic encephalopathy. The aetiology of "alpha coma" also affects outcome. The survival rate appears higher in patients with respiratory arrest than in those with combined cardiopulmonary arrest.     

Unusual EEG patterns in coma, and their evolution.

A 23-year-old chronic asthmatic patient is reported who showed successively four different EEG patterns within a 7 day period of unconsciousness following cardio-respiratory arrest. The initial record was dominated by alpha activity, then beta activity supervened, to be followed by spindle components. Finally an isoelectric tracing occurred before death. A computer file search for all cases of unusual EEG coma patterns was carried out. It failed to reveal any other patient with a similar sequence, but various types of evolution were noted. Such features are seen in only a very small percentage of comatose patients, and in the context of cardio-respiratory arrest are almost invariably fatal.     

Prognostic value of myoclonus status in comatose survivors of cardiac arrest

Generalized myoclonus status is common in comatose patients after cardiac resuscitation, but its prognostic value is uncertain. We studied the clinical, radiologic, and pathologic findings in 107 consecutive patients who remained comatose after cardiac resuscitation. Myoclonus status was present in 40 patients (37%). Features more prevalent in patients with myoclonus status were burst suppression on electroencephalograms, cerebral edema or cerebral infarcts on computed tomography scans, and acute ischemic neuronal change in all cortical laminae. All patients with myoclonus status died. Of 67 patients without myoclonus, 20 awakened. We conclude that myoclonus status in postanoxic coma should be considered an agonal phenomenon that indicates devastating neocortical damage. Its presence in comatose patients after cardiac arrest must strongly influence the decision to withdraw life support.     

The EEG in coma.

The EEG allows insight into thalamocortical function in comatose patients when this is inaccessible clinically. A single EEG can help with broad diagnostic categorization whereas continuous or serial EEG provides monitoring for unstable and potentially treatable conditions and for monitoring the effects of therapy. The EEG plays a supplemental role in establishing the prognosis in disease states that are capable of causing neuronal death. The most prevalent and problematic of these conditions involves survivors of cardiac arrest who are initially in coma with intact brainstem reflexes. In such patients single EEGs are of 100% specificity for no possibility of recovery of consciousness only for essentially complete generalized suppression (<10 microV) after the first day of the arrest. Several other generalized patterns, including less marked suppression, burst-suppression, epileptiform activity, periodic complexes, and alpha-theta coma patterns, usually but not invariably indicate a poor outcome. Serial EEGs, continuous raw and automated "trending," testing of reactivity, and the inclusion of multiple variables hold promise for an improved role in the prognostic determination in these patients.     

Frequency and Timing of Nonconvulsive Status Epilepticus in Comatose Post-Cardiac Arrest Subjects Treated with Hypothermia

Background  

Therapeutic hypothermia (TH) improves outcomes in comatose patients resuscitated from cardiac arrest. However, nonconvulsive status epilepticus (NCSE) may cause persistent coma. The frequency and timing of NCSE after cardiac arrest is unknown.     

Postanoxic alpha (theta) coma: a reappraisal of its prognostic significance.

OBJECTIVES: To appraise the controversial prognostic significance of postanoxic alpha or theta coma (ATC). METHODS: We prospectively assessed 14 comatose patients with ATC after cardiac arrest by means of a protocol which included repeated clinical examinations, EEG, and median somatosensory evoked potentials (SEP). Good outcome was defined by the reappearance of cognition (Glasgow outcome scale 3-5) at any time during the 1 year follow-up. RESULTS: Nine of 14 patients had a monotonous, frontally accentuated and a reactive alpha (theta) EEG activity (complete ATC). In these patients ATC was recorded a mean of 47 h after resuscitation, the mean Glasgow coma scale (GCS) was 4 at 48 h, and early cortical SEPs were altered or absent in 5 of 7 patients. All nine patients died. In five of 14 patients the alpha (theta) EEG activity was either not monotonous, partially reactive or posteriorly dominant (incomplete ATC). In these patients ATC was recorded a mean of 43 h after resuscitation, the mean GCS was 8 at 48 h, and early cortical SEP were normal in 4 of 5 patients. Three of 5 patients regained cognition, two of them remained however dependent in activities of everyday life. CONCLUSIONS: This study and a review 283 cases of postanoxic ATC reported in the literature suggest the existence of incomplete and complete variants of postanoxic ATC. Whereas complete ATC is invariably associated with a poor outcome, full recovery is possible in patients with incomplete ATC. The combination of EEG, clinical, and SEP findings improves the prognostic accuracy of postanoxic ATC.     

