Background and Purpose: Case series indicating cerebrovascular disorders in coronavirus disease 2019 (COVID-19) have been published. Comprehensive workups, including clinical characteristics, laboratory, electroencephalography, neuroimaging, and cerebrospinal fluid findings, are needed to understand the mechanisms. Methods: We evaluated 32 consecutive critically ill patients with COVID-19 treated at a tertiary care center from March 9 to April 3, 2020, for concomitant severe central nervous system involvement. Patients identified underwent computed tomography, magnetic resonance imaging, electroencephalography, cerebrospinal fluid analysis, and autopsy in case of death. Results: Of 32 critically ill patients with COVID-19, 8 (25%) had severe central nervous system involvement. Two presented with lacunar ischemic stroke in the early phase and 6 with prolonged impaired consciousness after termination of analgosedation. In all but one with delayed wake-up, neuroimaging or autopsy showed multiple cerebral microbleeds, in 3 with additional subarachnoid hemorrhage and in 2 with additional small ischemic lesions. In 3 patients, intracranial vessel wall sequence magnetic resonance imaging was performed for the first time to our knowledge. All showed contrast enhancement of vessel walls in large cerebral arteries, suggesting vascular wall pathologies with an inflammatory component. Reverse transcription-polymerase chain reactions for SARS-CoV-2 in cerebrospinal fluid were all negative. No intrathecal SARS-CoV-2-specific IgG synthesis was detectable. Conclusions: Different mechanisms of cerebrovascular disorders might be involved in COVID-19. Acute ischemic stroke might occur early. In a later phase, microinfarctions and vessel wall contrast enhancement occur, indicating small and large cerebral vessels involvement. Central nervous system disorders associated with COVID-19 may lead to long-term disabilities. Mechanisms should be urgently investigated to develop neuroprotective strategies.

Background Comprehensive data on the cerebrospinal fluid (CSF) profile in patients with COVID-19 and neurological involvement from large-scale multicenter studies are missing so far. Objective To analyze systematically the CSF profile in COVID-19. Methods Retrospective analysis of 150 lumbar punctures in 127 patients with PCR-proven COVID-19 and neurological symptoms seen at 17 European university centers Results The most frequent pathological finding was blood-CSF barrier (BCB) dysfunction (median QAlb 11.4 [6.72–50.8]), which was present in 58/116 (50%) samples from patients without pre-/coexisting CNS diseases (group I). QAlb remained elevated > 14d (47.6%) and even > 30d (55.6%) after neurological onset. CSF total protein was elevated in 54/118 (45.8%) samples (median 65.35 mg/dl [45.3–240.4]) and strongly correlated with QAlb. The CSF white cell count (WCC) was increased in 14/128 (11%) samples (mostly lympho-monocytic; median 10 cells/µl, > 100 in only 4). An albuminocytological dissociation (ACD) was found in 43/115 (37.4%) samples. CSF l-lactate was increased in 26/109 (24%; median 3.04 mmol/l [2.2–4]). CSF-IgG was elevated in 50/100 (50%), but was of peripheral origin, since QIgG was normal in almost all cases, as were QIgA and QIgM. In 58/103 samples (56%) pattern 4 oligoclonal bands (OCB) compatible with systemic inflammation were present, while CSF-restricted OCB were found in only 2/103 (1.9%). SARS-CoV-2-CSF-PCR was negative in 76/76 samples. Routine CSF findings were normal in 35%. Cytokine levels were frequently elevated in the CSF (often associated with BCB dysfunction) and serum, partly remaining positive at high levels for weeks/months (939 tests). Of note, a positive SARS-CoV-2-IgG-antibody index (AI) was found in 2/19 (10.5%) patients which was associated with unusually high WCC in both of them and a strongly increased interleukin-6 (IL-6) index in one (not tested in the other). Anti-neuronal/anti-glial autoantibodies were mostly absent in the CSF and serum (1509 tests). In samples from patients with pre-/coexisting CNS disorders (group II [N = 19]; including multiple sclerosis, JC-virus-associated immune reconstitution inflammatory syndrome, HSV/VZV encephalitis/meningitis, CNS lymphoma, anti-Yo syndrome, subarachnoid hemorrhage), CSF findings were mostly representative of the respective disease. Conclusions The CSF profile in COVID-19 with neurological symptoms is mainly characterized by BCB disruption in the absence of intrathecal inflammation, compatible with cerebrospinal endotheliopathy. Persistent BCB dysfunction and elevated cytokine levels may contribute to both acute symptoms and ‘long COVID’. Direct infection of the CNS with SARS-CoV-2, if occurring at all, seems to be rare. Broad differential diagnostic considerations are recommended to avoid misinterpretation of treatable coexisting neurological disorders as complications of COVID-19.

