Andrew W. Asimos

Addition of Brain Infarction to the ABCD2 Score (ABCD2I) A Collaborative Analysis of Unpublished Data on 4574 Patients

Background and Purpose— The ABCD system was developed to predict early stroke risk after transient ischemic attack. Incorporation of brain imaging findings has been suggested, but reports have used inconsistent methods and been underpowered. We therefore performed an international, multicenter collaborative study of the prognostic performance of the ABCD2 score and brain infarction on imaging to determine the optimal weighting of infarction in the score (ABCD2I). Methods— Twelve centers provided unpublished data on ABCD2 scores, presence of brain infarction on either diffusion-weighted imaging or CT, and follow-up in cohorts of patients with transient ischemic attack diagnosed by World Health Organization criteria. Optimal weighting of infarction in the ABCD2I score was determined using area under the receiver operating characteristic curve analyses and random effects meta-analysis. Results— Among 4574 patients with TIA, acute infarction was present in 884 (27.6%) of 3206 imaged with diffusion-weighted imaging and new or old infarction was present in 327 (23.9%) of 1368 imaged with CT. ABCD2 score and presence of infarction on diffusion-weighted imaging or CT were both independently predictive of stroke (n=145) at 7 days (after adjustment for ABCD2 score, OR for infarction=6.2, 95% CI=4.2 to 9.0, overall; 14.9, 7.4 to 30.2, for diffusion-weighted imaging; 4.2, 2.6 to 6.9, for CT; all P<0.001). Incorporation of infarction in the ABCD2I score improved predictive power with an optimal weighting of 3 points for infarction on CT or diffusion-weighted imaging. Pooled areas under the curve increased from 0.66 (0.53 to 0.78) for the ABCD2 score to 0.78 (0.72 to 0.85) for the ABCD2I score. Conclusions— In secondary care, incorporation of brain infarction into the ABCD system (ABCD2I score) improves prediction of stroke in the acute phase after transient ischemic attack.

A Multicenter Evaluation of the ABCD2 Score's Accuracy for Predicting Early Ischemic Stroke in Admitted Patients With Transient Ischemic Attack

STUDY OBJECTIVE We evaluate, in admitted patients with transient ischemic attack, the accuracy of the ABCD(2) (age [A], blood pressure [B], clinical features [weakness/speech disturbance] [C], transient ischemic attack duration [D], and diabetes history [D]) score in predicting ischemic stroke within 7 days. METHODS At 16 North Carolina hospitals, we enrolled a prospective, nonconsecutive sample of admitted patients with transient ischemic attack and with no stroke history, presenting within 24 hours of transient ischemic attack symptom onset. We conducted a medical record review to determine ischemic stroke outcomes within 7 days. According to a modified Rankin Scale Score, strokes were classified as disabling (>2) or nondisabling (< or =2). RESULTS During a 35-month period, we enrolled 1,667 patients, of whom 373 (23%) received a diagnosis of an ischemic stroke within 7 days. Eighteen percent (69/373) of all strokes were disabling. We were unable to calculate an ABCD(2) score in 613 patients (37%); however, our imputed analysis indicated this did not significantly alter results. The discriminatory power of the ABCD(2) score was modest for ischemic stroke in 7 days (c statistic 0.59), and fair for disabling ischemic stroke within 7 days (c statistic 0.71). Patients characterized as low risk according to ABCD(2) score (< or =3) were at low risk for experiencing a disabling stroke within 7 days, with a negative likelihood ratio of 0.16 (95% confidence interval [CI] 0.04 to 0.64) with missing values excluded and 0.34 (95% CI 0.15 to 0.76) when missing values were imputed. CONCLUSION Our analysis suggests the best application of the ABCD(2) score may be to identify patients at low risk for an early disabling ischemic stroke. Further study of the ability to determine an ABCD(2) score in all patients is needed, along with validation in a large, consecutive population of patients with transient ischemic attack.

