Influence of vascular imaging acquisition at local stroke centers on workflows in the drip-n-ship model: a RACECAT post hoc analysis.

BACKGROUND: The influence of vascular imaging acquisition on workflows at local stroke centers (LSCs) not capable of performing thrombectomy in patients with a suspected large vessel occlusion (LVO) stroke remains uncertain. We analyzed the impact of performing vascular imaging (VI+) or not (VI- at LSC arrival on variables related to workflows using data from the RACECAT Trial. OBJECTIVE: To compare workflows at the LSC among patients enrolled in the RACECAT Trial with or without VI acquisition. METHODS: We included patients with a diagnosis of ischemic stroke who were enrolled in the RACECAT Trial, a cluster-randomized trial that compared drip-n-ship versus mothership triage paradigms in patients with suspected acute LVO stroke allocated at the LSC. Outcome measures included time metrics related to workflows and the rate of interhospital transfers and thrombectomy among transferred patients. RESULTS: Among 467 patients allocated to a LSC, vascular imaging was acquired in 277 patients (59%), of whom 198 (71%) had a LVO. As compared with patients without vascular imaging, patients in the VI+ group were transferred less frequently as thrombectomy candidates to a thrombectomy-capable center (58% vs 74%, P=0.004), without significant differences in door-indoor-out time at the LSC (median minutes, VI+ 78 (IQR 69-96) vs VI- 76 (IQR 59-98), P=0.6). Among transferred patients, the VI+ group had higher rate of thrombectomy (69% vs 55%, P=0.016) and shorter door to puncture time (median minutes, VI+ 41 (IQR 26-53) vs VI- 54 (IQR 40-70), P<0.001). CONCLUSION: Among patients with a suspected LVO stroke initially evaluated at a LSC, vascular imaging acquisition might improve workflow times at thrombectomy-capable centers and reduce the rate of futile interhospital transfers. These results deserve further evaluation and should be replicated in other settings and geographies.

Accuracy of a Smartwatch to Assess Heart Rate Monitoring and Atrial Fibrillation in Stroke Patients.

(1) Background: Consumer smartwatches may be a helpful tool to screen for atrial fibrillation (AF). However, validation studies on older stroke patients remain scarce. The aim of this pilot study from RCT NCT05565781 was to validate the resting heart rate (HR) measurement and the irregular rhythm notification (IRN) feature in stroke patients in sinus rhythm (SR) and AF. (2) Methods: Resting clinical HR measurements (every 5 min) were assessed using continuous bedside ECG monitoring (CEM) and the Fitbit Charge 5 (FC5). IRNs were gathered after at least 4 h of CEM. Lin's concordance correlation coefficient (CCC), Bland-Altman analysis, and mean absolute percentage error (MAPE) were used for agreement and accuracy assessment. (3) Results: In all, 526 individual pairs of measurements were obtained from 70 stroke patients-age 79.4 years (SD ± 10.2), 63% females, BMI 26.3 (IQ 22.2-30.5), and NIHSS score 8 (IQR 1.5-20). The agreement between the FC5 and CEM was good (CCC 0.791) when evaluating paired HR measurements in SR. Meanwhile, the FC5 provided weak agreement (CCC 0.211) and low accuracy (MAPE 16.48%) when compared to CEM recordings in AF. Regarding the accuracy of the IRN feature, analysis found a low sensitivity (34%) and high specificity (100%) for detecting AF. (4) Conclusion: The FC5 was accurate at assessing the HR during SR, but the accuracy during AF was poor. In contrast, the IRN feature was acceptable for guiding decisions regarding AF screening in stroke patients.

Blood Biomarkers to Predict Long-Term Mortality after Ischemic Stroke.

Stroke is a major cause of disability and death globally, and prediction of mortality represents a crucial challenge. We aimed to identify blood biomarkers measured during acute ischemic stroke that could predict long-term mortality. Nine hundred and forty-one ischemic stroke patients were prospectively recruited in the Stroke-Chip study. Post-stroke mortality was evaluated during a median 4.8-year follow-up. A 14-biomarker panel was analyzed by immunoassays in blood samples obtained at hospital admission. Biomarkers were normalized and standardized using Z-scores. Multiple Cox regression models were used to identify clinical variables and biomarkers independently associated with long-term mortality and mortality due to stroke. In the multivariate analysis, the independent predictors of long-term mortality were age, female sex, hypertension, glycemia, and baseline National Institutes of Health Stroke Scale (NIHSS) score. Independent blood biomarkers predictive of long-term mortality were endostatin > quartile 2, tumor necrosis factor receptor-1 (TNF-R1) > quartile 2, and interleukin (IL)-6 > quartile 2. The risk of mortality when these three biomarkers were combined increased up to 69%. The addition of the biomarkers to clinical predictors improved the discrimination (integrative discriminative improvement (IDI) 0.022 (0.007-0.048), p < 0.001). Moreover, endostatin > quartile 3 was an independent predictor of mortality due to stroke. Altogether, endostatin, TNF-R1, and IL-6 circulating levels may aid in long-term mortality prediction after stroke.

Correlation of blood biomarkers with early-onset seizures after an acute stroke event.

