No abstract

Introduction: We recently published a risk prediction score for telestroke (TS) encounters to differentiate stroke mimics (SM) from ischemic cerebrovascular disease, derived and validated at multiple telestroke sites across the US and Europe. In this study, we assessed if it could be applied to a comprehensive stroke center, non-telemedicine, stroke code registry. Method: In this IRB approved analysis, we performed ROC curve analysis on retrospectively assessed prospectively collected data from acute stroke code registry database for patients from 10/2004 to 7/2018. We tested only characteristics previously shown to be associated with SM. The TM score = (Age multiplied by 0.2) + 6 (if Hx of atrial fib) + 3 (if Hx of HTN) + 9 (if facial weakness) + 5 (if NIHSS > 14) - 6 (if Hx of seizure)). Result: Based on final diagnosis, SM accounted for 1,978/4,185 (47.2%) of patients. Age, NIHSS > 14, facial weakness, atrial fibrillation, hypertension, and seizure were all significantly associated with diagnosis of SM. The TM Score performed well on ROC curve analysis with AUC of 0.704 (p<0.001). Conclusion: This non-TS, face to face, validation cohort performed similarly to our validations at prior centers (0.70 vs 0.72). This finding not only continues to validate the TM score as an effective tool in assessing the ability to predict SMs, but also broadens its potential for use in non-TS populations. It is promising that it performed well despite a substantially higher proportion of SMs than in TS encounters where some may have already been screened out. Tools like the TM score may help highlight key clinical differences between mimics and stroke patients during complex, time-critical acute evaluations.

Introduction and Hypothesis: Intracranial Atherosclerotic Stenosis (ICAS) is associated with 8-10% of all strokes in the U.S. Although there is evidence in the Asian population that inflammation plays a role in ICAS, it has not been shown in the U.S. population. We hypothesized that midlife sensitivity C-reactive protein (hs-CRP), a marker of inflammation, is associated with late-life ICAS in the U.S. population. Methods: The Atherosclerosis Risk in Communities (ARIC) study recruited participants from four U.S. communities between 1987-1989. In the ancillary Dental ARIC study, dentate subjects from ARIC undergoing full-mouth examination also had blood samples obtained to measure the serum inflammatory marker, hs-CRP (1996-1998). High sensitivity ELISA assay that had been validated against nephelometry, was used to measure hs-CRP. Of this cohort, a subset (N=909) underwent high resolution 3T magnetic resonance angiogram at a follow-up visit (2011-2013). All images were analyzed in a centralized lab and ICAS was graded as no stenosis/<50% stenosis, or ≥50% stenosis/complete occlusion. Crude and adjusted Odds Ratio (OR, adjusted for age, gender, race, body mass index, hypertension, diabetes, low density lipoprotein level, and smoking) were calculated to test the association between hs-CRP (stratified as <1, 1-3 and >3 mg/l), and ICAS. Results: A total of 909 subjects (mean age 62±6, 45% male, 81% Caucasian and 19% African-American), underwent assessment of hs-CRP and ICAS. Compared with the reference group (hs-CRP <1 mg/l) modestly elevated hs-CRP (1-3 mg/l) was not significantly associated with >50% ICAS, on univariate (Crude OR 1.3 95% CI: 0.9-2.0) or multivariable analysis (Adjusted OR 1.3, 95% CI: 0.9-2.0). Elevated hs-CRP (>3mg/l) was significantly associated with >50% ICAS in both univariate (Crude OR 1.6, 95% CI:1.1-2.3) and adjusted model (Adjusted OR 1.6, 95% CI:1.1-2.4). Conclusions: In this US population-based community study, we report a significant and independent association between inflammatory marker hs-CRP and ICAS. Further studies are required to test if anti-inflammatory drugs or diet prevents ICAS.

Introduction: There has been extensive education required as part of the Joint Commission (TJC) stroke center certification to rapidly identify acute stroke patients. One study found from 1998 to 2001, 25.3% of stroke codes (SC) were deemed stroke mimics (SM). The purpose of this study was to assess if SC activation in true stroke (TS) patients has improved as part of TJC certification. Methods: This study was a retrospective, observational study of prospectively collected data from an IRB approved Stroke Registry. This includes all SC managed by the stroke team from June 2006-June 2018. Data collected includes initial diagnosis, final diagnosis, demographics, and treatment variables. Analysis included all patients in the registry. Final diagnosis was adjudicated by stroke faculty. Baseline demographics, medical history, treatments, and baseline NIHSS were assessed. Data was examined for frequencies and distribution. Baseline demographics and correlations were compared as appropriate. Results: Of all SC (n=4602), 2100 were SM (45.6%). SM were associated with lower age and blood pressure, history of seizure or dementia, female sex, and black race (Table 1). SM also had a lower median NIHSS (3 vs 6, p<0.0001). Of SM, 62/2100 (3%) received IV rt-PA. The most common SM final diagnoses were other, somatization, seizure, encephalopathy and migraine (Figure 1). Conclusions: In this large retrospective, study, 45.6% of SC activations were SM. This is a significant increase in the number of SM captured in previous studies. These results show healthcare professionals are overly cautious at alerting a stroke code as they do not want to miss an opportunity to provide thrombolytic treatment.

Background: Because acute treatment in stroke is time-based for inclusion, efficacy and safety, obtaining an accurate Last Known Normal (LKN) is of critical importance in stroke codes. We sought to assess with a larger sample if the assessment of 1st documented LKN times has improved since our prior 2013 data. Methods: Data was obtained from an IRB approved stroke registry in a single center from July 2013 to December 2018, for LKN time documented by a neurologist (“LKN2”). Chart review was done to document 1st reported LKN time as documented by EMS (or ED if no runsheets available) (“LKN1”). Inpatient stroke codes and hospital transfers were excluded. Differences in LKN1 and LKN2 were computed and stratified into Groups A (LKN1 is earlier in time than LKN2), B (LKN1 is the same as LKN2), and C (LKN1 is later in time than LKN2). Baseline characteristics, thrombolysis rates, stroke code time interval metrics, 90-day disability and death, discharge disposition, and symptomatic ICH rates, were compared between groups. Results: Of 990 stroke codes, 397 or 40.1% had agreeable LKN1 and LKN2 times (Group B) (increased from a historic 26.4%;p=<.001), while 593 or 59.9% had a discrepancy in LKN1 and LKN2 times. Of 593, 177 (29.8%) had an LKN1 earlier than LKN2 (Group A), 416 (70.2%) had LKN1 later than LKN2 (Group C). The mean age in Groups A, B, and C were 63.5, 63.4, and 66.1, respectively (p=0.04). Discharge disposition to home/self-care was seen more in Group C (n=284, 69.4%;A n=117, 63.2%;B n=255, 66.2%;p=0.03). There were no other differences in baseline characteristics, r-tPA rates, 90-day disability and death, or sICH rates. Among Group C patients who were excluded from IV-tPA based on time, 55.6% would have been treated outside of stroke guidelines had LKN1 been used (55.6% vs. prior report of 69.7%;p=0.2). Conclusion: Though initial LKN times obtained by EMS and ED responders have improved over time, there remains a significant discrepancy with 60% incorrect initial reports. Caution should be used when considering rt-PA treatments based on these LKN1 reports as 56% of cases could have been treated outside of current guidelines and evidence. This study highlights the need for continuous training in obtaining accurate LKN times and caution about using initial estimates of time.