Decoding the biology and clinical implication of neutrophils in intracranial aneurysm.

OBJECTIVE: Abundant neutrophils have been identified in both ruptured and unruptured intracranial aneurysm (IA) domes, with their function and clinical implication being poorly characterized. MATERIALS AND METHODS: We employed single-cell RNA sequencing (scRNA-Seq) datasets of both human and murine model, and external bulk mRNA sequencing datasets to thoroughly explore the features and functional heterogeneous of neutrophils infiltrating the IA dome. RESULTS: We found that both unruptured and ruptured IA dome contain a substantial population of neutrophils, characterized by FCGR3B, G0S2, CSF3R, and CXCR2. These cells exhibited heterogeneity in terms of function and differentiation. Despite similar transcriptional activation, neutrophils in IA dome expressed a repertoire of gene programs that mimicked transcriptomic alterations observed from bone marrow to peripheral blood, showing self-similarity. In addition, the recruitment of neutrophils in unruptured IA was primarily mediated by monocytes/macrophages, and once ruptured, both neutrophils, and a specific subset of inflammatory smooth muscle cells (SMCs) were involved in the process. The receiver operator characteristic curve (ROC) analysis indicated that distinct neutrophil subclusters were associated with IA formation and rupture, respectively. By reviewing current studies, we found that neutrophils play a detrimental role to IA wall integrity through secreting specific ligands, ferroptosis driven by ALOX5AP and PTGS2, and the formation of neutrophil extracellular traps (NETs) mediated by PADI4. INTERPRETATION: This study delineated the biology and potential clinical implications of neutrophils in IA dome and provided a reliable basis for future researches.

Decoding the Cell Atlas and Inflammatory Features of Human Intracranial Aneurysm Wall by Single-Cell RNA Sequencing.

BACKGROUND: Intracranial aneurysm (IA) is common and occasionally results in life-threatening hemorrhagic strokes. However, the cell architecture and inflammation in the IA dome remain less understood. METHODS AND RESULTS: Single-cell RNA sequencing was performed on ruptured and unruptured human IA domes for delineating the cell atlas, gene expression perturbations, and inflammation features. Two external bulk mRNA sequencing-based data sets and serological results of 126 patients were collected for validation. As a result, a total of 21 332 qualified cells were captured. Vascular cells, including endothelial cells, smooth muscle cells, fibroblasts, and pericytes, were assigned in extremely sparse numbers (4.84%), and were confirmed by immunofluorescence staining. Pericytes, characterized by ABCC9 and HIGD1B, were identified in the IA dome for the first time. Abundant immune cells were identified, with the proportion of monocytes/macrophages and neutrophils being remarkably higher in ruptured IA. The lymphocyte compartment was also thoroughly categorized. By leveraging external data sets and machine learning algorithms, macrophages were robustly associated with IA rupture, irrespective of their polarization status. The single nucleotide polymorphism rs2280543, which is identified in East Asian populations, was associated with macrophage metabolic reprogramming through regulating TALDO1 expression. CONCLUSIONS: This study provides insights into the cellular architecture and inflammatory features in the IA dome and may enlighten novel therapeutics for unruptured IA.

Ivy Sign: Usefulness in Diagnosis and Prognosis Prediction of Moyamoya Disease.

BACKGROUND: Moyamoya disease (MMD) cannot be found commonly as a rare type compared with other vascular disease, such as aneurysm. However, it cannot be ignored for its high fatality and disability rates. In addition, exact pathogenesis study of this disease is still on the way. The ivy sign is always observed in MMD, but the clinical importance of this sign in MMD isn't clearly known. The main purpose of this research was to specifically investigate the clinical significance. METHODS: In this retrospective cohort study to gather the baseline clinical and imaging study, the patients with MMD were hospitalized from January 2016 to 2020. In the analysis, univariate and multivariate logistic regression was used to testify whether ivy sign was independently associated with MMD characteristics including cerebrovascular morphology, cerebral hemodynamics, cerebrovascular events, and postoperative collateral formation (PCF). RESULTS: We included 156 patients with 312 hemispheres. As for the result of multivariate logistic regression analysis, we could discover a fact that ivy sign was tightly connected to the Suzuki stage ≥IV (odds ratio [OR], 1.386; 95% confidence interval [CI], 1.055-1.822; P = 0.019), cerebral blood flow (CBF) decreased type (OR, 2.330; 95% CI, 1.733-3.133; P = 0.000), age acted as a protective factor for CBF (OR, 0.966; 95% CI, 0.946-0.986; P = 0.001), the elder was more likely associated with decreased CBF. Ivy sign also played a significant role in ischemic cerebrovascular events (OR, 5.653; 95% CI, 3.092-10.336; P = 0.003), their remarkable connection could be seen on the study. We could also find that ivy sign was closely connected to the good PCF (OR, 2.830; 95% CI, 1.329-6.027; P = 0.007), and we couldn't ignore the fact that age was associated with good PCF as well (OR, 0.933; 95% CI, 0.882-0.987; P = 0.015). DISCUSSION: We could be more aware of the connection between ivy sign and Moyamoya disease from this study in order to implement diagnosis, treatment, and prognosis more efficiently.

