Growing evidence links COVID-19 with acute and long-term neurological dysfunction. However, the pathophysiological mechanisms resulting in central nervous system involvement remain unclear, posing both diagnostic and therapeutic challenges. Here we show outcomes of a cross-sectional clinical study (NCT04472013) including clinical and imaging data and corresponding multidimensional characterization of immune mediators in the cerebrospinal fluid (CSF) and plasma of patients belonging to different Neuro-COVID severity classes. The most prominent signs of severe Neuro-COVID are blood-brain barrier (BBB) impairment, elevated microglia activation markers and a polyclonal B cell response targeting self-antigens and non-self-antigens. COVID-19 patients show decreased regional brain volumes associating with specific CSF parameters, however, COVID-19 patients characterized by plasma cytokine storm are presenting with a non-inflammatory CSF profile. Post-acute COVID-19 syndrome strongly associates with a distinctive set of CSF and plasma mediators. Collectively, we identify several potentially actionable targets to prevent or intervene with the neurological consequences of SARS-CoV-2 infection.

Background and Purpose— Commonly used tools to determine functional outcome after aneurysmal subarachnoid hemorrhage (aSAH) have limitations. Time spent at the patient’s home has previously been proposed as a robust outcome measure after ischemic stroke. Here, we set out to validate home-time as an outcome measure after aSAH. Methods— We examined prospectively collected data from a nationwide multicenter registry of aSAH patients admitted to a tertiary neurosurgical department in Switzerland (Swiss SOS [Swiss Study on Aneurysmal Subarachnoid Hemorrhage]; 2009–2015). We calculated mean home-time (defined as days spent at home for the first 90 days after aSAH) and 95% CIs for each category of modified Rankin Scale at discharge and 1-year follow-up, using linear regression models to analyze home-time differences per modified Rankin Scale category. Results— We had home-time data from 1076 of 1866 patients (57.7%), and multiple imputation was used to fill-in missing data from the remaining 790 patients. Increasing home-time was associated with improved modified Rankin Scale scores at time of hospital discharge ( P <0.0001) and at 1-year follow-up ( P <0.0001). Within each of the 8 participating hospitals, the relationship between home-time and modified Rankin Scale was maintained. Conclusions— Home-time for the first 90 days after aSAH offers a robust and easily ascertainable outcome measure, discriminating particularly well across better recovery levels at time of hospital discharge and at 1-year follow-up. This measure complies with the modern trend of patient-centered healthcare and research, representing an outcome that is particularly relevant to the patient. Clinical Trial Registration— URL: https://clinicaltrials.gov . Unique identifier: NCT03245866.

BACKGROUND Current prognostic tools in aneurysmal subarachnoid hemorrhage (aSAH) are constrained by being primarily based on patient and disease characteristics on admission. OBJECTIVE To develop and validate a complication- and treatment-aware outcome prediction tool in aSAH. METHODS This cohort study included data from an ongoing prospective nationwide multicenter registry on all aSAH patients in Switzerland (Swiss SOS [Swiss Study on aSAH]; 2009-2015). We trained supervised machine learning algorithms to predict a binary outcome at discharge (modified Rankin scale [mRS] ≤ 3: favorable; mRS 4-6: unfavorable). Clinical and radiological variables on admission (“Early” Model) as well as additional variables regarding secondary complications and disease management (“Late” Model) were used. Performance of both models was assessed by classification performance metrics on an out-of-sample test dataset. RESULTS Favorable functional outcome at discharge was observed in 1156 (62.0%) of 1866 patients. Both models scored a high accuracy of 75% to 76% on the test set. The “Late” outcome model outperformed the “Early” model with an area under the receiver operator characteristics curve (AUC) of 0.85 vs 0.79, corresponding to a specificity of 0.81 vs 0.70 and a sensitivity of 0.71 vs 0.79, respectively. CONCLUSION Both machine learning models show good discrimination and calibration confirmed on application to an internal test dataset of patients with a wide range of disease severity treated in different institutions within a nationwide registry. Our study indicates that the inclusion of variables reflecting the clinical course of the patient may lead to outcome predictions with superior predictive power compared to a model based on admission data only.

Collaterals from the ophthalmic artery are frequent in Moyamoya disease. Their development depends on the perfusion needs of the anterior cerebral artery territories. Three other systems of compensation could be present (callosal circle, leptomeningeal anastomosis, and duro-pial anastomoses).

Importance Growing evidence suggests that coronavirus disease 2019 (COVID-19) is associated with neurological sequelae. However, the underlying pathophysiological mechanisms resulting in central nervous system (CNS) derogation remain unclear. Objective To identify severity-dependent immune mechanisms in the cerebrospinal fluid (CSF) and plasma of COVID-19 patients and their association with brain imaging alterations. Design Prospective cross-sectional cohort study. Setting This study was performed from August 2020 to April 2021. Participants were enrolled in the outpatient clinics, hospital wards and intensive care units (ICU) of two clinical sites in Basel and Zurich, Switzerland. Participants Age >18 years and a positive SARS-CoV-2 test result were inclusion criteria. Potentially matching individuals were identified (n=310), of which 269 declined to participate and 1 did not match inclusion criteria. Paired CSF and plasma samples, as well as brain images, were acquired. The COVID-19 cohort (n=40; mean [SD] age, 54 [20] years; 17 women (42%)) was prospectively assorted by neurological symptom severity (classes I, II and III). Age/sex-matched inflammatory (n=25) and healthy (n=25) CSF and plasma control samples were obtained. For volumetric brain analysis, a healthy age/sex-matched control cohort (n=36) was established. Exposures Lumbar puncture, blood sampling and cranial MRI and/or CT. Main outcomes and measures Proteomics, standard parameters and antibody profiling of paired CSF and plasma samples in COVID-19 patients and controls. Brain imaging and gray matter volumetric analysis in association with biomarker profiles. Follow-up after 10-months. Results COVID-19 patients displayed a plasma cytokine storm but a non-inflammatory CSF profile. Class III patients displayed signs of blood-brain barrier (BBB) impairment and a polyclonal B cell response targeting self- and non-self antigens. Decreased regional brain volumes were present in COVID-19 patients and associated with specific CSF and plasma parameters. Conclusion and relevance Neuro-COVID class III patients had a strong, peripheral immune response resulting in (1) BBB impairment (2) ingress of (auto-)antibodies, (3) microglia activation and neuronal damage signatures. Our data point towards several potentially actionable targets that may be addressed to prevent COVID-19-related neurological sequelae. Trial registration