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Although CSF analysis routinely enables the diagnosis of neurological diseases, it is mainly used for the gross distinction between infectious, autoimmune inflammatory, and degenerative disorders of the CNS. To investigate, whether a multi-dimensional cellular blood and CSF characterization can support the diagnosis of clinically similar neurological diseases, we analysed 546 patients with autoimmune neuroinflammatory, degenerative, or vascular conditions in a cross-sectional retrospective study. By combining feature selection with dimensionality reduction and machine learning approaches we identified pan-disease parameters that were altered across all autoimmune neuroinflammatory CNS diseases and differentiated them from other neurological conditions and inter-autoimmunity classifiers that subdifferentiate variants of CNS-directed autoimmunity. Pan-disease as well as diseases-specific changes formed a continuum, reflecting clinical disease evolution. A validation cohort of 231 independent patients confirmed that combining multiple parameters into composite scores can assist the classification of neurological patients. Overall, we showed that the integrated analysis of blood and CSF parameters improves the differential diagnosis of neurological diseases, thereby facilitating early treatment decisions.

Objective: To analyze why numerous acute stroke treatments were successful in the laboratory but failed in large clinical trials.Methods: We searched all phase 3 trials of medical treatments for acute ischemic stroke and corresponding early clinical and experimental studies. We compared the overall efficacy and assessed the impact of publication bias and study design on the efficacy. Furthermore, we estimated power and true report probability of experimental studies.Results: We identified 50 phase 3 trials with 46,008 subjects, 75 early clinical trials with 12,391 subjects, and 209 experimental studies with >7,141 subjects. Three (6%) phase 3, 24 (32%) early clinical, and 143 (69.08%) experimental studies were positive. The mean treatment effect was 0.76 (95% confidence interval [CI] = 0.70-0.83) in experimental studies, 0.87 (95% CI = 0.71-1.06) in early clinical trials, and 1.00 (95% CI = 0.95-1.06) in phase 3 trials. Funnel plot asymmetry and trim-and-fill revealed a clear publication bias in experimental studies and early clinical trials. Study design and adherence to quality criteria had a considerable impact on estimated effect sizes. The mean power of experimental studies was 17%. Assuming a bias of 30% and pre-study odds of 0.5 to 0.7, this leads to a true report probability of <50%.Interpretation: Pivotal study design differences between experimental studies and clinical trials, including different primary end points and time to treatment, publication bias, neglected quality criteria and low power, contribute to the stepwise efficacy decline of stroke treatments from experimental studies to phase 3 clinical trials. Even under conservative estimates, less than half of published positive experimental stroke studies are truly positive. ANN NEUROL 2020;87:40-51. [ABSTRACT FROM AUTHOR]

Demyelination of corticospinal tract neurons contributes to long‐term disability after cortical stroke. Nonetheless, poststroke myelin loss has not been addressed as a therapeutic target, so far. We hypothesized that an antibody‐mediated inhibition of the Nogo receptor‐interacting protein (LINGO‐1, leucine‐rich repeat and immunoglobulin domain‐containing Nogo receptor‐interacting protein) may counteract myelin loss, enhance remyelination and axonal growth, and thus promote functional recovery following stroke. To verify this hypothesis, mice were subjected to photothrombotic stroke and received either an antibody against LINGO‐1 (n = 19) or a control treatment (n = 18). Behavioral tests were performed to assess the effects of anti‐LINGO‐1 treatment on the functional recovery. Seven weeks after stroke, immunohistochemical analyses were performed to analyze the effect of anti‐LINGO‐1 treatment on myelination and axonal loss of corticospinal tract neurons, proliferation of oligodendrocytes and neurogenesis. Anti‐LINGO‐1 treatment resulted in significantly improved functional recovery (p < 0.0001, repeated measures analysis of variance), and increased neurogenesis in the hippocampus and subventricular zone of the ipsilateral hemisphere (p = 0.0094 and p = 0.032, t‐test). Notably, we observed a significant increase in myelin (p = 0.0295, t‐test), platelet‐derived growth factor receptor α‐positive oligodendrocyte precursor cells (p = 0.0356, t‐test) and myelinating adenomatous polyposis coli‐positive cells within the ipsilateral internal capsule of anti‐LINGO‐1‐treated mice (p = 0.0021, t‐test). In conclusion, we identified anti‐LINGO‐1 as the first neuroregenerative treatment that counteracts poststroke demyelination of corticospinal tract neurons, presumably by increased proliferation of myelin precursor cells, and thereby improves functional recovery. Most importantly, our study presents myelin loss as a novel therapeutic target following stroke. [ABSTRACT FROM AUTHOR]