Blood-Blister Aneurysms of the Internal Carotid Artery in Tibetan and Han Populations : A Retrospective Observational Study.

Objective: Blood-blister aneurysms (BBAs) of the internal carotid artery (ICA) are challenging lesions with high morbidity and mortality rates. Although research on BBAs is well documented in different populations, the study of BBAs in the Tibetan population is extremely rare. This study aimed to evaluate the characteristics of BBAs and analyze the treatment modalities and long-term outcomes in the Tibetan population in comparison with the Han population. Methods: The characteristics of patients with BBAs of the ICA from January 2009 to January 2021 at our institution were reviewed. The features of aneurysms, treatment modalities, complications, and follow-up outcomes were retrospectively analyzed. Results: A total of 130 patients (41 Tibetan and 89 Han patients) with BBAs of the ICA who underwent treatment were enrolled. Compared with the Han group, the Tibetan group significantly demonstrated a high ratio of BBAs among ICAs (8.6%, 41/477 vs. 1.6%, 89/5563; p<0.05), a high ratio of vasospasm (34.1%, 14/41 vs. 6.7%, 6/89; p=0.001), a high risk of ischemic events (43.9%, 18/41 vs. 22.5%, 20/89; p<0.05), and a low ratio of good outcomes (modified Rankin Scale, 0-2) at the 1-year follow-up (51.2%, 21/41 vs. 74.2%, 66/89; p<0.05). The multivariate regression model showed that ischemic events significantly contributed to the prediction of outcomes at 1 year. Further analysis revealed that microsurgery and vasospasm were associated with ischemic events. Conclusion: In comparison with Han patients, the Tibetan population had a high ratio of BBA occurrence, a high incidence of ischemic events, and a high ratio of poor outcomes. The endovascular approach showed more benefits in BBA patients.

Tumor-associated macrophage-related strategies for glioma immunotherapy.

High-grade glioma is one of the deadliest primary tumors of the central nervous system. Despite the many novel immunotherapies currently in development, it has been difficult to achieve breakthrough results in clinical studies. The reason may be due to the suppressive tumor microenvironment of gliomas that limits the function of specific immune cells (e.g., T cells) which are currently the primary targets of immunotherapy. However, tumor-associated macrophage, which are enriched in tumors, plays an important role in the development of GBM and is becoming a research hotspot for immunotherapy. This review focuses on current research advances in the use of macrophages as therapeutic targets or therapeutic tools for gliomas, and provides some potential research directions.

COVPRIG robustly predicts the overall survival of IDH wild-type glioblastoma and highlights METTL1+ neural-progenitor-like tumor cell in driving unfavorable outcome.

