Early bispectral index and sedation requirements during therapeutic hypothermia predict neurologic recovery following cardiac arrest

Bispectral index and suppression ratio after cardiac arrest: are they useful as bedside tools for rational treatment escalation plans?

INTRODUCTION AND OBJECTIVES

Myocardial dysfunction contributes to early mortality (24-72 hours) among survivors of a cardiac arrest (CA). The benefits of mechanical support in refractory shock should be balanced against the patient's potential for neurological recovery. To date, these early treatment decisions have been taken based on limited information leading mainly to undertreatment. Therefore, there is a need for early, reliable, accessible, and simple tools that offer information on the possibilities of neurological improvement.

METHODS

We collected data from bispectral index (BIS) and suppression ratio (SR) monitoring of adult comatose survivors of CA managed with targeted temperature management (TTM). Neurological status was assessed according to the Cerebral Performance Category (CPC) scale.

RESULTS

We included 340 patients. At the first full neurological evaluation, 211 patients (62.1%) achieved good outcome or CPC 1-2. Mean BIS values were significantly higher and median SR lower in patients with CPC 1-2. An average BIS> 26 during first 12 hours of TTM predicted good outcome with 89.5% sensitivity and 75.8% specificity (AUC of 0.869), while average SR values> 24 during the first 12 hours of TTM predicted poor outcome (CPC 3-5) with 91.5% sensitivity and 81.8% specificity (AUC, 0.906). Hourly BIS and SR values exhibited good predictive performance (AUC> 0.85), as soon as hour 2 for SR and hour 4 for BIS.

CONCLUSIONS

BIS/SR are associated with patients' potential for neurological recovery after CA. This finding could help to create awareness of the possibility of a better outcome in patients who might otherwise be wrongly considered as nonviable and to establish personalized treatment escalation plans.

Tools Are Needed to Promote Sedation Practices for Mechanically Ventilated Patients

Suboptimal sedation practices continue to be frequent, although the updated guidelines for management of pain, agitation, and delirium in mechanically ventilated (MV) patients have been published for several years. Causes of low adherence to the recommended minimal sedation protocol are multifactorial. However, the barriers to translation of these protocols into standard care for MV patients have yet to be analyzed. In our view, it is necessary to develop fresh insights into the interaction between the patients' responses to nociceptive stimuli and individualized regulation of patients' tolerance when using analgesics and sedatives. By better understanding this interaction, development of novel tools to assess patient pain tolerance and to define and predict oversedation or delirium may promote better sedation practices in the future.

Correlation between bispectral index and prognosis of patients with acute cerebral infarction

INTRODUCTION

This study aimed to investigate the clinical value of bispectral index (BIS) monitoring in assessing the consciousness and prognosis of acute cerebral infarction (ACI) patients.

METHODS

In total, 64 patients who suffered from ACI with consciousness disturbance were enrolled in this study. Glasgow Coma Scale (GCS) was performed to evaluate the consciousness level of ACI patients, and BIS was used to monitor the depth of anesthesia and sedation. Then, patients were divided into good prognosis, poor prognosis and death groups according to modified Rankin score (mRS). Discrimination analysis of BIS values and GCS score for the prediction of prognosis was performed using the receiver operator characteristic (ROC) curve.

RESULTS

GCS score and BIS values showed statistically significant differences among the three groups. Spearman rank correlation analysis revealed a significant positive correlation between BIS values and GCS score, while BIS values was negatively related with mRS. The ROC curve of prognosis prediction showed strong prognostic power, with area under the curves (AUCs) between 0.830 and 0.917. Moreover, the AUC of BISmean score was higher than that of BISmax, BISmin and GCS, and BISmean of 74 was the best cut-off point for good prognosis.

CONCLUSION

BIS directly reflects the degree of consciousness disturbance in ACI patients, and thus accurately predicts the prognosis, indicating potential application values of BIS in clinical practice.

Post-Cardiac Arrest Syndrome

More than 356 000 out-of-hospital cardiac arrests occur in the United States annually. Complications involving post-cardiac arrest syndrome occur because of ischemic-reperfusion injury to the brain, lungs, heart, and kidneys. Post-cardiac arrest syndrome is a clinical state that involves global brain injury, myocardial dysfunction, macrocirculatory dysfunction, increased vulnerability to infection, and persistent precipitating pathology (ie, the cause of the arrest). The severity of outcomes varies and depends on precipitating factors, patient health before cardiac arrest, duration of time to return of spontaneous circulation, and underlying comorbidities. In this article, the pathophysiology and treatment of post-cardiac arrest syndrome are reviewed and potential novel therapies are described.

