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161 Emergency Department Patient Perception of Stroke
Research Forum Abstracts Conclusion: Analysis revealed that a qEEG discriminant score for prediction of positive head CT was weakly correlated with post-concussion syndrome at 7 and 45 days.
161
Emergency Department Patient Perception of Stroke
Benaron D, Castillo E, Vilke G, Guluma K/University of California, San Diego, La Jolla, CA; University of California, San Diego, La Jolla, CA
160
Utility of Hand-held EEG Device in Predicting Postconcussion Syndrome in Patients With Closed Head Injury
Mika V, Ayaz SI, Robinson D, Medado P, Pearson C, Millis S, O’Neil B/Wayne State University, Detroit, MI
Background: In the year 2000, loss of productivity and direct medical costs from traumatic brain injury (TBI) totaled $60 billion in the United States. From 2002 to 2006, an increase of 14.4% in TBI-related emergency department visits resulted in an increase of the direct and indirect cost of TBI. According to the CDC, 80% of TBI patients are treated and discharged from the ED. The number of patients that continue to have symptoms after ED discharge is difficult to estimate. Patients who have persistent symptoms after suffering from a mild traumatic brain injury (mTBI) or concussion are said to suffer from post-concussion syndrome. The patients who are destined for post-concussion syndrome are difficult to identify in the ED as there are no good predictive instruments. Study Objective: The objective of this study is to determine the ability of a handheld EEG acquisition device to predict post-concussion syndrome after a closed head injury. Methods: A total of 74 patients presenting to the ED after closed head trauma between the ages of 18 and 80, and a GCS score of 9-15, with a negative head CT were enrolled in this prospective cohort study at 2 academic emergency departments. An 8 Lead EEG was obtained and a quantitative electroencephalography (qEEG) discriminant score previously validated for acute CT pathology was tested for prediction of post-concussion syndrome. Post-concussion syndrome was defined as a score of greater than 12 on the Concussion Symptom Inventory at 7 and/or 45 day follow up. Logistic regression was used to classify and predict post-concussion syndrome against the qEEG discriminant score of the device. Results: Of the 74 negative head CT patients included in the study, 44% of patients with post-concussion syndrome (CSI ⬎12) were identified correctly at 1 week and 32% of patients with post-concussion syndrome were identified correctly at 45 days by this qEEG discriminant score. Discussion: The previously defined abnormality index cut off of 65 based on a ROC curve analysis of earlier data was a poor discriminator of post-concussion syndrome. Additionally, multiple clinical evaluations and neuropsych testing have been performed on these patients with post-concussion syndrome and all have poor predictive value. Since post-concussive syndrome involves neuronal dysfunction without CT findings of intracranial injury, a hand-held qEEG device with a real time algorithm has theoretic potential as a clinically useful predictor. A larger study would allow identification of a more precise cut off for this syndrome.
S58 Annals of Emergency Medicine
Background: Stroke is one of the top ten leading causes of disability in the United States. Much of the disability associated with stroke can be prevented by adequate treatment with t-PA within 3 hours of initial stroke symptoms but only a small percentage of patients are eligible to receive therapy, largely due to a delayed presentation for care. Study Objectives: The goal of this project is to gain a better understanding of the factors potentially influencing a patient’s decision to pursue timely care for acute stroke symptoms. Methods: We conducted a prospective, multi-center cross sectional survey of English-speaking patients presenting to 2 EDs with a combined census of 62,000. One hospital is an urban, academic teaching hospital (Level 1 trauma center) with an annual census of approximately 38,000 visits. The other hospital is a suburban community hospital with an annual census of approximately 24,000 visits. Participants were presented with second-person vignettes of a patient experiencing stroke. The vignettes alter timing (time of day, day of week) of the stroke, the nature of stroke symptoms and geographical location (home, public, work) of the stroke. The study subjects are then asked to rank choices, A) calling 911 wait a couple of hours and get a ride to the ED if the symptoms do not improve, B) having someone drive them to an ED immediately, C) going to a community clinic, D) calling 911, E) going to a primary care doctor the next day, or F) calling a health care hotline for advice. Additional questions include: 1) demographic data (age, sex, income, race/ ethnicity and education level), 2) past and current medical conditions, and 3) knowledge of stroke symptoms. Informed consent and data collection was, and continues to be, collected by trained research associates. Means and frequencies were used to describe participants. Results: Thus far 241 surveys have been completed. When provided a list of typical stroke symptoms, the percentages of participants identifying dizziness, severe headache, problems with vision, slurred speech, weakness and numbness as a stroke symptom were 82%, 79%, 80%, 93%, 97% and 94% respectively. Preliminary data is showing that, depending on the vignette, an overwhelming majority (73%-90%) of patients chose to dial 911 as either their most likely, or second most likely responses when faced with stroke. The same trend was found when patient were grouped by sex and race. Conclusion: Regardless of time, place or stroke symptoms, patients overwhelmingly decide to dial 911 immediately when faced with stroke. This highlights the fact that a majority of patients do recognize common stroke symptoms, and are likely to appropriately access emergent treatment when these symptoms arise.