BACKGROUND: Accurately predicting the outcome of isocitrate dehydrogenase (IDH) wild-type glioblastoma (GBM) remains hitherto challenging. This study aims to Construct and Validate a Robust Prognostic Model for IDH wild-type GBM (COVPRIG) for the prediction of overall survival using a novel metric, gene-gene (G × G) interaction, and explore molecular and cellular underpinnings. METHODS: Univariate and multivariate Cox regression of four independent trans-ethnic cohorts containing a total of 800 samples. Prediction efficacy was comprehensively evaluated and compared with previous models by a systematic literature review. The molecular underpinnings of COVPRIG were elucidated by integrated analysis of bulk-tumor and single-cell based datasets. RESULTS: Using a Cox-ph model-based method, six of the 93,961 G × G interactions were screened to form an optimal combination which, together with age, comprised the COVPRIG model. COVPRIG was designed for RNA-seq and microarray, respectively, and effectively identified patients at high risk of mortality. The predictive performance of COVPRIG was satisfactory, with area under the curve (AUC) ranging from 0.56 (CGGA693, RNA-seq, 6-month survival) to 0.79 (TCGA RNAseq, 18-month survival), which can be further validated by decision curves. Nomograms were constructed for individual risk prediction for RNA-seq and microarray-based cohorts, respectively. Besides, the prognostic significance of COVPRIG was also validated in GBM including the IDH mutant samples. Notably, COVPRIG was comprehensively evaluated and externally validated, and a systemic review disclosed that COVPRIG outperformed current validated models with an integrated discrimination improvement (IDI) of 6-16%. Moreover, integrative bioinformatics analysis predicted an essential role of METTL1+ neural-progenitor-like (NPC-like) malignant cell in driving unfavorable outcome. CONCLUSION: This study provided a powerful tool for the outcome prediction for IDH wild-type GBM, and preliminary molecular underpinnings for future research.

Perturbation of mitochondrial dynamics links to the aggravation of periodontitis by diabetes.

Diabetes and periodontitis are prevalent diseases that considerably impact global economy and diabetes is a major risk factor of periodontitis. Mitochondrial dynamic alterations are involved in many diseases including diabetes and this study aims to evaluate their relevance with diabetes aggravated periodontitis. Sixty mice are randomly divided into 4 groups: control, periodontitis, diabetes and diabetic periodontitis. Periodontitis severity is evaluated by alveolar bone loss, inflammation and oxidative stress status. Mitochondrial structural and functional defects are evaluated by the mitochondrial fission/fusion events, mitochondrial reactive oxygen species (ROS) accumulation, complex activities and adenosine triphosphate (ATP) production. Advanced glycation end product (AGE) and Porphyromonas gingivalis are closely related to periodontitis occurrence and development. Human gingival fibroblast cells (HGF-1) are used to investigate the AGE role and lipopolysaccharide (LPS) from Porphyromonas gingivalis (P-LPS) in aggravating diabetic periodontitis by mitochondrial dynamic and function alterations. In vivo, diabetic mice with periodontitis show severe bone loss, increased inflammation and oxidative stress accumulation. Among mice with periodontitis, diabetic mice show worse mitochondrial dynamic perturbations than lean mice, along with fusion protein levels inducing more mitochondrial fission in gingival tissue. In vitro, AGEs and P-LPS co-treatment causes severe.

PP-NAS: Searching for Plug-and-Play Blocks on Convolutional Neural Networks.

Multiscale features are of great importance in modern convolutional neural networks, showing consistent performance gains on numerous vision tasks. Therefore, many plug-and-play blocks are introduced to upgrade existing convolutional neural networks for stronger multiscale representation ability. However, the design of plug-and-play blocks is getting more and more complex, and these manually designed blocks are not optimal. In this work, we propose PP-NAS to develop plug-and-play blocks based on neural architecture search (NAS). Specifically, we design a new search space PPConv and develop a search algorithm consisting of one-level optimization, zero-one loss, and connection existence loss. PP-NAS minimizes the optimization gap between super-net and subarchitectures and can achieve good performance even without retraining. Extensive experiments on image classification, object detection, and semantic segmentation verify the superiority of PP-NAS over state-of-the-art CNNs (e.g., ResNet, ResNeXt, and Res2Net). Our code is available at https://github.com/ainieli/PP-NAS.

Differentiable RandAugment: Learning Selecting Weights and Magnitude Distributions of Image Transformations.

Automatic data augmentation is a technique to automatically search for strategies for image transformations, which can improve the performance of different vision tasks. RandAugment (RA), one of the most widely used automatic data augmentations, achieves great success in different scales of models and datasets. However, RA randomly selects transformations with equivalent probabilities and applies a single magnitude for all transformations, which is suboptimal for different models and datasets. In this paper, we develop Differentiable RandAugment (DRA) to learn selecting weights and magnitudes of transformations for RA. The magnitude of each transformation is modeled following a normal distribution with both learnable mean and standard deviation. We also introduce the gradient of transformations to reduce the bias in gradient estimation and KL divergence as part of the loss to reduce the optimization gap. Experiments on CIFAR-10/100 and ImageNet demonstrate the efficiency and effectiveness of DRA. Searching for only 0.95 GPU hours on ImageNet, DRA can reach a Top-1 accuracy of 78.19% with ResNet-50, which outperforms RA by 0.28% under the same settings. Transfer learning on object detection also demonstrates the power of DRA. The proposed DRA is one of the few that surpasses RA on ImageNet and has great potential to be integrated into modern training pipelines to achieve state-of-the-art performance. Our code will be made publicly available for out-of-the-box use.