Resuscitating the Globally Ischemic Brain: TTM and Beyond

Cardiac arrest (CA) afflicts ~ 550,000 people each year in the USA. A small fraction of CA sufferers survive with a majority of these survivors emerging in a comatose state. Many CA survivors suffer devastating global brain injury with some remaining indefinitely in a comatose state. The pathogenesis of global brain injury secondary to CA is complex. Mechanisms of CA-induced brain injury include ischemia, hypoxia, cytotoxicity, inflammation, and ultimately, irreversible neuronal damage. Due to this complexity, it is critical for clinicians to have access as early as possible to quantitative metrics for diagnosing injury severity, accurately predicting outcome, and informing patient care. Current recommendations involve using multiple modalities including clinical exam, electrophysiology, brain imaging, and molecular biomarkers. This multi-faceted approach is designed to improve prognostication to avoid "self-fulfilling" prophecy and early withdrawal of life-sustaining treatments. Incorporation of emerging dynamic monitoring tools such as diffuse optical technologies may provide improved diagnosis and early prognostication to better inform treatment. Currently, targeted temperature management (TTM) is the leading treatment, with the number of patients needed to treat being ~ 6 in order to improve outcome for one patient. Future avenues of treatment, which may potentially be combined with TTM, include pharmacotherapy, perfusion/oxygenation targets, and pre/postconditioning. In this review, we provide a bench to bedside approach to delineate the pathophysiology, prognostication methods, current targeted therapies, and future directions of research surrounding hypoxic-ischemic brain injury (HIBI) secondary to CA.

Data Driven Investigation of Bispectral Index Algorithm

Bispectral index (BIS), a useful marker of anaesthetic depth, is calculated by a statistical multivariate model using nonlinear functions of electroencephalography-based subparameters. However, only a portion of the proprietary algorithm has been identified. We investigated the BIS algorithm using clinical big data and machine learning techniques. Retrospective data from 5,427 patients who underwent BIS monitoring during general anaesthesia were used, of which 80% and 20% were used as training datasets and test datasets, respectively. A histogram of data points was plotted to define five BIS ranges representing the depth of anaesthesia. Decision tree analysis was performed to determine the electroencephalography subparameters and their thresholds for classifying five BIS ranges. Random sample consensus regression analyses were performed using the subparameters to derive multiple linear regression models of BIS calculation in five BIS ranges. The performance of the decision tree and regression models was externally validated with positive predictive value and median absolute error, respectively. A four-level depth decision tree was built with four subparameters such as burst suppression ratio, power of electromyogram, 95% spectral edge frequency, and relative beta ratio. Positive predictive values were 100%, 80%, 80%, 85% and 89% in the order of increasing BIS in the five BIS ranges. The average of median absolute errors of regression models was 4.1 as BIS value. A data driven BIS calculation algorithm using multiple electroencephalography subparameters with different weights depending on BIS ranges has been proposed. The results may help the anaesthesiologists interpret the erroneous BIS values observed during clinical practice.

Management of Comatose Survivors of Cardiac Arrest

PURPOSE OF REVIEW

Because the whole-body ischemia-reperfusion insult associated with cardiac arrest often results in brain injury, neurologists perform an important role in postresuscitation cardiac arrest care. This article provides guidance for the assessment and management of brain injury following cardiac arrest.

RECENT FINDINGS

Neurologists have many roles in postresuscitation cardiac arrest care: (1) early assessment of brain injury severity to help inform triage for invasive circulatory support or revascularization; (2) advocacy for the maintenance of a neuroprotective thermal, hemodynamic, biochemical, and metabolic milieu; (3) detection and management of seizures; (4) development of an accurate, multimodal, and conservative approach to prognostication; (5) application of shared decision-making paradigms around the likely outcomes of therapy and the goals of care; and (6) facilitation of the neurocognitive assessment of survivors. Therefore, optimal management requires early neurologist involvement in patient care, a detailed knowledge of postresuscitation syndrome and its complex interactions with prognosis, expertise in bringing difficult cases to their optimal conclusions, and a support system for survivors with cognitive deficits.

