Neurocritical Care最新文献

Background: Electroencephalograpy (EEG) reactivity may aid functional outcome prediction in the intensive care unit (ICU). Different types of stimuli could vary in their ability to evoke reactivity. This study explored which type of stimulus is best to elicit EEG reactivity in ICU patients with an impaired consciousness. We also investigated associations between reactivity and hospital survival and functional outcome. Lastly, we compared standardized testing with random stimuli application.

Methods: Adult ICU patients with an impaired consciousness and an EEG with reactivity testing were screened for eligibility. Stimuli were auditory (clapping and calling patient's name), visual, tactile, and noxious. Three raters, blinded to clinical outcomes, scored each EEG recording and stimulus for reactivity. Interrater reliability was assessed using Fleiss' kappa. Associations between reactivity and outcomes were analyzed with logistic regression.

Results: In total, 72 patients were included, most commonly with traumatic brain injury which was present in 19 patients (26.4%) and a median GCS score of 6 (interquartile range, IQR 3-11). EEG reactivity was present in 30.6% of patients. Auditory stimuli were most effective, accounting for 57% of all reactive stimuli. Interrater reliability was highest for clapping (κ = 0.633, 77% raw agreement) and calling the patient's name (κ = 0.584, 74% raw agreement). Reactivity was not associated with hospital survival or 6-month functional outcome. Standardized testing was applied in 23.6% of patients and improved raters' certainty in detecting reactivity compared with the application of random stimuli (88.2% vs. 41.8%, p = 0.002).

Conclusions: Auditory stimuli (clapping and calling the patient's name) proved most effective in eliciting EEG reactivity. Reactivity was not associated with outcomes. Standardized testing increased raters' certainty in detecting reactivity.

Background/objective: Prognostication of critically ill children appearing acutely comatose remains challenging. Event-related potentials (ERPs) using electroencephalography (EEG) offer a noninvasive method to detect covert consciousness. These include the mismatched negativity (MMN) and P300b responses. We investigated ERPs using the auditory local-global oddball paradigm to assess inattentive or attentive cortical processing in critically ill, clinically unresponsive children.

Methods: We prospectively enrolled pediatric intensive care unit (PICU) patients undergoing continuous EEG with Glasgow coma scale scores < 8. Each patient underwent testing with the local-global oddball paradigm. In each trial, five brief tones were delivered; the fifth tone was either identical (local-standard) or different (local-deviant). In total, 80% of trials shared the same local structure (global-standard), and 20% deviated (global-deviant). MMN-like responses were assessed by contrasting local-deviant vs. local-standard trials (100-250 ms post-stimulus) at frontocentral electrodes; P300b-like responses were assessed by contrasting global-deviant vs. global-standard trials (250-700 ms post-stimulus) at centroparietal electrodes. Cluster-based permutation testing identified significant ERPs. Functional outcomes were assessed at 10-12 months using the Glasgow outcome scale extended-Pediatrics (GOSE-Peds), and ERP-outcome associations were analyzed using the Mann-Whitney U test.

Results: Among 29 children, 6 (20.7%) showed reproducible ERPs-2 (6.9%) with MMN-like responses and 4 (13.8%) with P300b-like responses. Presence of either ERP response was associated with lower GOSE-Peds scores (p = 0.029), indicating more favorable outcomes.

Conclusions: ERPs can detect both inattentive and attentive cortical processing in critically ill clinically unresponsive children. The presence of reproducible responses resembling MMN or P300b may be associated with better long-term functional recovery.

Objective: To investigate the effect of bevacizumab on traumatic cerebral edema and its relationship with the blood-brain barrier (BBB) in traumatic brain injury (TBI).

Methods: Seventy rats were randomly divided into the control, sham, TBI, TBI + normal saline (TBI-NS), and TBI + bevacizumab (TBI-Beva) groups. A total of 24 h after TBI, western blotting was used to detect vascular endothelial growth factor (VEGF) and occludin. Pathological examination was used to observe cerebral edema. Magnetic resonance imaging (MRI) was performed to observe cerebral edema and brain tissue enhancement. Transmission electron microscope was used to observe the structure of BBB. Immunofluorescence was used to detect immunoglobulin G (IgG) intensity.

