Carrier-Free Self-Assembly Nano-Sonosensitizers for Sonodynamic-Amplified Cuproptosis-Ferroptosis in Glioblastoma Therapy.

Cuproptosis is a newly discovered form of programmed cell death significantly depending on the transport efficacy of copper (Cu) ionophores. However, existing Cu ionophores, primarily small molecules with a short blood half-life, face challenges in transporting enough amounts of Cu ions into tumor cells. This work describes the construction of carrier-free nanoparticles (Ce6@Cu NPs), which self-assembled by the coordination of Cu2+ with the sonosensitizer chlorin e6 (Ce6), facilitating sonodynamic-triggered combination of cuproptosis and ferroptosis. Ce6@Cu NPs internalized by U87MG cells induce a sonodynamic effect and glutathione (GSH) depletion capability, promoting lipid peroxidation and eventually inducing ferroptosis. Furthermore, Cu+ concentration in tumor cells significantly increases as Cu2+ reacts with reductive GSH, resulting in the downregulation of ferredoxin-1 and lipoyl synthase. This induces the oligomerization of lipoylated dihydrolipoamide S-acetyltransferase, causing proteotoxic stress and irreversible cuproptosis. Ce6@Cu NPs possess a satisfactory ability to penetrate the blood-brain barrier, resulting in significant accumulation in orthotopic U87MG-Luc glioblastoma. The sonodynamic-triggered combination of ferroptosis and cuproptosis in the tumor by Ce6@Cu NPs is evidenced both in vitro and in vivo with minimal side effects. This work represents a promising tumor therapeutic strategy combining ferroptosis and cuproptosis, potentially inspiring further research in developing logical and effective cancer therapies based on cuproptosis.

Naoxueshu Oral Liquid Accelerates Post-Craniotomy Hematoma Absorption in Patients: An Open-Label, Multicenter, and Randomized Controlled Trial.

OBJECTIVE: To investigate whether Naoxueshu Oral Liquid (NXS) could promote hematoma absorption in post-craniotomy hematoma (PCH) patients. METHODS: This is an open-label, multicenter, and randomized controlled trial conducted at 9 hospitals in China. Patients aged 18-80 years with post-craniotomy supratentorial hematoma volume ranging from 10 to 30 mL or post-craniotomy infratentorial hematoma volume less than 10 mL, or intraventricular hemorrhage following cranial surgery were enrolled. They were randomly assigned at a 1:1 ratio to the NXS (10 mL thrice daily for 15 days) or control groups using a randomization code table. Standard medical care was administered in both groups. The primary outcome was the percentage reduction in hematoma volume from day 1 to day 15. The secondary outcomes included the percentage reduction in hematoma volume from day 1 to day 7, the absolute reduction in hematoma volume from day 1 to day 7 and 15, and the change in neurological function from day 1 to day 7 and 15. The safety was closely monitored throughout the study. Moreover, subgroup analysis was performed based on age, gender, history of diabetes, and etiology of intracerebral hemorrhage (ICH). RESULTS: A total of 120 patients were enrolled and randomly assigned between March 30, 2018 and April 15, 2020. One patient was lost to follow-up in the control group. Finally, there were 119 patients (60 in the NXS group and 59 in the control group) included in the analysis. In the full analysis set (FAS) analysis, the NXS group had a greater percentage reduction in hematoma volume from day 1 to day 15 than the control group [median (Q1, Q3): 85% (71%, 97%) vs. 76% (53%, 93%), P<0.05]. The secondary outcomes showed no statistical significance between two groups, either in FAS or per-protocol set (P>0.05). Furthermore, no adverse events were reported during the study. In the FAS analysis, the NXS group exhibited a higher percentage reduction in hematoma volume on day 15 in the following subgroups: male patients, patients younger than 65 years, patients without diabetes, or those with initial cranial surgery due to ICH (all P<0.05). CONCLUSIONS: The administration of NXS demonstrated the potential to promote the percentage reduction in hematoma volume from day 1 to day 15. This intervention was found to be safe and feasible. The response to NXS may be influenced by patient characteristics. (Registration No. ChiCTR1800017981).