Inflammatory causes of stroke are frequent and often pose diagnostic and therapeutic challenges due to the scarcity of randomized trials and the absence of clear guideline recommendations for many scenarios. Following the publication of the recommendations of the European Stroke Organization on primary angiitis of the central nervous system (PACNS) last year, the German Neurological Society (DGN) has issued very clear guidelines this year on the diagnostics and treatment of PACNS and updated the recommendations for systemic vasculitides; however, stroke often occurs not only as a result of primary vascular inflammation but also as a complication of another organ infection. Approximately 5% of all patients with sepsis, ca. 20% of patients with bacterial meningitis and up to 40% of patients with bacterial endocarditis suffer from a stroke as a complication. This article summarizes the key characteristics of these inflammatory causes of stroke and particularly focuses on the current recommendations for diagnostic and therapeutic management., (© 2024. The Author(s).)

Background and Purpose: Automated perfusion imaging can detect stroke patients with unknown time of symptom onset who are eligible for thrombolysis. However, the availability of this technique is limited. We, therefore, established the novel concept of computed tomography (CT) hypoperfusion-hypodensity mismatch, i.e., an ischemic core lesion visible on cerebral perfusion CT without visible hypodensity in the corresponding native cerebral CT. We compared both methods regarding their accuracy in identifying patients suitable for thrombolysis., Methods: In a retrospective analysis of the MissPerfeCT observational cohort study, patients were classified as suitable or not for thrombolysis based on established time window and imaging criteria. We calculated predictive values for hypoperfusion-hypodensity mismatch and automated perfusion imaging to compare accuracy in the identification of patients suitable for thrombolysis., Results: Of 247 patients, 219 (88.7%) were eligible for thrombolysis and 28 (11.3%) were not eligible for thrombolysis. Of 197 patients who were within 4.5 h of symptom onset, 190 (96.4%) were identified by hypoperfusion-hypodensity mismatch and 88 (44.7%) by automated perfusion mismatch ( p  < 0.001). Of 22 patients who were beyond 4.5 h of symptom onset but were eligible for thrombolysis, 5 patients (22.7%) were identified by hypoperfusion-hypodensity mismatch. Predictive values for the hypoperfusion-hypodensity mismatch vs. automated perfusion mismatch were as follows: sensitivity, 89.0% vs. 50.2%; specificity, 71.4% vs. 100.0%; positive predictive value, 96.1% vs. 100.0%; and negative predictive value, 45.5% vs. 20.4%., Conclusion: The novel method of hypoperfusion-hypodensity mismatch can identify patients suitable for thrombolysis with higher sensitivity and lower specificity than established techniques. Using this simple method might therefore increase the proportion of patients treated with thrombolysis without the use of special automated software.The MissPerfeCT study is a retrospective observational multicenter cohort study and is registered with clinicaltrials.gov (NCT04277728)., Competing Interests: JM has received grants from Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung (BMBF), Else KrönerFresenius-Stiftung, EVER Pharma Jena GmbH, and Ferrer International, travel grants from Boehringer Ingelheim, and speaking fees from Bayer Vital and Chugai Pharma. MD has received honoraria for lectures from Bayer Vital and Sanofi Genzyme. Consultant for Hovid Berhad and Roche Pharma. CL received consulting and speaker’s honoraria from Biogen Idec, Bayer Schering, Bristol-Myers Squibb, Daiichi Sanykyo, Merck Serono, Novartis, Sanofi, Genzyme and TEVA. JF has received grants from German Ministry of Science and Education (BMBF), German Ministry of Economy and Innovation (BMWi), German Research Foundation (DFG), European Union (EU), Hamburgische Investitions- und Förderbank (IFB), Medtronic, Microvention, Route92, Stryker. Consultant for: Acandis, Bayer, Boehringer Ingelheim, Cerenovus, Evasc Neurovascular, MD Clinicals, Medtronic, Microvention, Penumbra, Phenox, Stryker, Transverse Medical. Stock holder: Tegus Medical. CK has received honoraria and travel grants from Bayer Vital and Daiichi-Sankyo. DK receives a grant from Else Kröner-Fresenius-Center for Digital Health. PS has received grants from Siemens and Penumbra. Consultant for: Penumbra, Phenox, Stryker, Cerus endovascular. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Sporns, Kemmling, Meyer, Krogias, Puetz, Thierfelder, Duering, Lukas, Kaiser, Langner, Brehm, Rotkopf, Kunz, Beuker, Heindel, Fiehler, Schramm, Wiendl, Minnerup, Psychogios and Minnerup.)