162
Can Quantitative Brain Electrical Activity Aid in the Triage of Mild Traumatic Brain Injured Patients?
Ayaz SI, Parsons D, Robinson D, Medado P, O’Neil B/Wayne State University, Detroit, MI
Background: The incidence of US emergency department (ED) visits for traumatic brain injury (TBI) exceeds 1,000,000 cases per year, with the vast majority classified as mild (mTBI). Current decision rules, such as the New Orleans Criteria (NOC) is utilized as a decision tool before these patients get a head computed tomography (CT) scan. Approximately 70% of these patients have a negative CT scan. Study Objective: To evaluate the use of quantified brain electrical activity in the initial triage of ED mTBI patients as compared to the NOC. Methods: 88 patients between the ages of 18 to 80, who reported to the ED with head trauma and received head CT, were included in the study. Utilizing a hand-held device for EEG acquisition and analysis, data was collected from frontal leads. Algorithmic analysis of brain electrical activity was stored and processed off-line to generate a discriminant score. Only a discriminant score of 17 or above was included in the study because it was considered to have high probability in predicting head CT positive in this population. This discriminant was derived from a selected subset of qEEG features which are extracted from the artifact-free EEG and entered into the algorithm. The threshold was computed from the ROC curve for the performance of
Volume , . : October
161
Emergency Department Patient Perception of Stroke
Benaron D, Castillo E, Vilke G, Guluma K/University of California, San Diego, La Jolla, CA; University of California, San Diego, La Jolla, CA
160
Utility of Hand-held EEG Device in Predicting Postconcussion Syndrome in Patients With Closed Head Injury
Mika V, Ayaz SI, Robinson D, Medado P, Pearson C, Millis S, O’Neil B/Wayne State University, Detroit, MI
Background: In the year 2000, loss of productivity and direct medical costs from traumatic brain injury (TBI) totaled $60 billion in the United States. From 2002 to 2006, an increase of 14.4% in TBI-related emergency department visits resulted in an increase of the direct and indirect cost of TBI. According to the CDC, 80% of TBI patients are treated and discharged from the ED. The number of patients that continue to have symptoms after ED discharge is difficult to estimate. Patients who have persistent symptoms after suffering from a mild traumatic brain injury (mTBI) or concussion are said to suffer from post-concussion syndrome. The patients who are destined for post-concussion syndrome are difficult to identify in the ED as there are no good predictive instruments. Study Objective: The objective of this study is to determine the ability of a handheld EEG acquisition device to predict post-concussion syndrome after a closed head injury. Methods: A total of 74 patients presenting to the ED after closed head trauma between the ages of 18 and 80, and a GCS score of 9-15, with a negative head CT were enrolled in this prospective cohort study at 2 academic emergency departments. An 8 Lead EEG was obtained and a quantitative electroencephalography (qEEG) discriminant score previously validated for acute CT pathology was tested for prediction of post-concussion syndrome. Post-concussion syndrome was defined as a score of greater than 12 on the Concussion Symptom Inventory at 7 and/or 45 day follow up. Logistic regression was used to classify and predict post-concussion syndrome against the qEEG discriminant score of the device. Results: Of the 74 negative head CT patients included in the study, 44% of patients with post-concussion syndrome (CSI ⬎12) were identified correctly at 1 week and 32% of patients with post-concussion syndrome were identified correctly at 45 days by this qEEG discriminant score. Discussion: The previously defined abnormality index cut off of 65 based on a ROC curve analysis of earlier data was a poor discriminator of post-concussion syndrome. Additionally, multiple clinical evaluations and neuropsych testing have been performed on these patients with post-concussion syndrome and all have poor predictive value. Since post-concussive syndrome involves neuronal dysfunction without CT findings of intracranial injury, a hand-held qEEG device with a real time algorithm has theoretic potential as a clinically useful predictor. A larger study would allow identification of a more precise cut off for this syndrome.