DPA714 PET Imaging Shows That Inflammation of the Choroid Plexus Is Active in Chronic-Phase Intracerebral Hemorrhage.

PURPOSE: Our aims were to investigate the presence of choroid plexus (CP) inflammation in chronic-phase intracerebral hemorrhage (ICH) patients and to characterize any inflammatory cells in the CP. PATIENTS AND METHODS: An in vivo 18 F-DPA714 PET study was undertaken in 22 chronic-phase ICH patients who were admitted to the First Affiliated Hospital of Fujian Medical University or Tianjin Medical University General Hospital from April 2017 to June 2020. Ten control participants with nonhemorrhagic central nervous system diseases were included. Choroid plexus 18 F-DPA714 uptake was calculated as the average SUVR. To aid the interpretation of the 18 F-DPA714 uptake results at the CP level, Cy5-DPA714 in vivo imaging and immunofluorescence staining were used to show the presence of CP inflammation in an ICH mouse model during the chronic phase (14 weeks after ICH). Then immunofluorescence staining against translocator protein and other specific biomarkers was used to characterize the cells present in the inflamed CP of ICH mice in the chronic phase. RESULTS: PET imaging showed that CP DPA714 SUVRs in chronic-phase ICH patients were higher than in controls (mean CP SUVR ± SD; ICH group: 1.05 ± 0.35; control group: 0.81 ± 0.21; P = 0.006). Immunofluorescence staining of the CP in ICH model mice identified a population of CD45 + immune cells, peripheral monocyte-derived CD14 + cells, CD68 + phagocytes, and CD11b + resident microglia/macrophages expressing translocator protein, possibly contributing to the increased 18 F-DPA714 uptake. CONCLUSIONS: Our study shows that CP DPA714 uptake in chronic-phase ICH patients was higher than that of participants with nonhemorrhagic central nervous system diseases, which means that CP inflammation is still active in chronic-phase ICH patients.

ADAM17 Aggravates the Inflammatory Response by Modulating Microglia Polarization Through the TGF-ß1/Smad Pathway Following Experimental Traumatic Brain Injury.

Microglia-mediated neuroinflammatory responses play important roles in secondary neurological injury after traumatic brain injury (TBI). The TGF-ß pathway participates in the regulation of M1/M2 phenotype transformation of microglia. TGF-ß can activate the Smad pathway by binding to TGF-ßRs, which is regulated by the cleavage function of A disintegrin and metalloproteinase 17 (ADAM17). However, the role of ADAM17 and the associated signaling pathways in the pathological process after TBI remain unclear. Herein, we assessed the transformation of microglia M1/M2 phenotype polarization and the neuroinflammatory response after the inhibition of ADAM17. The formation of TGF-ßRs and TGF-ß1/TGF-ßRII complexes on microglia were detected to evaluate the effect of ADAM17 inhibition on the TGF-ß1/Smad pathway. ADAM17 was highly expressed after TBI and mainly located in the microglia. the inhibition of ADAM17 improved neurological function after TBI. The neuroprotective effect of ADAM17 inhibition was related to a shift from the M1 microglial phenotype to the M2 microglial phenotype, thus reducing TBI-induced neuroinflammation. ADAM17 inhibition increased expression of TGF-ßRs on the microglia membrane, promoted formation of TGF-ß1/TGF-ßRII complexes, and induced intranuclear translocation of Smads, which activated the TGF-ß/Smad pathway. In conclusion, our study suggested that ADAM17 inhibition regulated microglia M1/M2 phenotype polarization through the TGF-ß1/Smad pathway and influenced the neuroinflammatory response after TBI.

Association of lesion location with post-stroke depression in China: a systematic review and meta-analysis.