Nomogram to Predict Good Collateral Formation After the STA-MCA Bypass Surgery in Adult Patients With Moyamoya Disease.

BACKGROUND: Collateral formation from the extracranial carotid artery to ischemic brain tissue determines the clinical success of superficial temporal artery (STA) to middle cerebral artery (MCA) bypass surgery in adult patients with moyamoya disease, but postoperative collateral formation (PCF) after STA-MCA bypass surgery is unpredictable. Accurate preoperative prediction of acceptable PCF could improve patient selection. This study aims to develop a prediction nomogram model for PCF in this patient population. METHODS: Adult patients with moyamoya disease undergoing the STA-MCA bypass surgery between January 2013 and December 2020 at a single institution were retrospectively or prospectively enrolled in this observational study. Data including potential clinical and radiological predictors were obtained from hospital records. A nomogram was generated based on a multivariate logistic regression analysis, to identify potential predictors associated with good PCF. The performance of the nomogram was evaluated for discrimination, calibration, and clinical utility. RESULTS: Data from 243 patients with moyamoya disease who underwent the STA-MCA bypass surgery were analyzed to build the nomogram. After 1-year follow-up, 162 (66.7%) hemispheres had good PCF and 81 (33.3%) had poor PCF. Good PCF is associated with 3 preoperative factors: age at operation, a diameter of donor branch of STA, and the preinfarction period stage. Incorporating these 3 factors, the model achieved a concordance index of 0.88 (95% CI, 0.84-0.92) and had a well-fitted calibration curve and good clinical application value. A cutoff value of 100 was determined to predict good PCF via this nomogram. CONCLUSIONS: The nomogram exhibits high accuracy in predicting good PCF after the STA-MCA bypass surgery in adult patients with moyamoya disease and may allow surgeons to better evaluate preoperatively candidacy for successful bypass surgery.

Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas.

Diffuse midline glioma-H3K27M mutant (DMG) and glioblastoma (GBM) are the most lethal brain tumors that primarily occur in pediatric and adult patients, respectively. Both tumors exhibit significant heterogeneity, shaped by distinct genetic/epigenetic drivers, transcriptional programs including RNA splicing, and microenvironmental cues in glioma niches. However, the spatial organization of cellular states and niche-specific regulatory programs remain to be investigated. Here, we perform a spatial profiling of DMG and GBM combining short- and long-read spatial transcriptomics, and single-cell transcriptomic datasets. We identify clinically relevant transcriptional programs, RNA isoform diversity, and multi-cellular ecosystems across different glioma niches. We find that while the tumor core enriches for oligodendrocyte precursor-like cells, radial glial stem-like (RG-like) cells are enriched in the neuron-rich invasive niche in both DMG and GBM. Further, we identify niche-specific regulatory programs for RG-like cells, and functionally confirm that FAM20C mediates invasive growth of RG-like cells in a neuron-rich microenvironment in a human neural stem cell derived orthotopic DMG model. Together, our results provide a blueprint for understanding the spatial architecture and niche-specific vulnerabilities of DMG and GBM.

GelMA/κ-carrageenan double-network hydrogels with superior mechanics and biocompatibility.

Hydrogels are crosslinked hydrophilic polymer networks of high-water content. Although they have been widely investigated, preparing hydrogels with excellent mechanical properties and biocompatibility remains a challenge. In the present work, we developed a novel GelMA/κ-carrageenan (GelMA/KC) double network (DN) hydrogel through a dual crosslinking strategy. The three-dimensional (3D) microstructure of KC is the first network, and covalently crosslinked on the κ-carrageenan backbone is the second network. The GelMA/KC hydrogel shows advantages in physical properties, including higher compression strength (10% GelMA/1% KC group, 130 kPa) and Young's modulus (10% GelMA/1% KC group, 300), suggesting its excellent elasticity and compressive capability. When using a higher concentration of GelMA, the hybrid hydrogel has even higher mechanical properties. In addition, the GelMA/KC hydrogel is favorable for cell spreading and proliferation, demonstrating its excellent biocompatibility. This study provides a new possibility for a biodegradable and high-strength hydrogel as a new generation material of orthopedic implants.