SUMMARY

Neurologists have a critical role in postresuscitation cardiac arrest care and are key participants in the treatment team from the time of first restoration of a perfusing heart rhythm through the establishment of rehabilitation services for survivors.

The maximum value of bispectral index predicts outcome in hypoxic-ischemic encephalopathy after resuscitation, better than minimum or mean value

OBJECTIVE

Although bispectral index (BIS) has been widely used for predicting neurological outcomes in clinical practice, its optimal value concerning maximum (BIS_max), minimum (BIS_min) and mean (BIS_mean) on accurately predicting the prognosis of patients with hypoxic-ischemic encephalopathy (HIE) after resuscitation has not been clearly determined.

METHODS

For a total number of 45 cases, the duration of each BIS measurement was 12 h, with the data collected at a 30 min interval. Outcome was recorded as survival and non-survival count 60 days after the resuscitation. Receiver operator characteristic curve was used to assess the BIS_max, BIS_min and BIS_mean for predicting clinical outcome.

RESULTS

By the end of observation, 20 cases (44.4%) survived with a significantly higher BIS_max. The area under the curve for BIS_max of predicting survival was the highest compared to BIS_min and BIS_mean. The optimal cut-off value of BIS_max was 71.5 with 100% sensitivity and 60% specificity. Ten patients presented BIS value down to zero at any time point did not survive the observation.

CONCLUSION

The BIS_max is a better outcome predictor than BIS_min or BIS_mean for patients with HIE after resuscitation. Lower BIS_max represents higher risk of mortality. Additionally, BIS value decreases to zero represents a poor outcome.

The prognostic value of bispectral index and suppression ratio monitoring after out-of-hospital cardiac arrest: a prospective observational study

Background

We investigated the ability of bispectral index (BIS) monitoring to predict poor neurological outcome in out-of-hospital cardiac arrest (OHCA) patients fully treated according to guidelines.

Results

In this prospective, observational study, 77 successfully resuscitated OHCA patients were enrolled in whom BIS, suppression ratio (SR) and electromyographic (EMG) values were continuously monitored during the first 36 h after the initiation of targeted temperature management at 33 °C. The Cerebral Performance Category (CPC) scale was used to define patients’ outcome at 180 days after OHCA (CPC 1–2: good–CPC 3–5: poor neurological outcome). Using mean BIS and SR values calculated per hour, receiver operator characteristics curves were constructed to determine the optimal time point and threshold to predict poor neurological outcome. At 180 days post-cardiac arrest, 39 patients (51%) had a poor neurological outcome. A mean BIS value ≤ 25 at hour 12 predicted poor neurological outcome with a sensitivity of 49% (95% CI 30–65%), a specificity of 97% (95% CI 85–100%) and false positive rate (FPR) of 6% (95% CI 0–29%) [AUC: 0.722 (0.570–0.875); p = 0.006]. A mean SR value ≥ 3 at hour 23 predicted poor neurological with a sensitivity of 74% (95% CI 56–87%), a specificity of 92% (95% CI 78–98%) and FPR of 11% (95% CI 3–29%) [AUC: 0.836 (0.717–0.955); p < 0.001]. No relationship was found between mean EMG and BIS < 25 (R² = 0.004; p = 0.209).

Conclusion

This study found that mean BIS ≤ 25 at hour 12 and mean SR ≥ 3 at hour 23 might be used to predict poor neurological outcome in an OHCA population with a presumed cardiac cause. Since no correlation was observed between EMG and BIS < 25, our calculated BIS threshold might assist with poor outcome prognostication following OHCA.

Prediction of conscious awareness recovery after severe acute ischemic stroke

BACKGROUND

Ischemic stroke that is sufficiently severe to cause loss of consciousness has a high rate of morbidity and mortality. Many individuals who suffer from these disorders never recover conscious awareness. In this study, we aimed to identify an accurate and simple bedside method to predict awareness recovery after severe acute ischemic stroke.

METHODS

Between 2013 and 2017, all consecutive patients with consciousness disorders after acute ischemic stroke were recruited to the study. The demographic data, Full Outline of UnResponsiveness (FOUR) score, Glasgow Coma Scale (GCS) and Bispectral Index (BIS) were recorded at study entry and each day of Days 3-8 during the stroke period. We followed patients for 90days to assess whether the subjects recovered conscious awareness. Logistic regression and receiver operating characteristic (ROC) curve analyses were used to evaluate the predictors' abilities for outcome prognosis.

