Nomogram for Early Prediction of Outcome in Coma Patients with Severe Traumatic Brain Injury Receiving Right Median Nerve Electrical Stimulation Treatment.

BACKGROUND: Accurate outcome prediction can serve to approach, quantify and categorize severe traumatic brain injury (TBI) coma patients for right median electrical stimulation (RMNS) treatment, which can support rehabilitation plans. As a proof of concept for individual risk prediction, we created a novel nomogram model combining amplitude-integrated electroencephalography (AEEG) and clinically relevant parameters. METHODS: This study retrospective collected and analyzed a total of 228 coma patients after severe TBI in two medical centers. According to the extended Glasgow Outcome Scale (GOSE), patients were divided into a good outcome (GOSE 3-8) or a poor outcome (GOSE 1-2) group. Their clinical and biochemical indicators, together with EEG features, were explored retrospectively. The risk factors connected to the outcome of coma patients receiving RMNS treatment were identified using Cox proportional hazards regression. The discriminative capability and calibration of the model to forecast outcome were assessed by C statistics, calibration plots, and Kaplan-Meier curves on a personalized nomogram forecasting model. RESULTS: The study included 228 patients who received RMNS treatment for long-term coma after a severe TBI. The median age was 40 years, and 57.8% (132 of 228) of the patients were male. 67.0% (77 of 115) of coma patients in the high-risk group experienced a poor outcome after one year and the comparative data merely was 30.1% (34 of 113) in low-risk group patients. The following variables were integrated into the forecasting of outcome using the backward stepwise selection of Akaike information criterion: age, Glasgow Coma Scale (GCS) at admission, EEG reactivity (normal, absence, or the stimulus-induced rhythmic, periodic, or ictal discharges (SIRPIDs)), and AEEG background pattern (A mode, B mode, or C mode). The C statistics revealed that the nomograms' discriminative potential and calibration demonstrated good predictive ability (0.71). CONCLUSION: Our findings show that the nomogram model using AEEG parameters has the potential to predict outcomes in severe TBI coma patients receiving RMNS treatment. The model could classify patients into prognostic groups and worked well in internal validation.

Exosomes derived from bone marrow mesenchymal stem cells inhibit neuroinflammation after traumatic brain injury.

Exosomes derived from bone marrow mesenchymal stem cells can inhibit neuroinflammation through regulating microglial phenotypes and promoting nerve injury repair. However, the underlying molecular mechanism remains unclear. In this study, we investigated the mechanism by which exosomes derived from bone marrow mesenchymal stem cells inhibit neuroinflammation. Our in vitro co-culture experiments showed that bone marrow mesenchymal stem cells and their exosomes promoted the polarization of activated BV2 microglia to their anti-inflammatory phenotype, inhibited the expression of proinflammatory cytokines, and increased the expression of anti-inflammatory cytokines. Our in vivo experiments showed that tail vein injection of exosomes reduced cell apoptosis in cortical tissue of mouse models of traumatic brain injury, inhibited neuroinflammation, and promoted the transformation of microglia to the anti-inflammatory phenotype. We screened some microRNAs related to neuroinflammation using microRNA sequencing and found that microRNA-181b seemed to be actively involved in the process. Finally, we regulated the expression of miR181b in the brain tissue of mouse models of traumatic brain injury using lentiviral transfection. We found that miR181b overexpression effectively reduced apoptosis and neuroinflamatory response after traumatic brain injury and promoted the transformation of microglia to the anti-inflammatory phenotype. The interleukin 10/STAT3 pathway was activated during this process. These findings suggest that the inhibitory effects of exosomes derived from bone marrow mesenchymal stem cells on neuroinflamation after traumatic brain injury may be realized by the action of miR181b on the interleukin 10/STAT3 pathway.

The Value of the Correlation Coefficient Between the ICP Wave Amplitude and the Mean ICP Level (RAP) Combined With the Resistance to CSF Outflow (Rout) for Early Prediction of the Outcome Before Shunting in Posttraumatic Hydrocephalus.

