English, Stephen

Introduction: Central retinal artery occlusion (CRAO) is an under-recognized stroke subtype that may benefit from hyperacute reperfusion therapies. We aimed to evaluate the ability of telestroke activations to provide CRAO diagnosis and thrombolysis. Methods: This retrospective observational study investigates all encounters conducted for acute visual loss between 2010 and 2021 in our multicentric Mayo Clinic Telestroke Network. Demographics, time from visual loss to telestroke evaluation, ocular examination, diagnostic, and therapeutic recommendations were collected for CRAO subjects. Results: Out of 9,511, 49 encounters (0.51%) were conducted for an acute ocular complaint. Five patients had possible CRAO, and 4 presented within 4.5 h from symptom onset (range 1.5–5 h). None received thrombolytic therapy. All telestroke physicians recommended ophthalmology consultation. Conclusion: Current telestroke assessment of acute visual loss is suboptimal and patients eligible for acute reperfusion therapies may not be offered treatment. Teleophthalmologic evaluations and advanced ophthalmic diagnostic tools should complement telestroke systems.

Introduction: Prehospital telestroke is increasingly utilized in mobile stroke units and telemedicine-enabled ambulances for acute ischemic stroke (AIS). While the NIHSS remains the standard for telestroke assessment, simpler scales have been validated to help paramedics recognize large vessel occlusion (LVO) strokes but have not been evaluated in a traditional telestroke network. We aimed to determine the accuracy of common LVO scales in a large academic telestroke practice. Methods: This retrospective study included all telestroke consults performed in a large academic telestroke network from 2019 to 2020. Patients were excluded if no NIHSS or vessel imaging was performed. We recorded presenting NIHSS, site of vessel occlusion, and discharge diagnosis. LVO was defined as an acute occlusion of the internal carotid artery and/or M1 middle cerebral artery. The NIHSS was used to calculate 7 LVO scales (RACE, C-STAT, FAST-ED, 3I-SS, PASS, VAN, and G-FAST). Diagnostic performance was assessed by calculating sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), and accuracy using the established thresholds of each scale. These results were compared to NIHSS at thresholds of 6, 8, and 10. Area under curve (AUC) was calculated using c-statistics by treating scales as continuous variables. Results: A total of 625 patients were included, 373/625 (59.7%) of which were diagnosed with AIS at discharge. LVO was identified in 78/625 (12.5%) patients. VAN was the most sensitive prehospital stroke scale (83.3%), whereas 3I-SS ≥ 4 was the most specific (95.2%). Both the RACE and FAST-ED scales demonstrated superior accuracy and AUC compared to the NIHSS (Table 1). Conclusions: To our knowledge, this is the first study assessing LVO scale accuracy in a large telestroke network. As use of prehospital telestroke grows, this study highlights several scales that may allow for faster prehospital triage decisions without sacrificing accuracy.

Introduction: Collateral circulation plays a crucial role in determining the extent of brain tissue ischemia and functional outcome in large vessel occlusive (LVO) stroke. Heart failure (HF) is known to cause cerebral hypoperfusion, yet the relationship between HF and robustness of collateral flow has not been well described. Here we hypothesized that HF is associated with poor collateral flow and functional outcome in patients presenting with LVO treated with mechanical thrombectomy (MT). Methods: A single center retrospective study of patients presenting with LVO ischemic stroke who underwent MT between 2012-2020 was done. Single-phase CTA of head prior to MT was used to assess collateral status with poor status defined as ≤ 50% filling and good status as >50% filling. Classification of HF by left ventricular ejection fraction (LVEF) on echocardiogram was used where HF with reduced ejection fraction (HFrEF) had LVEF ≤40%, HF with preserved EF (HFpEF) had LVEF ≥50% with evidence of structural heart disease, and no HF was LVEF≥50% without structural heart disease. Functional outcome was modified Rankin scale (mRS) at 90 days with scores of 0-2 representing good outcome and 3-6 representing poor outcome. Multivariable logistic regression analyses were performed to evaluate the association between HF and poor collaterals after adjusting for vascular risk factors. Results: We identified 235 patients, mean age was 69 ±15 years, median NIHSS was 18, and 45.5% had HF (HFrEF 12.8%, HFmrEF 4.7%, HFpEF 28.1%) while 54.5% had no HF. Poor collaterals were seen in 47.7%, and those with HF were likely to have poor collaterals compared to those without HF (56.1% vs 35.1%, P=.001). There was a dose-dependent relationship between severity of HF and poor collaterals: adjusted odds of poor collaterals were 1.63 and 2.45 in HFpEF and HFrEF, compared to those without HF (trend p=.018). Patients with poor collaterals were likely to have poor outcome at 3 months compared to those with good collaterals (75.0% vs 57.8%; p=.015). Conclusion: Patients with HFrEF were twice as likely to have poor collaterals. This study demonstrated a likely mechanism for poor outcomes seen in ischemic stroke with HF, future studies may explore whether optimization of HF may augment collaterals to improve outcomes.

