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Background and Aim: Explicit diagnostic criteria for transient ischemic attack (TIA) (EDCT) have been recently proposed based on the assumption, that a migraine aura-like symptom is not typical for a TIA. However, migraine-like symptoms have been unexpectedly frequent in patients with confirmed ischemic stroke. This cross-sectional study aimed to field-test the EDCT to distinguish transient neurological symptoms caused by cerebral infarction from those caused by migraine aura., Methods: The sensitivity, specificity, positive and negative predictive values of the EDCT score were calculated in samples of patients with (i) transient symptoms caused by cerebral infarction confirmed by imaging and (ii) patients with migraine with aura diagnosed according to the International Classification of Headache Disorders 3rd edition. Sensitivity, specificity, positive and negative predictive values of the original and modified EDCT were calculated, as well as area under the curve adjusted for age and sex using the logistic regression method., Results: The study population included 59 patients with cerebral infarction and 324 patients with migraine with aura. The median age of the stroke group was 72 (IQR 61-81) and of the migraine group 39 (IQR 29-53). There were 36 (61%) men in the stroke group and 221 (68%) women in the migraine group. For the detection of TIA with imaging-proven cerebral infarction, the original EDCT had a sensitivity of 90% (95%CI 79-96), a specificity 77% (95%CI 72-82), a positive predictive value of 42% (95%CI 33-51), and the negative predictive value 98% (95% CI 95-99). For the modified EDCT, the sensitivity was 81% (95%CI 69-90), the specificity 97% (95%CI 94-98), the positive predictive value 81% (95%CI 69-90), and the negative predictive value 97% (95%CI 94-98)., Conclusions: The original and modified EDCT criteria miss up to 1 of 10 and 1 of 5 patients, respectively, with transient symptoms due to cerebral infarction. However, the modified EDCT criteria are more specific but less sensitive in detection of ischemic events. The optimal combination of clinical markers to reliably distinguish TIA from migraine aura remains to be found., Competing Interests: Declarations. Conflicts of interest: AS received research support from Swiss Heart Foundation and TEVA pharmaceuticals. MB reports research support from the Department of Neurology, Inselspital, and the University of Bern, Switzerland. TRM reports grants from the Bangerter-Rhyner Foundation, the Baasch-Medicus Foundation, the University of Bern, the Swiss National Science Foundation and the Swiss Heart Foundation. MA reports speaker honoraria from Astra Zeneca, Bayer, Covidien, Medtronic, Sanofi and honoraria for scientific advisory boards from Amgen, Bayer, BMS, Daiichi Sankyo, Medtronic, Pfizer, and research funding from the Swiss National Science Foundation (SNSF), and the Swiss Heart Foundation (SHF). UF reports financial support for the SWIFT DIRECT trial (Medtronic), research grants from Medtronic BEYOND SWIFT registry, SNSF, SHF, consulting fees from Medtronic, Stryker and CSL Behring (fees paid to institution); membership of a Data Safety Monitoring Board for the IN EXTREMIS trial and TITAN trial and Portola (Alexion) Advisory board (fees paid to institution). HPM was neurology principal investigator of the PC-Trial, was member of the steering committee of the PRIMA Trial, and reports consultancy fees from Medtronic, Stryker and Cerenovus. JO owns stock in Novo Nordisk, Moberg Pharma and Cephagenix. SJ reports grants from the Swiss National Science Foundation and the Swiss Heart Foundation. CJS reports consulting, Advisory Boards, Speaker, Travel Support for/from Abbvie, Allergan, Almirall, Amgen, Eli Lilly, Grnenthal, Lundbeck, MindMed, Novartis, Pfizer and TEVA Pharmaceuticals. All other authors have nothing to disclose., (© 2024. The Author(s).)