Results: The expression of VEGF increased after TBI, whereas bevacizumab inhibited the expression of VEGF. MRI showed obvious cerebral edema and enhancement areas around the trauma site after TBI, and bevacizumab treatment reduced both the cerebral edema and enhancement range. Compared with the Sham group, cerebral edema occurred after TBI, including vasogenic and intracellular edema, but bevacizumab treatment simultaneously reduced both types of cerebral edema. The expression of occludin was down-regulated and IgG intensity was up-regulated, and the BBB structure was damaged after TBI. The expression of occludin was up-regulated and IgG intensity was down-regulated after treatment with bevacizumab. Meanwhile, the extent of damage to the BBB structure was reduced.

Conclusion: Bevacizumab promotes recovery from traumatic cerebral edema by repairing BBB damage and is a potential drug for TBI treatment.

Background: Contrast-enhanced ultrasound (CEUS) has great potential for assessing increased intracranial pressure (ICP); however, the most appropriate parameters remain unknown. This study aimed to explore the application of quantitative analysis of CEUS diagnosing increased ICP in patients with severe brain injury after surgery, and to provide a novel idea for the non-invasive evaluation of ICP.

Methods: This observational study included 34 patients with craniocerebral injuries admitted to the intensive care unit from May 2022 to December 2023. Patients were divided into a normal cranial pressure group (< 20 mm Hg) and an intracranial hypertension group (≥ 20 mm Hg) on the basis of the invasive ICP monitoring values. All patients underwent CEUS examination within 24 h postoperatively. Time-intensity curves of the central retinal artery and short posterior ciliary artery were generated using CEUS quantitative analysis software. Quantitative parameters were obtained, and the difference was calculated. The diagnostic accuracy of each parameter was assessed by computing the area under the receiver operating characteristic curve (AUC).

Results: In total, 15 patients (44%) had intracranial hypertension. The arrival time difference (ΔAT) and peak time difference (ΔTP) were significantly higher in the intracranial hypertension group than in the normal cranial pressure group (P < 0.001 and P = 0.010, respectively). The peak intensity difference (ΔPkI) was significantly lower in the intracranial hypertension group than in the normal cranial pressure group (P = 0.025). The diagnostic accuracy of ΔAT for identifying intracranial hypertension was excellent, with an AUC of 0.944 [95% confidence interval (CI) 0.874-1.014], which yielded an optimal cutoff value of 0.86 s with 93.3% sensitivity (95% CI 0.849-1.017) and 84.2% specificity (95% CI 0.719-0.964). The AUC of ΔAT was significantly higher than that of ΔTP and ΔPkI (AUC 0.761 and 0.721, respectively; both P < 0.05).

Conclusions: The CEUS quantitative analysis parameter, ΔAT, is a promising parameter for evaluating postoperative ICP elevation in patients with severe brain injury.

Background: Traumatic brain injury (TBI) is a global health problem, and its mechanisms can be divided into primary and secondary damage. Secondary injuries play a significant role in TBI outcomes. Recent studies have shown that semaglutide, a novel glucose-dependent hypoglycemic agent, inhibits neuroinflammation and cell death in some neurodegenerative diseases. However, the association between semaglutide level and TBI remains unclear. Therefore, this study aimed to investigate the neuroprotective effects of semaglutide in patients with TBI.

Method: In total, 60 C57 male mice were randomly divided into three groups: SHAM, TBI, and SEMAGLUTIDE (operation + 50 nmol/kg/day semaglutide). Behavioral tests, immunofluorescence, and western blotting were performed 72 h after impact.

Results: Semaglutide reduced neuronal apoptosis, downregulated Bax expression, and increased Bcl-2 expression after TBI. Additionally, in the downstream apoptosis pathway, semaglutide regulated proteins associated with caspase-dependent and caspase-independent pathways, with the caspase-dependent pathway being the major one. Moreover, the activation of M1 microglia was also inhibited by semaglutide, which may be related to its protective effects.