Introduction: Telestroke facilitates emergent assessment of patients with suspected acute ischemic stroke (AIS) to identify candidates for acute interventions. The diagnostic accuracy of the telestroke consultation of a large academic hub and spoke telemedicine network has yet to be investigated. The goal of our study is to determine the diagnostic accuracy of the initial telestroke consultation. Methods: This is an IRB-exempt retrospective study including all patients evaluated for cerebral ischemia via video telestroke consultation in a large academic hub and spoke telemedicine network from 2019 to 2020. Detailed chart review was conducted to identify initial suspected diagnosis and final diagnosis. Cerebral ischemia was defined as AIS and transient ischemic attack (TIA). All other diagnoses were defined as stroke mimics. Data was organized into continuous and categorical variables. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, area under the curve (AUC) and likelihood ratio (LR+) for the initial telestroke consultation diagnosis were calculated while using the final diagnosis as the gold standard diagnosis. Results: A total of 1043 patients met inclusion criteria. Final diagnosis of cerebral ischemia was made in 63.5% of all patients (539/1043 with AIS,123/1043 with TIA). Stroke mimic was diagnosed in 36.5% patients (381/1043). The sensitivity and specificity of telestroke evaluation for diagnosis of cerebral ischemia were 97.1% and 81.4%, respectively. PPV was 90.1%, and NPV was 94.2%. Overall diagnostic accuracy was 91.4% with a LR+ of 5.21 and AUC of 0.89. The most common stroke mimics were metabolic encephalopathy (13.7%, 52/381), migraine (10.8%, 41/381) and seizure (10.5%, 40/381). Conclusions: This study highlights the high diagnostic accuracy of telestroke providers to diagnose cerebral ischemia and stroke mimic in a large academic hub and spoke network. Further research is needed to investigate methods to improve our diagnostic accuracy further, as well as explore the application of tele-neurology in the non-stroke setting.

The recognition and management of stroke in the prehospital setting has become increasingly important to improve patient outcomes. Several strategies to advance prehospital stroke care have been developed, including the mobile stroke unit and the telemedicine-enabled ambulance—or “mini-MSU.” These strategies both incorporate ambulance-based audio-visual telemedicine evaluation with a vascular neurologist to facilitate faster treatment but differ in several areas including upfront and recurring costs, scalability or growth potential, ability to integrate into existing emergency medical services systems, and interoperability across multiple specialties or conditions. While both the mobile stroke unit and mini-mobile stroke unit model are valid approaches to improve stroke care, the authors aim to compare these models based on costs, scalability, integration, and interoperability in order to guide our prehospital leaders to find the best solutions for their communities.