Background: Post-stroke depression (PSD) is a mental health condition that can develop after a stroke, with a higher risk of death and negative outcomes. However, limited research has explored how PSD incidence relates to brain locations in Chinese patients. This study aims to fill this gap by examining the link between PSD occurrence and brain lesion location, as well as the type of stroke experienced by the patient. Methods: We conducted a systematic search in databases to gather post-stroke depression literature published between January 1, 2015 and May 31, 2021. Following this, we performed a meta-analysis using RevMan to analyze the incidence of PSD associated with different brain regions and types of stroke separately. Results: We analyzed seven studies, with a total of 1604 participants. Our findings indicated that the incidence of PSD was higher when the stroke occurred in the left hemisphere compared to the right hemisphere (RevMan: Z = 8.93, P <0.001, OR = 2.69, 95% CI: 2.16-3.34, fixed model); PSD was more common when the stroke affected the cerebral cortex rather than the subcerebral cortex (RevMan: Z = 3.96, P <0.001, OR = 2.00, 95% CI: 1.42-2.81) and when it affected the anterior cortex compared to the posterior cortex (RevMan: Z = 3.85, P <0.001, OR = 1.89, 95% CI: 1.37-2.62). However, we did not find a significant difference in the occurrence of PSD between ischemic and hemorrhagic strokes (RevMan: Z = 0.62, P = 0.53, OR = 0.02, 95% CI: -0.05-0.09). Conclusions: Our findings revealed a higher likelihood of PSD in the left hemisphere, specifically in the cerebral cortex and anterior region.

A nomogram predictive model for long-term survival in spontaneous intracerebral hemorrhage patients without cerebral herniation at admission.

Stratification of spontaneous intracerebral hemorrhage (sICH) patients without cerebral herniation at admission, to determine the subgroups may be suffered from poor outcomes or benefit from surgery, is important for following treatment decision. The aim of this study was to establish and verify a de novo nomogram predictive model for long-term survival in sICH patients without cerebral herniation at admission. This study recruited sICH patients from our prospectively maintained ICH patient database (RIS-MIS-ICH, ClinicalTrials.gov Identifier: NCT03862729) between January 2015 and October 2019. All eligible patients were randomly classified into a training cohort and a validation cohort according to the ratio of 7:3. The baseline variables and long-term survival outcomes were collected. And the long-term survival information of all the enrolled sICH patients, including the occurrence of death and overall survival. Follow-up time was defined as the time from the onset to death of the patient or the last clinical visit. The nomogram predictive model was established based on the independent risk factors at admission for long-term survival after hemorrhage. The concordance index (C-index) and ROC curve were used to evaluate the accuracy of the predictive model. Discrimination and calibration were used to validate the nomogram in both the training cohort and the validation cohort. A total of 692 eligible sICH patients were enrolled. During the average follow-up time of 41.77 ± 0.85 months, a total of 178 (25.7%) patients died. The Cox Proportional Hazard Models showed that age (HR 1.055, 95% CI 1.038-1.071, P < 0.001), Glasgow Coma Scale (GCS) at admission (HR 2.496, 95% CI 2.014-3.093, P < 0.001) and hydrocephalus caused by intraventricular hemorrhage (IVH) (HR 1.955, 95% CI 1.362-2.806, P < 0.001) were independent risk factors. The C index of the admission model was 0.76 and 0.78 in the training cohort and validation cohort, respectively. In the ROC analysis, the AUC was 0.80 (95% CI 0.75-0.85) in the training cohort and was 0.80 (95% CI 0.72-0.88) in the validation cohort. SICH patients with admission nomogram scores greater than 87.75 were at high risk of short survival time. For sICH patients without cerebral herniation at admission, our de novo nomogram model based on age, GCS and hydrocephalus on CT may be useful to stratify the long-term survival outcomes and provide suggestions for treatment decision-making.

Optimal Timing of Cranioplasty and Predictors of Overall Complications After Cranioplasty: The Impact of Brain Collapse.