Clinical characteristics of intracranial aneurysms in elderly patents over 70 years old: a retrospective observational study.

BACKGROUND: Although the characteristics of intracranial aneurysms (IAs) in different age groups have been well documented, they remain relatively unclear in elderly patients due to a lack of large sample studies. METHODS: Data from IA patients aged more than 70 years who were treated in our centre from January 2016 to January 2020 were retrospectively collected. RESULTS: A total of 290 elderly patients (75.9% female) with a mean age of 74.0 ± 4.7 years were analysed. Rupture occurred in 60.7% of patients, 38.6% of whom presented with meningeal irritation, and seizures were noted in 2.3%. A total of 48.9% of the patients with ruptured IAs had initial symptoms presenting with slow development, and the mean delay from ictus was prolonged to 264.2 ± 914.0 hours. In addition, 61.9% of the patients with ruptured IAs had lesions with a maximum diameter of less than 5 mm. A total of 30.3% of the patients had multiple aneurysms, 35.5% had aneurysms with irregular shapes and 54.8% had cerebrovascular atherosclerotic stenosis (CAS). Pulmonary infection (n = 138, 47.6%), hydrocephalus (n = 72, 24.8%), and thrombosis (n = 35, 12.1%) were common complications during hospitalization. By the end of the 1-year follow-up, 22.1% of the patients had unfavourable clinical outcomes, and the mortality rate was 23.4%. CONCLUSIONS: Several characteristics regarding IAs in elderly patients were reported, including an obvious female predominance; mild, slow initial symptom development causing prolonged admission delay; a low incidence of meningeal irritation and seizures due to decreased electrophysiological activity of the neurons; increased percentages of CAS, multiple aneurysms, and aneurysms with daughter sacs causing a high risk of rupture even for small lesions; a high risk of complications during hospitalization; and relatively poor clinical outcomes.

Intraoperative Glioma Grading Using Neural Architecture Search and Multi-Modal Imaging.

Glioma grading during surgery can help clinical treatment planning and prognosis, but intraoperative pathological examination of frozen sections is limited by the long processing time and complex procedures. Near-infrared fluorescence imaging provides chances for fast and accurate real-time diagnosis. Recently, deep learning techniques have been actively explored for medical image analysis and disease diagnosis. However, issues of near-infrared fluorescence images, including small-scale, noise, and low-resolution, increase the difficulty of training a satisfying network. Multi-modal imaging can provide complementary information to boost model performance, but simultaneously designing a proper network and utilizing the information of multi-modal data is challenging. In this work, we propose a novel neural architecture search method DLS-DARTS to automatically search for network architectures to handle these issues. DLS-DARTS has two learnable stems for multi-modal low-level feature fusion and uses a modified perturbation-based derivation strategy to improve the performance on the area under the curve and accuracy. White light imaging and fluorescence imaging in the first near-infrared window (650-900 nm) and the second near-infrared window (1,000-1,700 nm) are applied to provide multi-modal information on glioma tissues. In the experiments on 1,115 surgical glioma specimens, DLS-DARTS achieved an area under the curve of 0.843 and an accuracy of 0.634, which outperformed manually designed convolutional neural networks including ResNet, PyramidNet, and EfficientNet, and a state-of-the-art neural architecture search method for multi-modal medical image classification. Our study demonstrates that DLS-DARTS has the potential to help neurosurgeons during surgery, showing high prospects in medical image analysis.

Ordered structure constructed from C2-symmetric hexa-peri-hexabenzocoronene linked with oligo(dimethylsiloxane).

The preparation of sub-5-nm ordered structures is very important to the development of today's nanotechnology. Block molecules have the potential to form structures with significantly small characteristic dimensions. Herein two novel organic-inorganic block molecules composed of a hexa-peri-hexabenzocoronene (HBC) core and two oligo(dimethylsiloxane) (ODMS) tails with C2 symmetry are reported. A hierarchical lamello-columnar structure with a two-dimensional rectangular lattice where HBC cores adopt a tilted arrangement was obtained from their bulk self-assembly. The feature sizes are all below 5 nm and can be regulated via the number of ODMS chains. Sub-5-nm line structures were obtained through spin-coating of the block molecules onto silicon substrates modified with poly(dimethylsiloxane). As organic-inorganic hybrid materials, these block molecules may be further applied in sub-5-nm nanopatterning.