Conclusions: Semaglutide inhibited apoptosis, increased neuronal survival rate, and inhibited M1 microglial activation to improve cognitive function in TBI mice. This neuroprotective effect of semaglutide may be regionally and time dependent.

Trial registration number: 202204008 Trial registration date: 2022Y12M3D.

Objectives: Patients with aneurysmal subarachnoid hemorrhage (aSAH) are at high risk of secondary ischemia, and timely insight into cerebral metabolism may improve clinical management. Cerebral microdialysis offers continuous metabolic monitoring but is invasive, focal, and confined to specialized centers. Peripheral blood and cerebrospinal fluid (CSF) could provide less invasive, more accessible surrogates for assessing cerebral metabolic status. This study aimed to evaluate glucose and lactate dynamics across blood, CSF, and brain parenchyma in patients with severe aSAH.

Patients and methods: A total of 39 patients with aSAH undergoing multimodal neuromonitoring were retrospectively analyzed. Glucose and lactate levels from plasma, CSF, and cerebral microdialysis were matched within 90-min intervals relative to each microdialysis measurement. Associations were analyzed using linear mixed-effects models.

Results: Plasma (p < 0.001) and CSF (p < 0.001) glucose levels were significantly associated with cerebral glucose concentrations. Moderate correlations were observed between plasma-brain (r = 0.54) and plasma-CSF (r = 0.55), while CSF-brain correlation was weaker (r = 0.36). For lactate, significant associations were found between CSF and brain (p = 0.04; r = 0.24) and between plasma and CSF (p < 0.001; r = 0.33), but plasma-brain lactate showed no significant relationship. The plasma-brain glucose association weakened slightly over time (p = 0.008) and strengthened during episodes of low brain tissue oxygenation (pbtO₂ < 15 mm Hg; p = 0.01). Insulin had no effect on glucose relationships but significantly attenuated the plasma-brain lactate association (p < 0.001). The presence of metabolic crisis (lactate/pyruvate ratio > 40) strengthened the CSF-brain lactate association (p = 0.04). CSF cell count had no significant effect.

Conclusions: In severe aSAH, glucose and lactate levels in blood and CSF reflect cerebral values in a compartment- and metabolite-specific manner, but with high variability influenced by clinical conditions. These findings suggest that blood and CSF provide only limited information about cerebral metabolism, highlighting the complementary value of cerebral microdialysis for individualized, brain-targeted monitoring.

Stroke-associated pneumonia (SAP) is a frequent and severe complication following stroke. Recently, several machine learning (ML) models have been developed to predict SAP. We aimed to evaluate the predictive performance of these models in SAP prediction. We searched PubMed, Embase, Scopus, and Web of Science up to 18 June 2025, for studies developing ML, deep learning (DL), or neural network (NN) models for SAP prediction. The pooled estimates of area under the curve (AUC), accuracy (ACC), sensitivity (SEN), specificity (SPE), and diagnostic odds ratio (DOR) were calculated using the R program. A total of 27 studies were included, with a prevalence of SAP at 18.9%. Most models were ML based (77.8%), and clinical data were the most common input (77.8%). The pooled AUC was 0.84 [95% (CI): 0.80-0.87], and the pooled ACC was 0.80 (95% CI: 0.76-0.84). SEN and SPE were 0.73 (95% CI: 0.63-0.81) and 0.85 (95% CI: 0.77-0.90), respectively. The pooled DOR was 15.4 (95% CI: 10.2-23.3), and the summary receiver operating characteristic (SROC) curve showed an AUC of 0.853 with a false positive rate of 0.153 (95% CI: 0.096-0.235). No significant differences were found between ischemic and hemorrhagic subgroups. ML-based models demonstrated promising performance in predicting SAP and can help physicians through the early identification of high-risk cases. However, further external validation and integration into clinical workflows are required before widespread clinical adoption.