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Maenia Scarpino,1 Giovanni Lanzo,1 Francesco Lolli,2 Antonello Grippo3 1Unit of Neurophysiopathology, Neuromuscolar Department, AOU Careggi, Florence, Italy; 2Neuroscience Department (NEUROFARBA), University of Florence, Florence, Italy; 3Intensive Rehabilitation Unit, IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy Abstract: Cerebral fat embolism (CFE) is an uncommon incomplete type of fat embolism syndrome (FES), characterized by purely cerebral involvement. It usually occurs 12–72 hours after the initial trigger, mainly represented by closed, long-bone multiple fractures of the lower extremities. Neurological manifestations are mainly characterized by headache, confusion, seizures, focal deficit, and alteration of the consciousness state up to coma onset. It represents a diagnostic challenge, above all when secondary to uncommon nontraumatic causes, because neurological signs and symptoms are variable and nonspecific, not satisfying the Gurd and Wilson’s criteria, the diagnostic features most widely used today for FES diagnosis. Neuroimaging (mainly MRI, but in some cases, brain computed tomography too) can hasten the diagnosis, avoiding other unnecessary investigations and treatment. Usually self-limiting, CFE may sometimes be fatal. Treatment is to date mainly supportive and prophylactic strategies are considered an important tool to decrease the development of fat embolism and, consequently, the rate of CFE. Keywords: cerebral fat embolism, neurological deterioration, neuroimaging, prophylactic strategies

Objective Investigation of the utility of association between electroencephalogram ( EEG) and somatosensory-evoked potentials ( SEPs) for the prediction of neurological outcome in comatose patients resuscitated after cardiac arrest ( CA) treated with therapeutic hypothermia, according to different recording times after CA. Methods Glasgow Coma Scale, EEG and SEPs performed at 12, 24 and 48-72 h after CA were assessed in 200 patients. Outcome was evaluated by Cerebral Performance Category 6 months after CA. Results Within 12 h after CA, grade 1 EEG predicted good outcome and bilaterally absent ( BA) SEPs predicted poor outcome. Because grade 1 EEG and BA- SEPs were never found in the same patient, the recording of both EEG and SEPs allows us to correctly prognosticate a greater number of patients with respect to the use of a single test within 12 h after CA. At 48-72 h after CA, both grade 2 EEG and BA- SEPs predicted poor outcome with FPR=0.0%. When these neurophysiological patterns are both present in the same patient, they confirm and strengthen their prognostic value, but because they also occurred independently in eight patients, poor outcome is predictable in a greater number of patients. Significance The combination of EEG/ SEP findings allows prediction of good and poor outcome (within 12 h after CA) and of poor outcome (after 48-72 h). Recording of EEG and SEPs in the same patients allows always an increase in the number of cases correctly classified, and an increase of the reliability of prognostication in a single patient due to concordance of patterns. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Across Europe, more than one third of patients are diagnosed with HIV infection late. Late presentation for care has been associated with higher risk of clinical progression and mortality. In the present study, we evaluated the prevalence, epidemiological characteristics and survival probability of patients with late and very late presentation, newly diagnosed with HIV infection in Catania, Italy, from 1985 to 2010. PATIENTS AND METHODS: According to the European Consensus definition, Late Presenters (LP) were defined as subjects presenting for care with a CD4+ T-cell count below 350 cells/µl or with an AIDS-defining event, regardless of CD4+ T-cell count; patients with advanced HIV disease (Very Late Presenters) (VLP) were those presenting with a CD4+ T-cell count below 200 cells/µl or with an AIDS-defining event, regardless of CD4+ T-cell count. RESULTS: 620 patients were included in the study. 345 (55.6%) subjects were LP, 35% of them were asymptomatic; 246 (39.7%) were VLP. In univariate analysis, late presentation was related to age (p < 0.001), to heterosexual exposure to HIV infection (70% of heterosexual subjects were LP) (p < 0.005) and to being diagnosed during the calendar period from 1991 to 2000 (p < 0.001). Very late presentation was related to age (p < 0.001), male sex (p < 0.01), heterosexual risk (p < 0.001) and to being diagnosed during the calendar period from 1991 to 2000 (p < 0.001). In multivariate analysis, age (p < 0.0001), being older than 50 years old (p = 0.02), years of diagnosis 1991-1995 (p < 0.005) and 1996-2000 (p < 0.05) in the subgroup of late presenters and age (p < 0.0001), being older than 50 years old (p < 0.005), male sex (p < 0.0001), years of diagnosis 1991-1995 (p < 0.05) and 1996-2000 (p < 0.005) in the subgroup of very late presenters maintained statistical significance. The survival probability within LP and VLP group was statistically lower than no LP/VLP (log rank test p < 0.0005 and p < 0.0001, respectively). For both LP (p < 0.002) and VLP (p < 0.0001), survival probability was significantly lower in the pre-HAART era, in comparison with the period of mono/dual therapy and the HAART era. CONCLUSIONS: More than fifty percent of patients in our setting were diagnosed late with HIV infection and, consequently, treated late. Late and very late presentation were associated with lower survival probability. The implementation of strategies focused on targeted prevention efforts and HIV testing programs appears fundamental to diagnose and treat HIV infection as early as possible. [ABSTRACT FROM AUTHOR]