BACKGROUND: The optimal timing of cranioplasty (CP) and predictors of overall postoperative complications are still controversial. OBJECTIVE: To determine the optimal timing of CP. METHODS: Patients were divided into collapsed group and noncollapsed group based on brain collapse or not, respectively. Brain collapse volume was calculated in a 3-dimensional way. The primary outcomes were overall complications and outcomes at the 12-month follow-up after CP. RESULTS: Of the 102 patients in this retrospective observation cohort study, 56 were in the collapsed group, and 46 were in the noncollapsed group. Complications were noted in 30.4% (n = 31), 24 (42.9%) patients in the collapsed group and 7 (15.2%) patients in the noncollapsed group, with a significant difference ( P = .003). Thirty-three (58.9%) patients had good outcomes (modified Rankin Scale 0-3) in the collapsed group, and 34 (73.9%) patients had good outcomes in the noncollapsed group without a statistically significant difference ( P = .113). Brain collapse ( P = .005) and Karnofsky Performance Status score at the time of CP ( P = .025) were significantly associated with overall postoperative complications. The cut-off value for brain collapse volume was determined as 11.26 cm 3 in the receiver operating characteristic curve. The DC-CP interval was not related to brain collapse volume or postoperative complications. CONCLUSION: Brain collapse and lower Karnofsky Performance Status score at the time of CP were independent predictors of overall complications after CP. The optimal timing of CP may be determined by tissue window based on brain collapse volume instead of time window based on the decompressive craniectomy-CP interval.

Global, regional, and national burden and attributable risk factors of neurological disorders: The Global Burden of Disease study 1990-2019.

Background: Neurological disorders are a major and increasing global health challenge, which accounts for a substantial portion of the disease burden worldwide. The aim of this systematic analysis is to present the most comprehensive and up-to-date estimates of disease burden, epidemiological trends, and attributable risk factors of neurological disorders at global, regional, and national levels. Methods: We extracted data of 18 neurological disorders from the Global Burden of Disease 2019 study database. The burden of neurological disorders was measured using the incidence, prevalence, mortality, and disability-adjusted life years (DALYs), and further described according to age, sex, year, geographical location and socio-demographic Index (SDI). All estimates were presented with corresponding 95% uncertainty intervals (UIs). Findings: Globally, in 2019, there were nearly 10 million deaths and 349 million DALYs due to neurological disorders. Among the 18 neurological disorders, stroke was the biggest contributor to DALYs (143232.18 [95%UI 133095.81-153241.82] in thousands) and deaths (6552.72 [95%UI 5995.20-7015.14] in thousands), followed by neonatal encephalopathy due to birth asphyxia and trauma. From 1990 to 2019, the DALYs of neurological diseases belonging to the communicable, maternal, neonatal and nutritional categories showed a sharp decrease, while Alzheimer's disease and other dementias and Parkinson's disease showed a large increase. Neurological disorders exhibited different profiles in different regions and age groups. A significant correlation between the SDI and the age-standardized DALY rates was also found except for Alzheimer's disease and other dementias. In addition, risk factors such as high systolic blood pressure, low birth weight and short gestation period, and metabolic risk contribute significantly to neurological disorders. Interpretation: The overall burden of neurological disorders has increased from 1990 to 2019, especially for non-communicable neurological disorders. The substantial variations of burden across regions emphasize the need for region-specific interventional strategies and allocation of resources based on priorities.

Quantitative hematoma heterogeneity associated with hematoma growth in patients with early intracerebral hemorrhage.