RESULTS

We assessed a total of 102 patients. 23 (23%) patients died without awareness recovery, whereas 61 (60%) patients regained conscious awareness. The earliest time with the greatest ability to predict conscious awareness recovery occurred at Day 3 after stroke, and the area under the ROC curve (AUC) of the multivariate model was 0.948 (95% confidence interval (CI) 0.885 to 0.982). Age, BIS, motor response and brainstem responses were independent predictors for conscious awareness recovery. We subsequently created a 20-point score termed "ABMB" based on their coefficients in the Day 3 model. The AUC of ABMB at Day 3 was 0.931 (95% CI 0.882 to 0.980). The ABMB also showed good predictive ability at Days 4 and 5.

CONCLUSIONS

The ABMB score accurately identified patients who will recover conscious awareness within 90days after acute severe ischemic stroke and thus provides a useful outcome message for clinicians and relatives.

Derivation and Validation of the CREST Model for Very Early Prediction of Circulatory Etiology Death in Patients Without ST-Segment-Elevation Myocardial Infarction After Cardiac Arrest

BACKGROUND

No practical tool quantitates the risk of circulatory-etiology death (CED) immediately after successful cardiopulmonary resuscitation in patients without ST-segment-elevation myocardial infarction. We developed and validated a prediction model to rapidly determine that risk and facilitate triage to individualized treatment pathways.

METHODS

With the use of INTCAR (International Cardiac Arrest Registry), an 87-question data set representing 44 centers in the United States and Europe, patients were classified as having had CED or a combined end point of neurological-etiology death or survival. Demographics and clinical factors were modeled in a derivation cohort, and backward stepwise logistic regression was used to identify factors independently associated with CED. We demonstrated model performance using area under the curve and the Hosmer-Lemeshow test in the derivation and validation cohorts, and assigned a simplified point-scoring system.

RESULTS

Among 638 patients in the derivation cohort, 121 (18.9%) had CED. The final model included preexisting coronary artery disease (odds ratio [OR], 2.86; confidence interval [CI], 1.83-4.49; P≤0.001), nonshockable rhythm (OR, 1.75; CI, 1.10-2.77; P=0.017), initial ejection fraction<30% (OR, 2.11; CI, 1.32-3.37; P=0.002), shock at presentation (OR, 2.27; CI, 1.42-3.62; P<0.001), and ischemic time >25 minutes (OR, 1.42; CI, 0.90-2.23; P=0.13). The derivation model area under the curve was 0.73, and Hosmer-Lemeshow test P=0.47. Outcomes were similar in the 318-patient validation cohort (area under the curve 0.68, Hosmer-Lemeshow test P=0.41). When assigned a point for each associated factor in the derivation model, the average predicted versus observed probability of CED with a CREST score (coronary artery disease, initial heart rhythm, low ejection fraction, shock at the time of admission, and ischemic time >25 minutes) of 0 to 5 was: 7.1% versus 10.2%, 9.5% versus 11%, 22.5% versus 19.6%, 32.4% versus 29.6%, 38.5% versus 30%, and 55.7% versus 50%.

CONCLUSIONS

The CREST model stratified patients immediately after resuscitation according to risk of a circulatory-etiology death. The tool may allow for estimation of circulatory risk and improve the triage of survivors of cardiac arrest without ST-segment-elevation myocardial infarction at the point of care.

Early detection of brain death using the Bispectral Index (BIS) in patients treated by extracorporeal cardiopulmonary resuscitation (E-CPR) for refractory cardiac arrest

BACKGROUND

Despite increasing use of extracorporeal cardiopulmonary resuscitation (E-CPR) for treatment of refractory cardiac arrest patients, prognosis remains dismal, often resulting in brain-death. However, clinical assessment of brain-death occurence is difficult in post-cardiac arrest patients, sedated, paralyzed, under mild therapeutic hypothermia (MTH). Our objective was to assess the usefulness of Bispectral-Index (BIS) monitoring at bedside for an early detection of brain-death occurrence in refractory cardiac arrest patients treated by E-CPR.

METHODS

This prospective study was performed in an intensive care unit of an university hospital. Forty-six patients suffering from refractory cardiac arrest treated by E-CPR were included. BIS was continuously recorded during ICU hospitalization. Clinical brain-death was confirmed when appropriate by EEG and/or cerebral CT angiography.