Early Diffusion Weighted MRI as a Negative Predictor for Disabling Stroke After ABCD2 Score Risk Categorization in Transient Ischemic Attack Patients

Background and Purpose— The prognostic value early diffusion-weighted magnetic resonance imaging (DWMRI) adds in the setting of transient ischemic attack (TIA), after risk stratification by a clinical score, is unclear. The purpose of this study is to evaluate, after ABCD2 score risk categorization in admitted TIA patients, whether negative DWMRI performed within 24 hours of symptom onset improves on the identification of patients at low risk for experiencing a disabling stroke within 90 days. Methods— At 15 North Carolina hospitals, we enrolled a prospective nonconsecutive sample of admitted TIA patients. We excluded patients not undergoing a DWMRI within 24 hours of admission and patients for whom a dichotomized (≤ or >3) ABCD2 score could not be calculated. We conducted a medical record review to determine disabling ischemic stroke outcomes within 90 days. Results— Over 35 months, 944 TIA patients met inclusion criteria, of whom 4% (n=41) had a disabling ischemic stroke within 90 days. In analyses stratified by low versus moderate/high ABCD2 score, the combination of a low risk ABCD2 score and a negative early DWMRI had excellent sensitivity (100%, 95% CI 34 to 100) for identifying low-risk patients. In patients classified as moderate to high risk, a negative early DWMRI predicted a low risk of disabling ischemic stroke within 90 days (sensitivity 92%, 95% CI 80 to 97; NLR 0.11, 95% CI 0.04 to 0.32). Conclusions— After risk stratification by the ABCD2 score, early DWMRI enhances the prediction of a low risk for disabling ischemic stroke within 90 days. Further study is warranted in a large, consecutive TIA population of early DWMRI as a sensitive negative predictor for disabling stroke within 90 days.

Out-of-Hospital Stroke Screen Accuracy in a State With an Emergency Medical Services Protocol for Routing Patients to Acute Stroke Centers

STUDY OBJECTIVE Emergency medical services (EMS) protocols, which route patients with suspected stroke to stroke centers, rely on the use of accurate stroke screening criteria. Our goal is to conduct a statewide EMS agency evaluation of the accuracies of the Cincinnati Prehospital Stroke Scale (CPSS) and the Los Angeles Prehospital Stroke Screen (LAPSS) for identifying acute stroke patients. METHODS We conducted a retrospective study in North Carolina by linking a statewide EMS database to a hospital database, using validated deterministic matching. We compared EMS CPSS or LAPSS results (positive or negative) to the emergency department diagnosis International Classification of Diseases, Ninth Revision codes. We calculated sensitivity, specificity, and positive and negative likelihood ratios for the EMS diagnosis of stroke, using each screening tool. RESULTS We included 1,217 CPSS patients and 1,225 LAPSS patients evaluated by 117 EMS agencies from 94 North Carolina counties. Most EMS agencies contributing data had high annual patient volumes and were governmental agencies with nonvolunteer, emergency medical technician-paramedic service level providers. The CPSS had a sensitivity of 80% (95% confidence interval [CI] 77% to 83%) versus 74% (95% CI 71% to 77%) for the LAPSS. Each had a specificity of 48% (CPSS 95% CI 44% to 52%; LAPSS 95% CI 43% to 53%). CONCLUSION The CPSS and LAPSS had similar test characteristics, with each having only limited specificity. Development of stroke screening scales that optimize both sensitivity and specificity is required if these are to be used to determine transport diversion to acute stroke centers.

A link to improve stroke patient care: a successful linkage between a statewide emergency medical services data system and a stroke registry.