Background: Early hematoma growth is associated with poor functional outcomes in patients with intracerebral hemorrhage (ICH). We aimed to explore whether quantitative hematoma heterogeneity in non-contrast computed tomography (NCCT) can predict early hematoma growth. Methods: We used data from the Risk Stratification and Minimally Invasive Surgery in Acute Intracerebral Hemorrhage (Risa-MIS-ICH) trial. Our study included patients with ICH with a time to baseline NCCT <12 h and a follow-up CT duration <72 h. To get a Hounsfield unit histogram and the coefficient of variation (CV) of Hounsfield units (HUs), the hematoma was segmented by software using the auto-segmentation function. Quantitative hematoma heterogeneity is represented by the CV of hematoma HUs. Multivariate logistic regression was utilized to determine hematoma growth parameters. The discriminant score predictive value was assessed using the area under the ROC curve (AUC). The best cutoff was determined using ROC curves. Hematoma growth was defined as a follow-up CT hematoma volume increase of >6 mL or a hematoma volume increase of 33% compared with the baseline NCCT. Results: A total of 158 patients were enrolled in the study, of which 31 (19.6%) had hematoma growth. The multivariate logistic regression analysis revealed that time to initial baseline CT (P = 0.040, odds ratio [OR]: 0.824, 95 % confidence interval [CI]: 0.686-0.991), "heterogeneous" in the density category (P = 0.027, odds ratio [OR]: 5.950, 95 % confidence interval [CI]: 1.228-28.828), and CV of hematoma HUs (P = 0.018, OR: 1.301, 95 % CI: 1.047-1.617) were independent predictors of hematoma growth. By evaluating the receiver operating characteristic curve, the CV of hematoma HUs (AUC = 0.750) has a superior predictive value for hematoma growth than for heterogeneous density (AUC = 0.638). The CV of hematoma HUs had an 18% cutoff, with a specificity of 81.9 % and a sensitivity of 58.1 %. Conclusion: The CV of hematoma HUs can serve as a quantitative hematoma heterogeneity index that predicts hematoma growth in patients with early ICH independently.

Integrative and comparative single-cell analysis reveals transcriptomic difference between human tumefactive demyelinating lesion and glioma.

Tumefactive demyelinating lesion (TDL) is an immune-mediated disease which can be misdiagnosed as glioma. At present, there is no study comparing difference between the two disorders at the cellular level. Here, we perform integrative and comparative single-cell RNA sequencing (ScRNA-seq) transcriptomic analysis on TDL and glioma lesions. At single-cell resolution, TDL is comprised primarily of immune cells, which is completely different from glioma. The integrated analysis reveals a TDL-specific microglial subset involving in B cell activation and proliferation. Comparative analysis highlights remyelination function of glial cells and demyelination function of T cells in TDL. Subclustering and pseudotime trajectory analysis of T cells in TDL reveal their heterogeneity and diverse functions involving in TDL pathogenesis and recovery process. Our study identifies substantial differences between TDL and glioma at single-cell resolution. The observed heterogeneity and potentially diverse functions of cells in TDL may be critical in disease progression.

Novel machine learning models to predict pneumonia events in supratentorial intracerebral hemorrhage populations: An analysis of the Risa-MIS-ICH study.

Background: Stroke-associated pneumonia (SAP) contributes to high mortality rates in spontaneous intracerebral hemorrhage (sICH) populations. Accurate prediction and early intervention of SAP are associated with prognosis. None of the previously developed predictive scoring systems are widely accepted. We aimed to derive and validate novel supervised machine learning (ML) models to predict SAP events in supratentorial sICH populations. Methods: The data of eligible supratentorial sICH individuals were extracted from the Risa-MIS-ICH database and split into training, internal validation, and external validation datasets. The primary outcome was SAP during hospitalization. Univariate and multivariate analyses were used for variable filtering, and logistic regression (LR), Gaussian naïve Bayes (GNB), random forest (RF), K-nearest neighbor (KNN), support vector machine (SVM), extreme gradient boosting (XGB), and ensemble soft voting model (ESVM) were adopted for ML model derivations. The accuracy, sensitivity, specificity, and area under the curve (AUC) were adopted to evaluate the predictive value of each model with internal/cross-/external validations. Results: A total of 468 individuals with sICH were included in this work. Six independent variables [nasogastric feeding, airway support, unconscious onset, surgery for external ventricular drainage (EVD), larger sICH volume, and intensive care unit (ICU) stay] for SAP were identified and selected for ML prediction model derivations and validations. The internal and cross-validations revealed the superior and robust performance of the GNB model with the highest AUC value (0.861, 95% CI: 0.793-0.930), while the LR model had the highest AUC value (0.867, 95% CI: 0.812-0.923) in external validation. The ESVM method combining the other six methods had moderate but robust abilities in both cross-validation and external validation and achieved an AUC of 0.843 (95% CI: 0.784-0.902) in external validation. Conclusion: The ML models could effectively predict SAP in sICH populations, and our novel ensemble model demonstrated reliable robust performance outcomes despite the populational and algorithmic differences. This attempt indicated that ML application may benefit in the early identification of SAP.