RESULTS

Twenty-nine patients evolved into brain-death and had average BIS values under MTH and after rewarming (temperature ≥35°C) of 4 (0-47) and 0 (0-82), respectively. Among these, 11 (38%) entered into a procedure of organs donation. Among the 17 non-brain-dead patients, the average BIS values at admission and after rewarming were 39 (0-65) and 59 (22-82), respectively. Two patients had on admission a BIS value equal to zero and evolved to a poor prognostic (CPC 4) and died after care limitations. BIS values were significantly different between patients who developed brain death and those who did not. In both groups, no differences were observed between the AUCs of ROC curves for BIS values under MTH and after rewarming (respectively 0.86 vs 0.83, NS).

CONCLUSIONS

Initial values of BIS could be used as an assessment tool for early detection of brain-death in refractory cardiac arrest patients treated by mild therapeutic hypothermia and E-CPR.

Recorded time periods of bispectral index values equal to zero predict neurological outcome after out-of-hospital cardiac arrest

Background

Prognostication in out-of-hospital cardiac arrest (OHCA) survivors is often difficult. Recent studies have shown the predictive ability of bispectral index (BIS) monitoring to assist with early neuroprognostication. The aim of this study was to investigate whether characteristics of BIS values equal to zero (BIS 0) (i.e. duration and/or uni- versus bilateral presence) instead of simply their occurrence are better indicators for poor neurological outcome after OHCA by aiming at a specificity of 100%.

Methods

Between 2011 and 2015, all successfully resuscitated OHCA patients were treated with targeted temperature management (TTM) at 33 °C for 24 hours followed by rewarming over 12 hours (0.3 °C/h). In total, BIS values were registered in 77 OHCA patients. The occurrence of unilateral (BIS 0 at one hemisphere) and bilateral (BIS 0 at both hemispheres) BIS 0 values as well as their total duration were calculated. Receiver operating characteristic (ROC) curves were constructed using the total duration with BIS 0 values calculated from the initiation of TTM onwards to determine poor neurological outcome.

Results

In 30 of 77 OHCA patients (39%), at least one BIS 0 value occurred during the first 48 hours after admission. Of these 30 patients, six (20%) had a good (cerebral performance category (CPC) 1–2) and 24 (80%) a poor neurological outcome (CPC3–5) at 180 days post-CA. Within these 30 patients, the incidence of bilateral BIS 0 values was higher in patients with poor neurological outcome (CPC1–2: 2 (33%) vs. CPC3–5: 19 (79%); p = 0.028). The presence of a BIS 0 value predicted poor neurological outcome with a sensitivity of 62% and specificity of 84% (AUC: 0.729; p = 0.001). With a ROC analysis, a total duration of 30,3 minutes with BIS 0 values calculated over the first 48 hours predicted poor neurological outcome with a sensitivity of 63% and specificity of 100% (AUC: 0.861; p = 0.007).

Conclusions

This study shows that a prolonged duration with (bilateral) BIS 0 values serves as a better outcome predictor after OHCA as compared to a single observation.

Increasing or fluctuating bispectral index values during post-resuscitation targeted temperature management can predict clinical seizures after rewarming

AIM

To investigate whether an increasing bispectral index (BIS) value during targeted temperature management (TTM) correlates with increased clinical seizures after TTM or worse neurological prognoses after TTM.

METHODS

We performed a retrospective prognostication study of patients who were treated with TTM after recovery of spontaneous circulation from cardiac arrest at a tertiary care hospital. We recorded the BIS regularly during TTM and calculated the correlations of the mean BIS values, standard deviations of the BIS values, and linear regression coefficient of the trend of the BIS values over time as index tests. Study outcomes included the occurrence of clinical seizures after TTM and unfavourable neurological outcomes (defined as a Cerebral Performance Scale score of 3-5). Receiver operating characteristics (ROC) analyses evaluated the predictability of the index tests for the study outcomes.

RESULTS

Of 534 patients with post-cardiac arrest who were admitted to the intensive care unit, 103 were enrolled in this study. Thirty-one patients (30.1%) experienced sequelae in the form of clinical seizures, and 52 (50.5%) had unfavourable neurological outcomes at 30days post-resuscitation. The standard deviation (area under the ROC curve [AUC]=0.763) and the regression coefficient (AUC=0.763) had higher predictability of clinical seizures than the mean BIS value (AUC=0.657); in contrast, the low mean BIS value best predicted unfavourable neurological outcomes (AUC=0.861) compared to the standard deviation (AUC=0.532) and regression coefficient (AUC=0.501).