INTRODUCTION: Blood biomarkers have not been widely studied in stroke-related seizures. In this study, we aimed to describe clinical factors and biomarkers present during acute stroke and to analyze their association with early-onset seizures. METHODS: We retrospectively evaluated a panel of 14 blood biomarkers in 1115 patients with ischemic and hemorrhagic stroke. Biomarkers were normalized and standardized using Z scores. We also recorded stroke and epilepsy-related variables, including stroke severity (National Institute of Health Stroke Scale [NIHSS] scores), type, and causes, time from onset of stroke to occurrence of early seizures, and type of seizure. Adjusted logistic regression models were built to identify clinical variables and biomarkers independently associated with early seizures. RESULTS: Mean ±â€¯standard deviation (SD) age was 72.3 ±â€¯13.2 years, and 56.8% of the patients were men. Thirty-eight patients (3.9%) developed early seizures with a median time to onset of 1 day (interquartile range (IQR), 0-4). A higher NIHSS score (odds ratio [OR] = 1.046; 95% confidence interval (CI): 1.001-1.094; p = 0.044) and hemorrhagic stroke (OR = 2.133; 95% CI: 1.010-4.504; p = 0.047) were independently associated with a greater risk of early seizures. Independent blood biomarkers predictive of early seizures were lower levels of tumor necrosis factor receptor 1 (TNF-R1) (<0.013) (p = 0.006; OR = 3.334; 95% CI: 1.414-7.864) and higher levels of neural cell adhesion molecule (NCAM) (>0.326) (p = 0.009; OR = 2.625; 95% CI: 1.271-5.420). The predictive power of the regression model was greater when clinical variables were combined with blood biomarkers (73.5%; 95% CI: 65.1%-81.9%) than when used alone (64%; 95% CI: 55%-72.9%). CONCLUSION: Higher NCAM and lower TNF-R1 levels may help predict the occurrence of early seizures. The combined use of these biomarkers and clinical variables could be useful for identifying patients at risk of seizures. This article is part of the Special Issue "Seizures & Stroke".

Revalidation of the RACE scale after its regional implementation in Catalonia: a triage tool for large vessel occlusion.

BACKGROUND AND PURPOSE: Our aim was to revalidate the RACE scale, a prehospital tool that aims to identify patients with large vessel occlusion (LVO), after its region-wide implementation in Catalonia, and to analyze geographical differences in access to endovascular treatment (EVT). METHODS: We used data from the prospective CICAT registry (Stroke Code Catalan registry) that includes all stroke code activations. The RACE score evaluated by emergency medical services, time metrics, final diagnosis, presence of LVO, and type of revascularization treatment were registered. Sensitivity, specificity, and area under the curve (AUC) for the RACE cut-off value ≥5 for identification of both LVO and eligibility for EVT were calculated. We compared the rate of EVT and time to EVT of patients transferred from referral centers compared with those directly presenting to comprehensive stroke centers (CSC). RESULTS: The RACE scale was evaluated in the field in 1822 patients, showing a strong correlation with the subsequent in-hospital evaluation of the National Institute of Health Stroke Scale evaluated at hospital (r=0.74, P<0.001). A RACE score ≥5 detected LVO with a sensitivity 0.84 and specificity 0.60 (AUC 0.77). Patients with RACE ≥5 harbored a LVO and received EVT more frequently than RACE <5 patients (LVO 35% vs 6%; EVT 20% vs 6%; all P<0.001). Direct admission at a CSC was independently associated with higher odds of receiving EVT compared with admission at a referral center (OR 2.40; 95% CI 1.66 to 3.46), and symtoms onset to groin puncture was 133 min shorter. CONCLUSIONS: This large validation study confirms RACE accuracy to identify stroke patients eligible for EVT, and provides evidence of geographical imbalances in the access to EVT to the detriment of patients located in remote areas.

Blood Biomarkers for the Early Diagnosis of Stroke: The Stroke-Chip Study.

BACKGROUND AND PURPOSE: Stroke diagnosis could be challenging in the acute phase. We aimed to develop a blood-based diagnostic tool to differentiate between real strokes and stroke mimics and between ischemic and hemorrhagic strokes in the hyperacute phase. METHODS: The Stroke-Chip was a prospective, observational, multicenter study, conducted at 6 Stroke Centers in Catalonia. Consecutive patients with suspected stroke were enrolled within the first 6 hours after symptom onset, and blood samples were drawn immediately after admission. A 21-biomarker panel selected among previous results and from the literature was measured by immunoassays. Outcomes were differentiation between real strokes and stroke mimics and between ischemic and hemorrhagic strokes. Predictive models were developed by combining biomarkers and clinical variables in logistic regression models. Accuracy was evaluated with receiver operating characteristic curves. RESULTS: From August 2012 to December 2013, 1308 patients were included (71.9% ischemic, 14.8% stroke mimics, and 13.3% hemorrhagic). For stroke versus stroke mimics comparison, no biomarker resulted included in the logistic regression model, but it was only integrated by clinical variables, with a predictive accuracy of 80.8%. For ischemic versus hemorrhagic strokes comparison, NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) >4.9 (odds ratio, 2.40; 95% confidence interval, 1.55-3.71; P<0.0001) and endostatin >4.7 (odds ratio, 2.02; 95% confidence interval, 1.19-3.45; P=0.010), together with age, sex, blood pressure, stroke severity, atrial fibrillation, and hypertension, were included in the model. Predictive accuracy was 80.6%. CONCLUSIONS: The studied biomarkers were not sufficient for an accurate differential diagnosis of stroke in the hyperacute setting. Additional discovery of new biomarkers and improvement on laboratory techniques seem necessary for achieving a molecular diagnosis of stroke.