Objective: To evaluate the value of the correlation coefficient between the ICP wave amplitude and the mean ICP level (RAP) and the resistance to CSF outflow (Rout) in predicting the outcome of patients with post-traumatic hydrocephalus (PTH) selected for shunting. Materials and Methods: As a training set, a total of 191 patients with PTH treated with VP shunting were retrospectively analyzed to evaluate the potential predictive value of Rout, collected from pre-therapeutic CSF infusion test, for a desirable recovery level (dRL), standing for the modified rankin scale (mRS) of 0-2. Eventually, there were 70 patients with PTH prospectively included as a validation set to evaluate the value of Rout-combined RAP as a predictor of dRL. We calculated Rout from a CSF infusion test and collected RAP during continuous external lumbar drainage (ELD). Maximum RAP (RAPmax) and its changes relative to the baseline (ΔRAPmax%) served as specific parameters of evaluation. Results: In the training set, Rout was proved to be a significant predictor of dRL to shunting, with the area under the curve (AUC) of 0.686 (p < 0.001) in receiver-operating characteristic (ROC) analysis. In the validation set, Rout alone did not present a significant value in the prediction of desirable recovery level (dRL). ΔRAPmax% after 1st or 2nd day of ELD both showed significance in predicting of dRL to shunting with the AUC of 0.773 (p < 0.001) and 0.786 (p < 0.001), respectively. Significantly, Rout increased the value of ΔRAPmax% in the prediction of dRL with the AUC of 0.879 (p < 0.001), combining with ΔRAPmax% after the 1st and 2nd days of ELD. RAPmax after the 1st and 2nd days of ELD showed a remarkable predictive value for non-dRL (Levels 3-6 in Modified Rankin Scale) with the AUC of 0.891 (p < 0.001) and 0.746 (p < 0.001). Conclusion: Both RAP and Rout can predict desirable recovery level (dRL) to shunting in patients with PTH in the early phases of treatment. A RAP-combined Rout is a better dRL predictor for a good outcome to shunting. These findings help the neurosurgeon predict the probability of dRL and facilitate the optimization of the individual treatment plan in the event of ineffective or unessential shunting.

An association of low high-density lipoprotein levels with recurrence of chronic subdural hematoma.

BACKGROUND: Chronic subdural hematoma (CSDH) is a common illness in neurosurgical practice with a substantial recurrence rate. Previous studies found that serum lipids were associated with the risk of stroke and subarachnoid hemorrhage. In the current study, we aimed to identify the relationship between serum lipids and CSDH recurrence. METHODS: The medical records of 274 consecutive surgical patients with CSDH in our department were reviewed and analyzed. Patients were separated into recurrence and non-recurrence groups. Univariable and multivariable Cox proportional hazards regression analyses were performed to identify serum lipids (triglycerides, total cholesterol, LDL, HDL) and other potential predictors associated with CSDH recurrence, and the performance of predictors was assessed with receiver operating characteristic (ROC) curve. RESULTS: Of the 274 patients included in the study, 42 (15.3%) experienced at least 1 recurrence of CSDH. Univariate analysis showed that age, hypertension, diabetes mellitus, anticoagulant use, triglycerides, HDL, and midline shift were all significantly associated with CSDH recurrence. Multivariable Cox regression analysis found that only age, diabetes mellitus, midline shift, and HDL level were independent risk factors for CSDH recurrence. A higher HDL level (HR = 0.929, 95% CI 0.905-0.953) was significantly associated with a lower risk of recurrence, and ROC curve analysis revealed that the optimal HDL cut-off value as a predictor was 37.45 mg/dl. CONCLUSIONS: Low level of high-density lipoprotein is significantly associated with recurrence of chronic subdural hematoma.

Alteration of microRNA expression in cerebrospinal fluid of unconscious patients after traumatic brain injury and a bioinformatic analysis of related single nucleotide polymorphisms.

PURPOSE: It is becoming increasingly clear that genetic factors play a role in traumatic brain injury (TBI), whether in modifying clinical outcome after TBI or determining susceptibility to it. MicroRNAs are small RNA molecules involved in various pathophysiological processes by repressing target genes at the post- transcriptional level, and TBI alters microRNA expression levels in the hippocampus and cortex. This study was designed to detect differentially expressed microRNAs in the cerebrospinal fluid (CSF) of TBI patients remaining unconscious two weeks after initial injury and to explore related single nucleotide polymorphisms (SNPs). METHODS: We used a microarray platform to detect differential microRNA expression levels in CSF samples from patients with post-traumatic coma compared with samples from controls. A bioinformatic scan was performed covering microRNA gene promoter regions to identify potential functional SNPs. RESULTS: Totally 26 coma patients and 21 controls were included in this study, with similar distribution of age and gender between the two groups. Microarray showed that fourteen microRNAs were differentially expressed, ten at higher and four at lower expression levels in CSF of traumatic coma patients compared with controls (p<0.05). One SNP (rs11851174 allele: C/T) was identified in the motif area of the microRNA hsa-miR-431-3P gene promoter region. CONCLUSION: The altered microRNA expression levels in CSF after brain injury together with SNP identified within the microRNA gene promoter area provide a new perspective on the mechanism of impaired consciousness after TBI. Further studies are needed to explore the association between the specific microRNAs and their related SNPs with post-traumatic unconsciousness.