Background and Objectives: A better understanding of the factors influencing D-dimer levels in code stroke patients is needed to guide further investigations of concomitant thrombotic conditions. This study aimed to investigate the impact of time from symptom onset and other factors on D-dimer levels in patients with acute ischemic stroke (AIS) or transient ischemic attack (TIA)., Methods: Data on consecutive AIS and TIA patients treated at our tertiary-care stroke center between January 2015 and December 2020 were retrospectively assessed. Patients with available D-dimer levels were evaluated for eligibility. Multivariable non-linear regression analyses were performed., Results: In total, 2467 AIS patients and 708 TIA patients were included. The median D-dimer levels differed between the AIS and TIA groups (746 µg/L [interquartile range 381-1468] versus 442 µg/L [interquartile range 244-800], p<0.001). In AIS patients, an early increase in D-dimer levels was demonstrated within the first 6 h (standardized beta coefficient [β] 0.728; 95% confidence interval [CI] 0.324-1.121). This was followed by an immediate decrease (β -13.022; 95% CI -20.401 to -5.643) and then by a second, late increase after 35 h (β 11.750; 95% CI 4.71-18.791). No time-dependent fluctuation in D-dimer levels was observed in TIA patients., Conclusion: The time from symptom onset may affect D-dimer levels in patients with AIS but not those with TIA. Further studies confirming these findings and validating time-specific variations are needed to enable D-dimer levels to be used efficiently as an acute stroke and thrombotic risk biomarker., Competing Interests: Declaration of competing interest Dr. Arnold reports personal fees from Bayer, Bristol-Myers Squibb, Medtronic, Amgen, Daiichi Sankyo, Nestlé Health Sciences, Boehringer Ingelheim, and Covidien during the conduct of the study. Dr. Jung reports grants from the Swiss National Science Foundation and the Swiss Heart Foundation. Dr. Beyeler reports research support from the Department of Neurology, Inselspital, Bern University Hospital and the University of Bern, Switzerland. None of the other authors report any conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background This study was conducted to explore the association of different phenotypes, count, and location of chronic covert brain infarctions (CBIs) with detection of atrial fibrillation (AF) on prolonged post-stroke cardiac rhythm monitoring (PCM). Methods and Results We conducted a cohort single-center study of consecutive first-ever ischemic stroke or transient ischemic attack patients undergoing PCM between January 2015 and December 2017. We blindly rated CBI phenotypes according to established definitions and white matter hyperintensities (WMHs) according to the age-related white matter changes rating scale. We used (multiple) regression models to assess the association of the imaging biomarkers and incident AF on PCM. A total of 795 patients (median [interquartile range]) aged 69 (57-78) years, 41% women, median National Institutes of Health Stroke Scale score 2 (0-5), median PCM duration 14 (7-14) days, and AF detection in 61 patients (7.7%) were included. On univariate analysis, WMHs (per point odds ratio, 1.35 [95% CI, 1.03-1.78]) but not CBIs (odds ratio, 0.90 [95% CI, 0.52-1.56]) were associated with AF detection. Neither CBI phenotype, count, nor location were associated with AF detection. After adjustment for age, hypertension, and stroke severity, neither increasing WMHs (per point adjusted odds ratio, 0.85 [95% CI, 0.60-1.20]) nor CBIs (adjusted odds ratio, 0.60 [95% CI, 0.33-1.09]) were independently associated with AF detection. Conclusions Although WMHs and CBIs represent surrogate biomarkers of vascular risk factors, neither WMHs nor CBIs, including their phenotypes, count, and location, were independently associated with AF detection on PCM. In patients with manifest ischemic stroke or transient ischemic attack, the presence of imaging biomarkers of chronic ischemic injury does not seem promising to further refine prediction tools for AF detection on PCM.

Background and Purpose: To investigate the association of different phenotypes, count, and locations of chronic covert brain infarctions (CBI) with long-term mortality in patients with first-ever manifest acute ischemic stroke (AIS) or transient ischemic attack (TIA). Additionally, to analyze their potential interaction with white matter hyperintensities (WMH) and predictive value in addition to established mortality scores., Methods: Single-center cohort study including consecutive patients with first-ever AIS or TIA with available MRI imaging from January 2015 to December 2017. Blinded raters adjudicated CBI phenotypes and WMH (age-related white matter changes score) according to established definitions. We compared Cox regression models including prespecified established predictors of mortality using Harrell's C and likelihood ratio tests., Results: A total of 2236 patients (median [interquartile range] age: 71 [59-80] years, 43% female, National Institutes of Health Stroke Scale: 2 [1-6], median follow-up: 1436 days, 21% death during follow-up) were included. Increasing WMH (per point adjusted Hazard Ratio [aHR] = 1.29 [1.14-1.45]), but not CBI (aHR = 1.21 [0.99-1.49]), were independently associated with mortality. Neither CBI phenotype, count, nor location was associated with mortality and there was no multiplicative interaction between CBI and WMH (p &gt; .1). As compared to patients without CBI or WMH, patients with moderate or severe WMH and additional CBI had the highest hazards of death (aHR = 1.62 [1.23-2.13]). The Cox regression model including CBI and WMH had a small but significant increment in Harrell's C when compared to the model including 14 clinical variables (0.831 vs. 0.827, p &lt; .001)., Discussion: WMH represent a strong surrogate biomarker of long-term mortality in first-ever manifest AIS or TIA patients. CBI phenotypes, count, and location seem less relevant. Incorporation of CBI and WMH slightly improves predictive capacity of established risk scores., (© 2022 The Authors. Journal of Neuroimaging published by Wiley Periodicals LLC on behalf of American Society of Neuroimaging.)