Introduction: Acute stroke pre-arrival notification by emergency medical services (EMS) allows hospital personnel to mobilize resources in advance, thereby improving treatment times and outcomes. However, criteria for pre-arrival notification vary by institution. In developing our own pre-arrival notification system, we aimed to determine whether objective measures, EMS clinical impression, or a combination of both best predicted accurate stroke team activation. Methods: Retrospective review of consecutive patients presenting to our institution via EMS with suspicion of acute stroke from 2014-2015. Data recorded included age, gender, time of symptom onset, glucose, Cincinnati Prehospital Stroke Scale (CPSS), Glasgow Coma Scale (GCS), and EMS impression. Univariate logistic regression was performed with acute stroke team activation in the emergency department (ED) as the endpoint. Results: 130 patients met inclusion criteria. Of these, 88 prompted the ED provider to activate the acute stroke team. Of variables analyzed, CPSS was clinically and statistically significant (OR. 1.7, 95% CI 1.2-2.5, p=0.0035) on univariate analysis, with arm weakness being the most predictive component (OR 2.9, 95% CI 1.04-8.1, p=0.04). EMS impression was not statistically significant (p>0.05). We then performed sensitivity and specificity analyses of CPSS, EMS impression, and CPSS combined with EMS impression (Table). A CPSS score of 3 had the highest specificity, and CPSS score of 1 combined with EMS impression the highest sensitivity. Conclusion: CPSS was the key significant predictor of ED acute stroke team activation, and more specific than EMS clinical impression. By combining CPSS and EMS impression, sensitivity improved, but at the expense of specificity. This suggests that reproducible measurements and scores, such as CPSS, should be the main driver for stroke pre-notification systems and should be integrated systematically into EMS education programs.

Background and Purpose: Field Assessment Stroke Triage for Emergency Destination (FAST-ED) scale is a helpful tool to triage patients with stroke in the field. However, data on its reliability in the prehospital setting are lacking. We aim to test the reliability of FAST-ED scale when used by paramedics in a mobile stroke unit covering a metropolitan area. Methods: As part of standard operating mobile stroke unit procedures, paramedics initially evaluated patients. If the event characterized a stroke alert, the FAST-ED score was determined by the paramedic upon patient contact (in-person) and then independently by a vascular neurologist (VN) immediately after paramedic evaluation (remotely/telemedicine). This allowed testing of the interrater agreement of the FAST-ED scoring performance between on-site prehospital providers and remotely located VN. Results: Of a total of 238 patients transported in the first 15 months of the mobile stroke unit’s activity, 173 were included in this study. Median age was 63 (interquartile range, 55.5–75) years and 52.6% were females. A final diagnosis of ischemic stroke was made in 71 (41%), transient ischemic attack in 26 (15%), intracranial hemorrhage in 15 (9%), whereas 61 (35%) patients were stroke mimics. The FAST-ED scores matched perfectly among paramedics and VN in 97 (56%) instances, while there was 0 to 1-point difference in 158 (91.3%), 0 to 2-point difference in 171 (98.8%), and 3 or more point difference in 2 (1.1%) patients. The intraclass correlation between VN and paramedic FAST-ED scores showed excellent reliability, intraclass correlation coefficient 0.94 (95% CI, 0.92–0.96; P <0.001). When VN recorded FAST-ED score ≥3, paramedics also scored FAST-ED≥3 in majority of instances (63/71 patients; 87.5%). A large vessel occlusion was identified in 16 (9.2%) patients; 13 occlusions were identified with a FAST-ED≥3 while 3 were missed. All of the latter patients had National Institutes of Health Stroke Scale score ≤5. Conclusions: We demonstrate excellent reliability of FAST-ED scale performed by paramedics when compared with VN, indicating that it can be accurately performed by paramedics in the prehospital setting.

AbstractVascular disorders of the spinal cord are uncommon yet under-recognized causes of myelopathy. Etiologies can be predominantly categorized into clinical and radiographic presentations of arterial ischemia, venous congestion/ischemia, hematomyelia, and extraparenchymal hemorrhage. While vascular myelopathies often produce significant morbidity, recent advances in the understanding and recognition of these disorders should continue to expedite diagnosis and proper management, and ideally improve patient outcomes. This article comprehensively reviews relevant spinal cord vascular anatomy, clinical features, radiographic findings, treatment, and prognosis of vascular disorders of the spinal cord.