Sex-different interrelationships of rs945270, cerebral gray matter volumes, and attention deficit hyperactivity disorder: a region-wide study across brain.

Previous genome-wide association studies (GWAS) reported that the allele C of rs945270 of the kinectin 1 gene (KTN1) most significantly increased the gray matter volume (GMV) of the putamen and modestly regulated the risk for attention deficit hyperactivity disorder (ADHD). On the other hand, ADHD is known to be associated with a reduction in subcortical and cortical GMVs. Here, we examined the interrelationships of the GMVs, rs945270 alleles, and ADHD symptom scores in the same cohort of children. With data of rs945270 genotypes, GMVs of 118 brain regions, and ADHD symptom scores of 3372 boys and 3129 girls of the Adolescent Brain Cognition Development project, we employed linear regression analyses to examine the pairwise correlations adjusted for the third of the three traits and other relevant covariates, and examine their mediation effects. We found that the major allele C of rs945270 modestly increased risk for ADHD in males only when controlling for the confounding effects of the GMV of any one of the 118 cerebral regions (0.026 ≤ p ≤ 0.059: Top two: left and right putamen). This allele also significantly increased putamen GMV in males alone (left p = 2.8 × 10-5, and right p = 9.4 × 10-5; α = 2.1 × 10-4) and modestly increased other subcortical and cortical GMVs in both sexes (α < p < 0.05), whether or not adjusted for ADHD symptom scores. Both subcortical and cortical GMVs were significantly or suggestively reduced in ADHD when adjusted for rs945270 alleles, each more significantly in females (3.6 × 10-7 ≤ p < α; Top two: left pallidum and putamen) and males (3.5 × 10-6 ≤ p < α), respectively. Finally, the left and right putamen GMVs reduced 14.0% and 11.7% of the risk effects of allele C on ADHD, and allele C strengthened 4.5% (left) and 12.2% (right) of the protective effects of putamen GMVs on ADHD risk, respectively. We concluded that the rs945270-GMVs-ADHD relationships were sex-different. In males, the major allele C of rs945270 increased risk for ADHD, which was compromised by putamen GMVs; this allele also but only significantly increased putamen GMVs that then significantly protected against ADHD risk. In females, the top two GMVs significantly decreasing ADHD risk were left pallidum and putamen GMVs. Basal ganglia the left putamen in particular play the most critical role in the pathogenesis of ADHD.

Forest Fire Detection via Feature Entropy Guided Neural Network.

Forest fire detection from videos or images is vital to forest firefighting. Most deep learning based approaches rely on converging image loss, which ignores the content from different fire scenes. In fact, complex content of images always has higher entropy. From this perspective, we propose a novel feature entropy guided neural network for forest fire detection, which is used to balance the content complexity of different training samples. Specifically, a larger weight is given to the feature of the sample with a high entropy source when calculating the classification loss. In addition, we also propose a color attention neural network, which mainly consists of several repeated multiple-blocks of color-attention modules (MCM). Each MCM module can extract the color feature information of fire adequately. The experimental results show that the performance of our proposed method outperforms the state-of-the-art methods.