Secondary brain injury after aneurysmal subarachnoid hemorrhage (SAH-SBI) contributes to poor outcomes in patients after rupture of an intracranial aneurysm. The lack of diagnostic biomarkers and novel drug targets represent an unmet need. The aim of this study was to investigate the clinical and pathophysiological association between cerebrospinal fluid hemoglobin (CSF-Hb) and SAH-SBI. In a cohort of 47 patients, we collected daily CSF-samples within 14 days after aneurysm rupture. There was very strong evidence for a positive association between spectrophotometrically determined CSF-Hb and SAH-SBI. The accuracy of CSF-Hb to monitor for SAH-SBI markedly exceeded that of established methods (AUC: 0.89 [0.85-0.92]). Temporal proteome analysis revealed erythrolysis accompanied by an adaptive macrophage response as the two dominant biological processes in the CSF-space after aneurysm rupture. Ex-vivo experiments on the vasoconstrictive and oxidative potential of Hb revealed critical inflection points overlapping CSF-Hb thresholds in patients with SAH-SBI. Selective depletion and in-solution neutralization by haptoglobin or hemopexin efficiently attenuated the vasoconstrictive and lipid peroxidation activities of CSF-Hb. Collectively, the clinical association between high CSF-Hb levels and SAH-SBI, the underlying pathophysiological rationale, and the favorable effects of haptoglobin and hemopexin in ex-vivo experiments position CSF-Hb as a highly attractive biomarker and potential drug target.

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Recognition of typical patterns of brain response to external stimuli using near-infrared spectroscopy (fNIRS) may become a gateway to detecting covert consciousness in clinically unresponsive patients. This is the first fNIRS study on the cortical hemodynamic response to favorite music using a frequency domain approach. The aim of this study was to identify a possible marker of cognitive response in healthy subjects by investigating variations in the oscillatory signal of fNIRS in the spectral regions of low-frequency (LFO) and very-low-frequency oscillations (VLFO). The experiment consisted of two periods of exposure to preferred music, preceded and followed by a resting phase. Spectral power in the LFO region increased in all the subjects after the first exposure to music and decreased again in the subsequent resting phase. After the second music exposure, the increase in LFO spectral power was less distinct. Changes in LFO spectral power were more proGfirst music exposure and the repetition-related habituation effect strongly suggest a cerebral origin of the fNIRS signal. Recognition of typical patterns of brain response to specific environmental stimulation is a required step for the concrete validation of a fNIRS-based diagnostic tool.

Explainable AI (XAI) is considered the number one solution for overcoming implementation hurdles of AI/ML in clinical practice. However, it is still unclear how clinicians and developers interpret XAI (differently) and whether building such systems is achievable or even desirable. This longitudinal multi-method study queries (n=112) clinicians and developers as they co-developed the DCIP – an ML-based prediction system for Delayed Cerebral Ischemia. The resulting framework reveals that ambidexterity between exploration and exploitation can help bridge opposing goals and requirements to improve the design and implementation of AI/ML in healthcare.

Explainable artificial intelligence (XAI) has emerged as a promising solution for addressing the implementation challenges of AI/ML in healthcare. However, little is known about how developers and clinicians interpret XAI and what conflicting goals and requirements they may have. This paper presents the findings of a longitudinal multi-method study involving 112 developers and clinicians co-designing an XAI solution for a clinical decision support system. Our study identifies three key differences between developer and clinician mental models of XAI, including opposing goals (model interpretability vs. clinical plausibility), different sources of truth (data vs. patient), and the role of exploring new vs. exploiting old knowledge. Based on our findings, we propose design solutions that can help address the XAI conundrum in healthcare, including the use of causal inference models, personalized explanations, and ambidexterity between exploration and exploitation mindsets. Our study highlights the importance of considering the perspectives of both developers and clinicians in the design of XAI systems and provides practical recommendations for improving the effectiveness and usability of XAI in healthcare.

Target temperature management with the new automated infusion device is feasible. Although we provided first data regarding safety, further controlled randomized studies are needed to evaluate the long-time safety, as well as the best indications and timing for this cooling device.