OBJECTIVES regionalization of stroke care, including diversion to stroke centers, requires that emergency medical services (EMS) systems accurately identify acute stroke patients. A barrier to evaluating and improving EMS stroke patient identification is the inability to link EMS data with hospital data for individual patients. We sought to create and validate a linkage of the North Carolina EMS Data System (NC-EMS-DS) with data contained in the North Carolina Stroke Care Collaborative (NCSCC) Registry. METHODS all NCSCC Registry patients arriving to one of three hospitals by EMS in a 6-month period were matched against NC-EMS-DS. Records were deterministically matched on receiving hospital, hospital arrival date/time, age, and sex. We performed linkage validation by providing each site investigator with a stroke patient list derived from North Carolina Stroke Care Collaborative Registry (NC-EMS-DS), matched by individual patient to deidentified data in the NCSCCR. Each site investigator determined the set of true matches by comparing the matched list to a NCSCCR patient identifier key maintained at each site. Incorrect matches were reviewed by the research team to identify methods for future improvement in the matching logic. RESULTS for the three validation hospitals, 753 NCSCC Registry patients arrived by EMS. For these patients, 473 (63%) matches to local EMS records were identified, and 421 (89%) of the matches were verified using full patient identifiers. Most match verification failures were due to incorrect date/time stamp and inability to find a corresponding EMS record. CONCLUSIONS linking EMS records electronically to a stroke registry is feasible and leads to a large number of valid matches. This small validation is limited by EMS data quality. Matching may improve with better EMS documentation and standardized facility documentation.

A geographic information system analysis of the impact of a statewide acute stroke emergency medical services routing protocol on community hospital bypass.

BACKGROUND Our goal was to determine if a statewide Emergency Medical Services (EMSs) Stroke Triage and Destination Plan (STDP), specifying bypass of hospitals unable to routinely treat stroke patients with thrombolytics (community hospitals), changed bypass frequency of those hospitals. METHODS Using a statewide EMS database, we identified stroke patients eligible for community hospital bypass and compared bypass frequency 1-year before and after STDP implementation. RESULTS Symptom onset time was missing for 48% of pre-STDP (n = 2385) and 29% of post-STDP (n = 1612) cases. Of the remaining cases with geocodable scene addresses, 58% (1301) in the pre-STDP group and 61% (2,078) in the post-STDP group were ineligible for bypass, because a community hospital was not the closest hospital to the stroke event location. Because of missing data records for some EMS agencies in 1 or both study periods, we included EMS agencies from only 49 of 100 North Carolina counties in our analysis. Additionally, we found conflicting hospital classifications by different EMS agencies for 35% of all hospitals (n = 38 of 108). Given these limitations, we found similar community hospital bypass rates before and after STDP implementation (64%, n = 332 of 520 vs. 63%, n = 345 of 552; P = .65). CONCLUSIONS Missing symptom duration time and data records in our states EMS data system, along with conflicting hospital classifications between EMS agencies limit the ability to study statewide stroke routing protocols. Bypass policies may apply to a minority of patients because a community hospital is not the closest hospital to most stroke events. Given these limitations, we found no difference in community hospital bypass rates after implementation of the STDP.

The First-Time Seizure Emergency Department Electroencephalogram Study

Study objective Seizures account for 1.2% of all emergency department (ED) visits, with 24% of those representing first‐time seizures. Our primary goal is to determine whether obtaining an electroencephalogram (EEG) in the ED after a first‐time seizure can identify individuals appropriate for initiation of anticonvulsant therapy on ED discharge. Our secondary goals are to determine the association of historical and clinical seizure features with epileptic EEGs and to determine the interobserver agreement for the EEG interpretation. Methods We conducted a prospective study including patients older than 17 years with either a first‐time seizure or previous seizures without a previous EEG, all of whom were candidates for discharge home from the ED without antiepileptic drug treatment. We based seizure diagnosis on provider impression. We excluded patients with laboratory studies or neuroimaging deemed to be the seizure cause. EEG technicians performed a 30‐minute EEG in the ED, which was immediately remotely interpreted by an epileptologist, who made a recommendation on antiepileptic drug initiation. We categorized EEGs as normal, abnormal but not epileptic, or epileptic. In accordance with duplicate EEG interpretation by a second, blinded epileptologist, we calculated interrater agreement for EEG interpretation and antiepileptic drug initiation. As a secondary analysis, according to questionnaires completed by patients and seizure observers, we explored the association of aura, focal symptoms, provocation, or historical risk factors with epilepsy. Results We enrolled 73 patients, 71 of whom had an EEG performed. All EEGs were performed within 11 hours of seizure, with an average of 3.85 hours. Twenty‐four percent of patients (95% confidence interval 15% to 36%) received a diagnosis of epilepsy, and all began receiving antiepileptic drug therapy from the ED. Our final study sample size afforded only an exploratory analysis about an association between aura, focal onset, provocation, or historical risk factors with an epilepsy diagnosis. Weighted &kgr; agreement for EEG interpretation was 0.69 (95% confidence interval 0.55 to 0.82). Of the 34 patients who followed up with an epileptologist, 9 had received a diagnosis of epilepsy in the ED, and none had antiepileptic drug medication stopped at initial follow‐up. Conclusion ED EEG performance in adults with first‐time seizures results in a substantial yield of an epilepsy diagnosis and immediate initiation of antiepileptic drug treatment. A larger study is required to determine whether historical and clinical seizure features are associated with an ED epilepsy diagnosis.

