Ultra-Early Differential Diagnosis of Acute Cerebral Ischemia and Hemorrhagic Stroke by Measuring the Prehospital Release Rate of GFAP.

BACKGROUND: Plasma glial fibrillary acidic protein (GFAP) and tau are promising markers for differentiating acute cerebral ischemia (ACI) and hemorrhagic stroke (HS), but their prehospital dynamics and usefulness are unknown. METHODS: We performed ultra-sensitivite single-molecule array (Simoa®) measurements of plasma GFAP and total tau in a stroke code patient cohort with cardinal stroke symptoms [National Institutes of Health Stroke Scale (NIHSS) ≥3]. Sequential sampling included 2 ultra-early samples, and a follow-up sample on the next morning. RESULTS: We included 272 cases (203 ACI, 60 HS, and 9 stroke mimics). Median (IQR) last-known-well to sampling time was 53 (35-90) minutes for initial prehospital samples, 90 (67-130) minutes for secondary acute samples, and 21 (16-24) hours for next morning samples. Plasma GFAP was significantly higher in patients with HS than ACI (P < 0.001 for <1 hour and <3 hour prehospital samples, and <3 hour secondary samples), while total tau showed no intergroup difference. The prehospital GFAP release rate (pg/mL/minute) occurring between the 2 very early samples was significantly higher in patients with HS than ACI [2.4 (0.6-14.1)] versus 0.3 (-0.3-0.9) pg/mL/minute, P < 0.001. For cases with <3 hour prehospital sampling (ACI n = 178, HS n = 59), a combined rule (prehospital GFAP >410 pg/mL, or prehospital GFAP 90-410 pg/mL together with GFAP release >0.6 pg/mL/minute) enabled ruling out HS with high certainty (NPV 98.4%) in 68% of patients with ACI (sensitivity for HS 96.6%, specificity 68%, PPV 50%). CONCLUSIONS: In comparison to single-point measurement, monitoring the prehospital GFAP release rate improves ultra-early differentiation of stroke subtypes. With serial measurement GFAP has potential to improve future prehospital stroke diagnostics.

Targets for improving dispatcher identification of acute stroke.

BACKGROUND: Accurate identification of acute stroke by Emergency Medical Dispatchers (EMD) is essential for timely and purposeful deployment of Emergency Medical Services (EMS), and a prerequisite for operating mobile stroke units. However, precision of EMD stroke recognition is currently modest. AIMS: We sought to identify targets for improving dispatcher stroke identification. METHODS: Dispatch codes and EMS patient records were cross-linked to investigate factors associated with an incorrect dispatch code in a prospective observational cohort of 625 patients with a final diagnosis of acute stroke or transient ischemic attack (TIA), transported to our stroke center as candidates for recanalization therapies. Call recordings were analyzed in a subgroup that received an incorrect low-priority dispatch code indicating a fall or unknown acute illness (n = 46). RESULTS: Out of 625 acute stroke/TIA patients, 450 received a high-priority stroke dispatch code (sensitivity 72.0%; 95% CI, 68.5-75.5). Independent predictors of dispatcher missed acute stroke included a bystander caller (aOR, 3.72; 1.48-9.34), confusion (aOR, 2.62; 1.59-4.31), fall at onset (aOR, 1.86; 1.24-2.78), and older age (aOR [per year], 1.02; 1.01-1.04). Of the analyzed call recordings, 71.7% revealed targets for improvement, including failure to recognize a Face Arm Speech Time (FAST) test symptom (21/46 cases, 18 with speech disturbance), or failure to thoroughly evaluate symptoms (12/46 cases). CONCLUSIONS: Based on our findings, efforts to improve dispatcher stroke identification should primarily focus on improving recognition of acute speech disturbance, and implementing screening of FAST-symptoms in emergency phone calls revealing a fall or confusion. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov . Unique identifier: NCT02145663.

Diagnosing cerebral ischemia with door-to-thrombolysis times below 20 minutes.

OBJECTIVES: To clarify diagnostic accuracy and consequences of misdiagnosis in the admission evaluation of stroke-code patients in a neurologic emergency department with less than 20-minute door-to-thrombolysis times. METHODS: Accuracy of admission diagnostics was studied in an observational cohort of 1,015 stroke-code patients arriving by ambulance as candidates for recanalization therapy between May 2013 and November 2015. Immediate admission evaluation was performed by a stroke neurologist or a neurology resident with dedicated stroke training, primarily utilizing CT-based imaging. RESULTS: The rate of correct admission diagnosis was 91.1% (604/663) for acute cerebral ischemia (ischemic stroke/TIA), 99.2% (117/118) for hemorrhagic stroke, and 61.5% (144/234) for stroke mimics. Of the 150 (14.8%) misdiagnosed patients, 135 (90.0%) had no acute findings on initial imaging and 100 (67.6%) presented with NIH Stroke Scale score 0 to 2. Misdiagnosis altered medical management in 70 cases, including administration of unnecessary treatments (thrombolysis n = 13, other n = 24), omission of thrombolysis (n = 5), delays to specific treatments of stroke mimics (n = 13, median 56 [31-93] hours), and delays to antiplatelet medication (n = 14, median 1 [1-2] day). Misdiagnosis extended emergency department stay (median 6.6 [4.7-10.4] vs 5.8 [3.7-9.2] hours; p = 0.001) and led to unnecessary stroke unit stay (n = 10). Detailed review revealed 8 cases (0.8%) in which misdiagnosis was possible or likely to have worsened outcomes, but no death occurred as a result of misdiagnosis. CONCLUSIONS: Our findings support the safety of highly optimized door-to-needle times, built on thorough training in a large-volume, centralized stroke service with long-standing experience. Augmented imaging and front-loaded specialist engagement are warranted to further improve rapid stroke diagnostics.