CONCLUSION

An increase of, or greater fluctuation in, BIS during hypothermia may predict clinical seizures after TTM.

Analgesia, sedation, and neuromuscular blockade during targeted temperature management after cardiac arrest

The approach to sedation, analgesia, and neuromuscular blockade during targeted temperature management (TTM) remains largely unstudied, forcing clinicians to adapt previous research from other patient environments. During TTM, very little data guide drug selection, doses, and specific therapeutic goals. Sedation should be deep enough to prevent awareness during neuromuscular blockade, but titration is complex as metabolism and clearance are delayed for almost all drugs during hypothermia. Deeper sedation is associated with prolonged intensive care unit (ICU) and ventilator therapy, increased delirium and infection, and delayed wakening which can confound early critical neurological assessments, potentially resulting in erroneous prognostication and inappropriate withdrawal of life support. We review the potential therapeutic goals for sedation, analgesia, and neuromuscular blockade during TTM; the adverse events associated with that treatment; data suggesting that TTM and organ dysfunction impair drug metabolism; and controversies and potential benefits of specific monitoring. We also highlight the areas needing better research to guide our therapy.

Is bispectral index (BIS) monitoring in the emergency department helpful for prognostication during resuscitation of cardiac arrest patients?

Objective:

It has been suggested that bispectral index (BIS) can be indicative of cerebral perfusion during advanced cardiac life support (ACLS) resuscitation of cardiac arrest patients. Our aim was to determine whether BIS monitoring during resuscitation in the emergency department (ED) can predict survival or neurological outcomes of patients with cardiac arrest.

Methods:

This was a prospective, single-centre, observational cohort study in the ED of a tertiary hospital, where we included 100 patients whom received resuscitation in the ED between December 2010 and March 2014. We recorded BIS values, suppression ratio, electromyography and signal quality index; throughout the resuscitation. A research coordinator set up the monitoring apparatus at the earliest time possible.

Results:

Out of the 100 patients recruited, 22 had a sustained return of spontaneous circulation (ROSC) and were admitted to the intensive care unit (ICU). Of these, 19 patients subsequently died in the ICU, two were discharged with good neurological recovery (cerebral performance category (CPC) 1) and one was discharged with poor neurological recovery (CPC4). By comparing the groups of patients who died in the ICU and were discharged, we found there was no significant difference in the initial BIS score ( p = 0.64), the score upon ROSC ( p = 0.36), the average BIS score 10 minutes post-ROSC ( p = 0.35), nor the BIS score upon admission to the ICU ( p = 0.22).

Conclusions:

Very early monitoring of BIS before admission to the ICU predicts neither survival nor neurological recovery in patients with cardiac arrest. Very low BIS scores in the ED may not indicate a poor prognosis, especially in patients undergoing therapeutic hypothermia.

Medical management of epileptic seizures: challenges and solutions

Epilepsy is one of the most common neurologic illnesses. This condition afflicts 2.9 million adults and children in the US, leading to an economic impact amounting to $15.5 billion. Despite the significant burden epilepsy places on the population, it is not very well understood. As this understanding continues to evolve, it is important for clinicians to stay up to date with the latest advances to provide the best care for patients. In the last 20 years, the US Food and Drug Administration has approved 15 new antiepileptic drugs (AEDs), with many more currently in development. Other advances have been achieved in terms of diagnostic modalities like electroencephalography technology, treatment devices like vagal nerve and deep-brain stimulators, novel alternate routes of drug administration, and improvement in surgical techniques. Specific patient populations, such as the pregnant, elderly, those with HIV/AIDS, and those with psychiatric illness, present their own unique challenges, with AED side effects, drug interactions, and medical-psychiatric comorbidities adding to the conundrum. The purpose of this article is to review the latest literature guiding the management of acute epileptic seizures, focusing on the current challenges across different practice settings, and it discusses studies in various patient populations, including the pregnant, geriatric, those with HIV/AIDS, comatose, psychiatric, and "pseudoseizure" patients, and offers possible evidence-based solutions or the expert opinion of the authors. Also included is information on newer AEDs, routes of administration, and significant AED-related drug-interaction tables. This review has tried to address only some of these issues that any practitioner who deals with the acute management of seizures may encounter. The document also highlights the numerous avenues for new research that would help practitioners optimize epilepsy management.