The development of spectral EEG changes during short periods of circulatory arrest.

The EEG was monitored in 56 patients during implantation of an internal cardioverter defibrillator. The purpose of this study was to determine the main EEG frequency ranges that represent ischemic changes during short periods of circulatory arrest. The EEG was recorded with a 16-channel common reference montage (Cz). After onset of circulatory arrest, the log spectral changes of three-epoch moving averages were calculated relative to the baseline spectrum. For factor analysis, 17 EEG periods were selected that showed changes progressing to an isoelectrical period. Topographic differences and the time course of quantitative EEG (qEEG) changes were studied in all 56 patients. For each patient the EEG period with the longest duration of circulatory arrest was chosen. Factor analysis revealed four factors that represented the spectral EEG changes occurring during circulatory arrest and recovery. The frequency intervals of these factors were 0 to 0.5 Hz, 1.5 to 3 Hz, 7.5 to 9.5 Hz, and 15 to 20 Hz for all channels. Only minor topographic differences were found in the power of the spectral changes; the sequence of events was similar for all electrode positions. The first EEG change after circulatory arrest was an initial increase in alpha power and a decrease in beta power. On average, after approximately 15 seconds alpha power started to decrease, beta power decreased further, delta-1 power started to increase, and delta-2 power started to decrease. After approximately 25 seconds, the delta-1 power increase appeared to plateau or to decrease. A circulatory arrest longer than approximately 30 seconds resulted in an isoelectrical EEG. After restoration of the circulation, there was a fast transient increase in delta-1 and delta-2 power, followed by a decrease to baseline. alpha and beta power showed a more gradual increase in power toward baseline and were the last to restore after 60 to 90 seconds. In general, the spectral changes in the alpha and beta frequency ranges were most pronounced and consistent. In conclusion, to detect intraoperative cerebral ischemia, monitoring of changes in the four frequency ranges found is preferable to monitoring changes in the classically defined frequency bands. Furthermore, these results stress the importance of the alpha and beta ranges in detecting cerebral ischemia.     

高颈段脊髓电刺激促醒颅脑创伤昏迷一例并文献复习

目的 研究高颈段脊髓电刺激对颅脑创伤昏迷的促醒作用.方法 观察1例重型颅脑创伤患者高颈段脊髓电刺激术后清醒时间、脑电图、诱发电位及脑血流的变化.结果 患者术后2个月逐渐清醒,脑电图逐渐转为正常α节律,诱发电位潜伏期延长逐渐改善,脑血流明显增加.结论 高颈段脊髓电刺激可能通过增加脑血流、恢复正常的神经电生理活动促醒颅脑创伤昏迷患者.

Abstract：

Objective To study the awoking effect of high cervical spinal cord stimulation on comatose patients with traumatic brain injury.Methods Recovery time,electroencephalogram(EEG),evoked patentials,cerebral blood perfusion after cervical spinal cord stimulation in a comatose patient were investigated.Results The patient emerged form conla at 2 months after spinal cord stimulation treatment.EEG gradually turned into a normal(rhythm,evoked potentials latency improved,and cerebral blood perfusion increased significantly.Conclusions High cervical spinal cord stimulation exerts its beneficial effects to comatose patients with traumatic brain injury by increasing cerebral blood perfusion and restoring normal cerebral electrical activity.     

'Alpha-pattern coma' and survival after cardiac arrest.

A case of survival despite on EEG in the alpha range during coma after cardiac arrest in connection with acute myocardial infarction is reported. The other 5 published cases are referred to. On the basis of the available literature it is concluded that it is impossible to determine the few patients who will survive despite 'alph-pattern coma'.