A Novel Titanium Cranioplasty Technique of Marking the Coronal and Squamosoparietal Sutures in Three-Dimensional Titanium Mesh as Anatomical Positioning Markers to Increase the Surgical Accuracy and Reduce Postoperative Complications.

Objective: The objective of this research is to modify the titanium cranioplasty (Ti-CP) technique to increase the surgical accuracy and preliminarily verify the effectiveness and safety of this improvement. Methods: We developed a novel technique of marking the coronal and squamosoparietal sutures in three-dimensional (3D) titanium mesh as anatomical positioning markers and designed a prospective trial in patients with a unilateral frontotemporoparietal skull defect. Patients were randomly divided into two groups by the presence or absence of the anatomical positioning markers, and the therapeutic effects of these two groups were compared. Results: Forty-four patients were included in this study, including 28 (64%) males and 16 (36%) females. The mean age was 44.8 ± 15.2 years (range, 13-75 years). Overall postoperative complication rate of the intervention group (18%) was significantly (P = 0.03) lower than the control group (50%). Surgical accuracy of the intervention group (97.8%) was significantly (P < 0.001) higher than the control group (94%). Visual analog scale for cosmesis (VASC) of the intervention group (8.4) was significantly (P < 0.001) higher than the control group (7). The overall postoperative complication rate was 34%. Multivariate analyses showed that surgical accuracy <95.8% (OR = 19.20, 95% CI = 3.17-116.45, P = 0.001) was significantly associated with overall postoperative complications. Independent predictor of overall postoperative complications was surgical accuracy (OR = 0.57, 95% CI = 0.40-0.82, P = 0.002). Conclusions: This novel technique for repairing frontotemporoparietal skull defects increases surgical accuracy, improves cosmetic prognosis, and reduces postoperative complications. Therefore, it is a safe and effective improvement for Ti-CP.

A Nomogram for Predicting the Need of Postoperative Tracheostomy in Patients With Aneurysmal Subarachnoid Hemorrhage.

Objective: Early identification for the need of tracheostomy (TT) in aneurysmal subarachnoid hemorrhage (aSAH) patients remains one of the main challenges in clinical practice. Our study aimed to establish and validate a nomogram model for predicting postoperative TT in aSAH patients. Methods: Patients with aSAH receiving active treatment (interventional embolization or clipping) in our institution between June 2012 and December 2018 were retrospectively included. The effects of patients' baseline information, aneurysm features, and surgical factors on the occurrence of postoperative TT were investigated for establishing a nomogram in the training cohort with 393 patients. External validation for the nomogram was performed in the validation cohort with 242 patients. Results: After multivariate analysis, higher age, high neutrophil-to-lymphocyte ratio (NLR), high World Federation of Neurological Surgeons Scale (WFNS), and high Barrow Neurological Institute (BNI) grade were left in the final logistic regression model. The predictive power of the model was excellent in both training cohort and validation cohort [area under the curve (AUC): 0.924, 95% confidence interval [CI]: 0.893-0.948; AUC: 0.881, 95% CI: 0.833-0.919]. A nomogram consisting of these factors had a C-index of 0.924 (95% CI: 0.869-0.979) in the training cohort and was validated in the validation cohort (C-index: 0.881, 95% CI: 0.812-0.950). The calibration curves suggested good match between prediction and observation in both training and validation cohorts. Conclusion: Our study established and validated a nomogram model for predicting postoperative TT in aSAH patients.

Preoperative serum lactate dehydrogenase level predicts progression and prognosis in patients with glioma.