Background We aimed to determine the diagnostic yield of transthoracic (TTE) and transesophageal echocardiography (TEE) in patients with ischemic stroke and transient ischemic attack with established indications for direct oral anticoagulants before the index event. Methods and Results This was a retrospective cohort study of consecutive patients with preceding established indications for long-term therapeutic direct oral anticoagulants presenting to a single comprehensive stroke center with ischemic stroke or transient ischemic attack. Choice of echocardiography modality was based on expert recommendations. The primary outcome was a composite of prespecified management-relevant high-risk findings adjudicated by an expert panel, based on TTE and TEE reports according to evidence-based recommendations. Explorative analyses were performed to identify biomarkers associated with the primary outcome. Of 424 patients included (median [interquartile range] age, 78 [70-84] years; 175 [41%] women; National Institutes of Health Stroke Scale, 4 [1-12]; 67% atrial fibrillation), 292 (69%) underwent echocardiography, while 132 (31%) did not. Modality was TTE in 191 (45%) and TEE in 101 (24%). Median time from index event to echocardiography was 2 (1-3) days. TTE identified 26 of 191 (14%) patients with 35 management-relevant pathologies. TEE identified 16 of 101(16%) patients with 20 management-relevant pathologies. Most management-relevant findings represented indicated coronary artery disease and valvular pathologies. In a further 3 of 191 (2%) patients with TTE and 4 of 101 (4%) patients with TEE, other relevant findings were identified. Variables associated with management-relevant high-risk pathologies included more severe stroke, diabetes, and laboratory biomarkers (NT-proBNP [N-terminal pro-B-type natriuretic peptide], C-reactive protein, d-dimer, and troponin levels). Conclusions In patients with established indications for long-term direct oral anticoagulant therapy and stroke who received echocardiography, both TTE and TEE identified a relevant and similar proportion of management-relevant high-risk pathologies and predictive biomarkers could help to guide diagnostic workup in such patients.

Background This study was conducted to compare frequencies of chronic brain infarctions (CBIs) and white matter hyperintensities (WMHs) as well as their associations with established early recurrence risk scores in patients with transient ischemic attack (TIA) and stroke mimics compared with ischemic stroke. Methods and Results Single-center cohort study including consecutive patients with TIA, stroke mimics, and acute ischemic stroke, with available magnetic resonance imaging from January 2015 to December 2017. Blinded raters adjudicated WMH (age-related white matter changes score) and CBI according to established definitions. A total of 2112 patients (median [Q1-Q3] age 71 [59-80] years, 43% women, National Institutes of Health Stroke Scale score of 2 [1-7], 80% ischemic stroke, 18% TIA, 2% stroke mimics) were included. While CBIs were present in only 10% of patients with stroke mimic, they were detected in 28% of TIAs and 38% of ischemic strokes ( P <0.001). WMHs were less pronounced (0, 0-1) in patients with stroke mimic, but there was no difference between TIA (1, 1-2) and ischemic stroke (0, 1-2) patients. CBIs (adjusted odds ratio, 0.3; 95% CI, 0.1-0.9) were associated with a lower rate of stroke mimic as the final diagnosis, while WMHs were not (adjusted odds ratio per point, 1.3; 95% CI, 0.7-2.2). WMH (β per point, 0.4; 95% CI, 0.3-0.6) and presence of CBI (β, 0.6; 95% CI, 0.3-0.9) were associated with a higher cardiovascular risk profile according to the ABCD3-I score. The accuracy of prediction was good for high-risk TIA (cross-validated area under the receiver operating characteristic curve, 0.89; 95% CI, 0.79-0.93) on the basis of brain imaging, age, and sex. Conclusions CBI and WMH differ between patients with stroke mimic and patients with TIA/ischemic stroke and are closely associated with established recurrence risk scores. Prospective studies need to clarify whether including brain frailty markers may contribute to the refinement of current management algorithms and risk stratifications.