First Clinical Investigation of Near-Infrared Window IIa/IIb Fluorescence Imaging for Precise Surgical Resection of Gliomas.

OBJECTIVE: The near-infrared window II (NIR-II, 1000-1700 nm) imaging, including NIR-IIa (1300-1400 mm) and NIR-IIb (1500-1700 mm), outperforms the near-infrared window I (NIR-I, 700-900 nm) imaging in biological researches. However, the advantages of NIR-IIa/IIb imaging in human study are ambiguous. This study aims to apply the NIR-IIa/IIb imaging to glioma resection and evaluate their performance by using the developed imaging instrument and intraoperative image fusion method. METHODS: A multispectral fluorescence imaging instrument that integrated NIR-I/II/IIa/IIb fluorescence imaging and an intraoperative image fusion method have been developed. Seven patients with grade III/IV glioma have been enrolled. NIR-I/II images of the tumor and NIR-I/II/IIa/IIb images of cerebral vessels were acquired with the administration of indocyanine green. Images were fused using the specialized fusion method to synchronously provide the distribution of the vessels and the surgical boundaries. RESULTS: The NIR-IIa/IIb imaging was successfully applied to the clinic. High imaging resolution and contrast have been attained in the NIR-IIa/IIb spectra. Besides, capillaries with an apparent diameter as small as 182 µm were acquired using NIR-IIb imaging. Tumor-feeding arteries were precisely blocked and tumors were excised to the maximum extent for all patients. The blood loss volume during surgery was significantly reduced compared with the control group. CONCLUSION: The multispectral fluorescence imaging showed high performance, which led to a significant reduction in blood loss volume. SIGNIFICANCE: The novel multispectral fluorescence imaging technology can assist surgeons in other vascular surgeries in the future.

Excitation-based fully connected network for precise NIR-II fluorescence molecular tomography.

Fluorescence molecular tomography (FMT) is a novel imaging modality to obtain fluorescence biomarkers' three-dimensional (3D) distribution. However, the simplified mathematical model and complicated inverse problem limit it to achieving precise results. In this study, the second near-infrared (NIR-II) fluorescence imaging was adopted to mitigate tissue scattering and reduce noise interference. An excitation-based fully connected network was proposed to model the inverse process of NIR-II photon propagation and directly obtain the 3D distribution of the light source. An excitation block was embedded in the network allowing it to autonomously pay more attention to neurons related to the light source. The barycenter error was added to the loss function to improve the localization accuracy of the light source. Both numerical simulation and in vivo experiments showed the superiority of the novel NIR-II FMT reconstruction strategy over the baseline methods. This strategy was expected to facilitate the application of machine learning in biomedical research.

Clipping versus coiling for aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis of prospective studies.

Neurosurgical clipping and endovascular coiling are both standard therapies to prevent rebleeding after aneurysmal subarachnoid hemorrhage (aSAH). However, controversy still exists about which is the optimal treatment. This meta-analysis aims to assess the effectiveness and safety of two treatments with high-quality evidence. Web of Science, Cochrane Library, EMBASE, Pubmed, Sinomed, China National Knowledge Infrastructure, and Wanfang Data databases were systematically searched on August 5, 2021. Randomized controlled trials (RCTs) and prospective cohort studies that evaluated the effectiveness and safety of clipping versus coiling in aSAH patients at discharge or within 1-year follow-up period were eligible. No restriction was set on the publication date. Meta-analyses were conducted to calculate the pooled estimates and 95% confidence intervals (CI) of relative risk (RR). Eight RCTs and 20 prospective cohort studies were identified. Compared to coiling, clipping was associated with a lower rebleeding rate at discharge (RR: 0.52, 95% CI: 0.29--0.94) and a higher aneurysmal occlusion rate (RR: 1.33, 95% CI: 1.19-1.48) at 1-year follow-up. In contrast, coiling reduced the vasospasm rate at discharge (RR: 1.45, 95% CI: 1.23-1.71) and 1-year poor outcome rate (RR: 1.27, 95% CI: 1.16-1.39). Subgroup analyses presented that among patients with a poor neurological condition at admission, no statistically significant outcome difference existed between the two treatments. The overall prognosis was better among patients who received coiling, but this advantage was not significant among patients with a poor neurological condition at admission. Therefore, the selection of treatment modality for aSAH patients should be considered comprehensively.