BACKGROUND: To evaluate the value of serum Lactate Dehydrogenase (LDH) level in predicting recurrence and the overall survival (OS) of glioma patients. MATERIALS AND METHODS: A total number of 216 patients with glioma in our institution were retrospectively recruited to analyze the relationship between preoperative serum LDH level and prognosis. RESULTS: Overall, the median age of patients was 46.0 (31.0-57.0) years old; 53.7% (116 of 216) of the enrolled patients were male. Multivariate analysis revealed that serum LDH level (odds ratio [OR] = 0.97, 95% confidence interval [CI] = 0.96-0.98, P < 0.001) and World Health Organization (WHO) grade (grade II: OR = 19.64, 95%CI = 5.56-69.35, P < 0.001; grade III: OR =1 9.50, 95%CI = 7.08-53.73, P < 0.001; grade IV: OR = 15.23, 95%CI = 4.94-46.97, P < 0.001) were significant and independent of 1-year Progression-free survival (PFS) after adjusting for confounders. The predictive performance of serum LDH level was represented with area under curve (AUC) = 0.741, 95%CI = 0.677-0.798. Multivariate Cox analysis revealed that LDH level (hazard ratio [HR] = 2.56, 95%CI = 1.59-4.15, P < 0.001) and WHO grade (grade II: HR = 4.58, 95%CI = 0.56-37.23, P = 0.155; grade III: HR = 16.35, 95%CI = 2.16-123.80, P = 0.007; grade IV: HR = 42.13, 95%CI = 5.83-304.47, P < 0.001) remained associated with survival at 2-year follow-up. At 3-year follow-up, lymphocyte count (HR = 0.68, 95%CI = 0.51-0.91, P = 0.008), LDH level (HR = 2.21, 95%CI = 1.40-3.49, P = 0.001), and WHO grade (grade II: HR = 1.44, 95%CI = 0.44-4.68, P = 0.543; grade III: HR = 4.99, 95%CI = 1.68-14.87, P = 0.004; grade IV: HR = 16.96, 95%CI = 6.13-46.93, P < 0.001) remained associated with survival in multivariate Cox analysis. CONCLUSION: Our study demonstrated that preoperative serum LDH level could serve as a reliable indicator for predicting prognosis of glioma patients. Further multicenter studies are still required to verify our findings.

Early Predictors of the Increase in Perihematomal Edema Volume After Intracerebral Hemorrhage: A Retrospective Analysis From the Risa-MIS-ICH Study.

Background and Purpose: Perihematomal edema (PHE) is associated with poor functional outcomes after intracerebral hemorrhage (ICH). Early identification of risk factors associated with PHE growth may allow for targeted therapeutic interventions. Methods: We used data contained in the risk stratification and minimally invasive surgery in acute intracerebral hemorrhage (Risa-MIS-ICH) patients: a prospective multicenter cohort study. Patients' clinical, laboratory, and radiological data within 24 h of admission were obtained from their medical records. The absolute increase in PHE volume from baseline to day 3 was defined as iPHE volume. Poor outcome was defined as modified Rankin Scale (mRS) of 4 to 6 at 90 days. Binary logistic regression was used to assess the relationship between iPHE volume and poor outcome. The receiver operating characteristic curve was used to find the best cutoff. Linear regression was used to identify variables associated with iPHE volume (ClinicalTrials.gov Identifier: NCT03862729). Results: One hundred ninety-seven patients were included in this study. iPHE volume was significantly associated with poor outcome [P = 0.003, odds ratio (OR) 1.049, 95% confidence interval (CI) 1.016-1.082] after adjustment for hematoma volume. The best cutoff point of iPHE volume was 7.98 mL with a specificity of 71.4% and a sensitivity of 47.5%. Diabetes mellitus (P = 0.043, ß = 7.66 95% CI 0.26-15.07), black hole sign (P = 0.002, ß = 18.93 95% CI 6.84-31.02), and initial ICH volume (P = 0.018, ß = 0.20 95% CI 0.03-0.37) were significantly associated with iPHE volume. After adjusting for hematoma expansion, the black hole sign could still independently predict the increase of PHE (P < 0.001, ß = 21.62 95% CI 10.10-33.15). Conclusions: An increase of PHE volume >7.98 mL from baseline to day 3 may lead to poor outcome. Patients with diabetes mellitus, black hole sign, and large initial hematoma volume result in more PHE growth, which should garner attention in the treatment.