Unconsciousness in severe acquired brain injury (sABI) patients occurs with different cognitive and neural profiles. Perturbational approaches, which enable the estimation of proxies for brain reorganization, have added a new avenue for investigating the non-behavioural diagnosis of consciousness. In this prospective observational study, we conducted a comparative analysis of the topological patterns of heartbeat-evoked potentials (HEP) between patients experiencing a prolonged disorder of consciousness (pDoC) and patients emerging from a minimally consciousness state (eMCS). A total of 219 sABI patients were enrolled, each undergoing a synchronous EEG-ECG resting-state recording, together with a standardized consciousness diagnosis. A number of graph metrics were computed before/after the HEP (Before/After) using the R-peak on the ECG signal. The peak value of the global field power of the HEP was found to be significantly higher in eMCS patients with no difference in latency. Power spectrum was not able to discriminate consciousness neither Before nor After. Node assortativity and global efficiency were found to vary with different trends at unconsciousness. Lastly, the Perturbational Complexity Index of the HEP was found to be significantly higher in eMCS patients compared with pDoC. Given that cortical elaboration of peripheral inputs may serve as a non-behavioural determinant of consciousness, we have devised a low-cost and translatable technique capable of estimating causal proxies of brain functionality with an endogenous, non-invasive stimulus. Thus, we present an effective means to enhance consciousness assessment by incorporating the interaction between the autonomic nervous system (ANS) and central nervous system (CNS) into the loop., (© 2024 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Objective: Within the continuum of consciousness, patients in a Minimally Conscious State (MCS) may exhibit high-level behavioral responses (MCS+) or may not (MCS-). The evaluation of residual consciousness and related classification is crucial to propose tailored rehabilitation and pharmacological treatments, considering the inherent differences among groups in diagnosis and prognosis. Currently, differential diagnosis relies on behavioral assessments posing a relevant risk of misdiagnosis. In this context, EEG offers a non-invasive approach to model the brain as a complex network. The search for discriminating features could reveal whether behavioral responses in post-comatose patients have a defined physiological background. Additionally, it is essential to determine whether the standard behavioral assessment for quantifying responsiveness holds physiological significance., Methods: In this prospective observational study, we investigated whether low-density EEG-based graph metrics could discriminate MCS+/- patients by enrolling 57 MCS patients (MCS-: 30; males: 28). At admission to intensive rehabilitation, 30 min resting-state closed-eyes EEG recordings were performed together with consciousness diagnosis following international guidelines. After EEG preprocessing, graphs' metrics were estimated using different connectivity measures, at multiple connection densities and frequency bands (α,θ,δ). Metrics were also provided to cross-validated Machine Learning (ML) models with outcome MCS+/-., Results: A lower level of brain activity integration was found in the MCS- group in the α band. Instead, in the δ band MCS- group presented an higher level of clustering (weighted clustering coefficient) respect to MCS+. The best-performing solution in discriminating MCS+/- through the use of ML was an Elastic-Net regularized logistic regression with a cross-validation accuracy of 79% (sensitivity and specificity of 74% and 85% respectively)., Conclusion: Despite tackling the MCS+/- differential diagnosis is highly challenging, a daily-routine low-density EEG might allow to differentiate across these differently responsive brain networks., Significance: Graph-theoretical features are shown to discriminate between these two neurophysiologically similar conditions, and may thus support the clinical diagnosis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Consciousness can be defined as a phenomenological experience continuously evolving. Current research showed how conscious mental activity can be subdivided into a series of atomic brain states converging to a discrete spatiotemporal pattern of global neuronal firing. Using the high temporal resolution of EEG recordings in patients with a severe Acquired Brain Injury (sABI) admitted to an Intensive Rehabilitation Unit (IRU), we detected a novel endotype of consciousness from the spatiotemporal brain dynamics identified via microstate analysis. Also, we investigated whether microstate features were associated with common neurophysiological alterations. Finally, the prognostic information comprised in such descriptors was analysed in a sub-cohort of patients with prolonged Disorder of Consciousness (pDoC). Occurrence of frontally-oriented microstates (C microstate), likelihood of maintaining such brain state or transitioning to the C topography and complexity were found to be indicators of consciousness presence and levels. Features of left-right asymmetric microstates and transitions toward them were found to be negatively correlated with antero-posterior brain reorganization and EEG symmetry. Substantial differences in microstates' sequence complexity and presence of C topography were found between groups of patients with alpha dominant background, cortical reactivity and antero-posterior gradient. Also, transitioning from left-right to antero-posterior microstates was found to be an independent predictor of consciousness recovery, stronger than consciousness levels at IRU's admission. In conclusions, global brain dynamics measured with scale-free estimators can be considered an indicator of consciousness presence and a candidate marker of short-term recovery in patients with a pDoC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)