PLUMBER Study (Prevalence of Large Vessel Occlusion Strokes in Mecklenburg County Emergency Response)

Background and Purpose— The recently proposed American Heart Association/American Stroke Association EMS triage algorithm endorses routing patients with suspected large vessel occlusion (LVO) acute ischemic strokes directly to endovascular centers based on a stroke severity score. The predictive value of this algorithm for identifying LVO is dependent on the overall prevalence of LVO acute ischemic stroke in the EMS population screened for stroke, which has not been reported. Methods— We performed a cross-sectional study of patients transported by our county’s EMS agency who were dispatched as a possible stroke or had a primary impression of stroke by paramedics. We determined the prevalence of LVO by reviewing medical record imaging reports based on a priori specified criteria. Results— We enrolled 2402 patients, of whom 777 (32.3%) had an acute stroke–related diagnosis. Among 485 patients with acute ischemic stroke, 24.1% (n=117) had an LVO, which represented only 4.87% (95% confidence interval, 4.05%–5.81%) of the total EMS population screened for stroke. Conclusions— Overall, the prevalence of LVO acute ischemic stroke in our EMS population screened for stroke was low. This is an important consideration for any EMS stroke severity-based triage protocol and should be considered in predicting the rates of overtriage to endovascular stroke centers.

Regional Evaluation of the Severity-Based Stroke Triage Algorithm for Emergency Medical Services Using Discrete Event Simulation

Background and Purpose— The Severity-Based Stroke Triage Algorithm for Emergency Medical Services endorses routing patients with suspected large vessel occlusion acute ischemic strokes directly to endovascular stroke centers (ESCs). We sought to evaluate different specifications of this algorithm within a region. Methods— We developed a discrete event simulation environment to model patients with suspected stroke transported according to algorithm specifications, which varied by stroke severity screen and permissible additional transport time for routing patients to ESCs. We simulated King County, Washington, and Mecklenburg County, North Carolina, distributing patients geographically into census tracts. Transport time to the nearest hospital and ESC was estimated using traffic-based travel times. We assessed undertriage, overtriage, transport time, and the number-needed-to-route, defined as the number of patients enduring additional transport to route one large vessel occlusion patient to an ESC. Results— Undertriage was higher and overtriage was lower in King County compared with Mecklenburg County for each specification. Overtriage variation was primarily driven by screen (eg, 13%–55% in Mecklenburg County and 10%–40% in King County). Transportation time specifications beyond 20 minutes increased overtriage and decreased undertriage in King County but not Mecklenburg County. A low- versus high-specificity screen routed 3.7× more patients to ESCs. Emergency medical services spent nearly twice the time routing patients to ESCs in King County compared with Mecklenburg County. Conclusions— Our results demonstrate how discrete event simulation can facilitate informed decision making to optimize emergency medical services stroke severity-based triage algorithms. This is the first step toward developing a mature simulation to predict patient outcomes.

Guidelines For Extending the Tissue Plasminogen Activator Treatment Window for Ischemic Stroke

To the Editor: The anticipated recently published guidelines, regarding extending the tissue plasminogen activator (tPA) treatment window for ischemic stroke, are sure to garner much attention and discussion within the United States.1 Largely based on the European Cooperative Acute Stroke Study (ECASS) III trial results, the newly proposed 3- to 4.5-hour tPA treatment guidelines appropriately exclude patients >80 years, those with a baseline National Institutes of Health Stroke Scale score >25, and …