S58 Annals of Emergency Medicine
Background: Stroke is one of the top ten leading causes of disability in the United States. Much of the disability associated with stroke can be prevented by adequate treatment with t-PA within 3 hours of initial stroke symptoms but only a small percentage of patients are eligible to receive therapy, largely due to a delayed presentation for care. Study Objectives: The goal of this project is to gain a better understanding of the factors potentially influencing a patient’s decision to pursue timely care for acute stroke symptoms. Methods: We conducted a prospective, multi-center cross sectional survey of English-speaking patients presenting to 2 EDs with a combined census of 62,000. One hospital is an urban, academic teaching hospital (Level 1 trauma center) with an annual census of approximately 38,000 visits. The other hospital is a suburban community hospital with an annual census of approximately 24,000 visits. Participants were presented with second-person vignettes of a patient experiencing stroke. The vignettes alter timing (time of day, day of week) of the stroke, the nature of stroke symptoms and geographical location (home, public, work) of the stroke. The study subjects are then asked to rank choices, A) calling 911 wait a couple of hours and get a ride to the ED if the symptoms do not improve, B) having someone drive them to an ED immediately, C) going to a community clinic, D) calling 911, E) going to a primary care doctor the next day, or F) calling a health care hotline for advice. Additional questions include: 1) demographic data (age, sex, income, race/ ethnicity and education level), 2) past and current medical conditions, and 3) knowledge of stroke symptoms. Informed consent and data collection was, and continues to be, collected by trained research associates. Means and frequencies were used to describe participants. Results: Thus far 241 surveys have been completed. When provided a list of typical stroke symptoms, the percentages of participants identifying dizziness, severe headache, problems with vision, slurred speech, weakness and numbness as a stroke symptom were 82%, 79%, 80%, 93%, 97% and 94% respectively. Preliminary data is showing that, depending on the vignette, an overwhelming majority (73%-90%) of patients chose to dial 911 as either their most likely, or second most likely responses when faced with stroke. The same trend was found when patient were grouped by sex and race. Conclusion: Regardless of time, place or stroke symptoms, patients overwhelmingly decide to dial 911 immediately when faced with stroke. This highlights the fact that a majority of patients do recognize common stroke symptoms, and are likely to appropriately access emergent treatment when these symptoms arise.
162
Can Quantitative Brain Electrical Activity Aid in the Triage of Mild Traumatic Brain Injured Patients?
Ayaz SI, Parsons D, Robinson D, Medado P, O’Neil B/Wayne State University, Detroit, MI
Background: The incidence of US emergency department (ED) visits for traumatic brain injury (TBI) exceeds 1,000,000 cases per year, with the vast majority classified as mild (mTBI). Current decision rules, such as the New Orleans Criteria (NOC) is utilized as a decision tool before these patients get a head computed tomography (CT) scan. Approximately 70% of these patients have a negative CT scan. Study Objective: To evaluate the use of quantified brain electrical activity in the initial triage of ED mTBI patients as compared to the NOC. Methods: 88 patients between the ages of 18 to 80, who reported to the ED with head trauma and received head CT, were included in the study. Utilizing a hand-held device for EEG acquisition and analysis, data was collected from frontal leads. Algorithmic analysis of brain electrical activity was stored and processed off-line to generate a discriminant score. Only a discriminant score of 17 or above was included in the study because it was considered to have high probability in predicting head CT positive in this population. This discriminant was derived from a selected subset of qEEG features which are extracted from the artifact-free EEG and entered into the algorithm. The threshold was computed from the ROC curve for the performance of
Volume , . : October