This study confirms a good agreement between TISS-28 and NEMS in a large, independent sample. However, as shown by the differences between medical and postoperative/trauma patients, a change in case mix may result in different regression equations. Further, wide limits of agreement indicate that there may be a rather large variability between the two measures at the individual level.
BackgroundData on the implementation of prehospital large vessel occlusion (LVO) scales to identify and triage patients with acute ischemic stroke (AIS) in the field are limited, with the majority of studies occurring outside the USA.ObjectiveTo report our long-term experience of a US countywide emergency medical services (EMS) acute stroke triage protocol using the Rapid Arterial oCclusion Evaluation (RACE) score.MethodsOur prospective database was used to identify all consecutive patients triaged within Lucas County, Ohio by the EMS with (1) a RACE score ≥5, taken directly to an endovascular capable center (ECC) as RACE-alerts (RA) and (2) a RACE score <5, taken to the nearest hospital as stroke-alerts (SA). Baseline demographics, RACE score, time metrics, final diagnosis, treatments, and clinical and angiographic outcomes were captured. The sensitivity and specificity for patients with a RACE score ≥5 with LVO, eligible for mechanical thrombectomy (MT), were calculated.ResultsBetween July 2015 and June 2018, 492 RA and 1147 SA were triaged within our five-hospital network. Of the RA, 37% had AIS secondary to LVOs. Of the 492 RA and 1147 SA, 125 (25.4%) and 38 (3.3%), respectively, underwent MT (OR=9.9; 95% CI 6.8 to 14.6; p<0.0001). Median times from onset-to-ECC arrival (74 vs 167 min, p=0.03) and dispatch-to-ECC arrival (31 vs 46 min, p=0.0002) were shorter in the RA-MT than in the SA-MT cohort. A RACE cut-off point ≥5 showed a sensitivity and specificity of 0.77 and 0.75 for detection of patients with LVO eligible for MT, respectively.ConclusionsWe have demonstrated the long-term feasibility of a countywide EMS-based prehospital triage protocol using the RACE Scale within our hospital network.
To the Editor:Morbidity and mortality associated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are extremely visible 1 ; however, the effect of the COVID-19 pandemic on the management of other pathologies requiring complex interventions and critical care resources-the bystander effect 2 -is not well described. This is certainly true of stroke patients whose clinical outcomes are a function of early presentation, timely diagnosis, emergent intervention, and critical care management. [3][4][5] With the arrival of COVID-19 cases in the month of March in the hotspot of Michigan, we describe the bystander effect of the COVID-19 pandemic on ischemic and hemorrhagic stroke. METHODSThis is a retrospective analysis of deidentified data submitted from 11 Comprehensive Stroke Centers (CSCs) and 1 Primary Stroke Center (PSC) in Michigan and northwest Ohio. The study was approved by the University Institutional Review Board. Patient consent was not required given the retrospective nature of the study. Using Poisson regression analysis, we calculated the incidence-rate ratios (IRRs) comparing the study period of March 2020 to each of the control periods (February 2020 and March 2019). Additionally, the unpaired t-test for continuous variables and the Chi-square test for categorical variables were used as appropriate.
Introduction: Multiple risk factors of mortality have been identified in patients with COVID-19. Here, we sought to determine the effect of a history of neurological disorder and development of neurological manifestations on mortality in hospitalized patients with COVID-19.Methods: From March 20 to May 20, 2020, hospitalized patients with laboratory confirmed or highly suspected COVID-19 were identified at four hospitals in Ohio. Previous history of neurological disease was classified by severity (major or minor). Neurological manifestations during disease course were also grouped into major and minor manifestations. Encephalopathy, ischemic or hemorrhagic stroke, and seizures were defined as major manifestations, whereas minor neurological manifestations included headache, anosmia, dysgeusia, dizziness or vertigo, and myalgias. Multivariate logistic regression models were used to determine significant predictors of mortality in patients with COVID-19 infection.Results: 574/626 hospitalized patients were eligible for inclusion. Mean age of the 574 patients included in the analysis was 62.8 (SD 17.6), with 298 (51.9%) women. Of the cohort, 240(41.8%) patients had a prior history of neurological disease (HND), of which 204 (35.5%) had a major history of neurological disease (HND). Mortality rates were higher in patients with a major HND (30.9 vs. 15.4%; p = 0.00002), although this was not a significant predictor of death. Major neurological manifestations were recorded in 203/574 (35.4%) patients during disease course. The mortality rate in patients who had major neurological manifestations was 37.4% compared to 11.9% (p = 2 × 10 −12 ) in those who did not. In multivariate analysis, major neurological manifestation (OR 2.1,; p = 0.002) was a predictor of death. Conclusions: In this retrospective study, history of pre-existing neurological disease in hospitalized COVID-19 patients did not impact mortality; however, development of major neurological manifestations during disease course was found to be an independent predictor of death. Larger studies are needed to validate our findings.
Background: Mechanical thrombectomy (MT) for ischemic stroke can be performed under local anesthesia (LA), conscious sedation (CS), or general anesthesia (GA). The need for monitoring by anesthesia providers may be resource intensive. We sought to determine differences in outcomes of MT when sedation is performed by an anesthesia team compared to sedation-trained providers. Methods: We performed a retrospective analysis on patients who were screened by a pre-hospital stroke severity screening tool and underwent MT at two stroke centers. Baseline characteristics, time metrics, sedatives, peri-procedural intubation, complications, and outcomes were recorded. Good outcome was defined as modified Rankin score of ≤2. Results: We analyzed 104 patients (sedation-trained provider = 63, anesthesia team = 41) between July 2015 and December 2017. In the sedation-trained provider group, four patients required intervention by an anesthesia team. There were no differences in patients receiving LA (sedation-trained provider 24% vs. anesthesia team 27% p = 0.82), CS (70 vs. 63%, p = 0.53), or GA (6 vs. 10%, p = 0.71) between groups. Sedation-trained providers were more likely to use only one drug during the procedure (62 vs. 34%, p = 0.009). The rate of procedural complications (9.5 vs. 4.5%, p = 0.48), good outcome (56 vs. 39%, p = 0.11), and mortality (22 vs. 24%, p = 0.82) was similar between groups. Sedation by provider type did not predict functional outcome or mortality at 3 months. Conclusions: Sedation-trained providers are capable of delivering appropriate sedation without compromising patient safety. The use of “as needed” anesthesia teams for MT may have considerable effect on resource allocation and cost.
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