Early-start antiplatelet therapy after operation in patients with spontaneous intracerebral hemorrhage and high risk of ischemic events (E-start):Protocol for a multi-centered, prospective, open-label, blinded endpoint randomized controlled trial

BACKGROUND: For severe spontaneous intracerebral hemorrhage (sSICH) patients with high risk of ischemic events, the incidence of postoperative major cardiovascular/cerebrovascular and peripheral vascular events (MACCPE) is notable. Although antiplatelet therapy is a potential way to benefit these patients, the severe hemorrhagic complications, e.g., intracranial re-hemorrhage, is a barrier for early starting antiplatelet therapy. OBJECTIVES: This randomized controlled trial aims to identify the benefit and safety of early starting antiplatelet therapy after operation for sSICH patients with high risk of ischemic events. METHODS: This study is a multicenter, prospective, randomized, open-label, blinded-endpoint trial. We will enroll 250 sSICH patients with a high risk of ischemic events (including cerebral infarcts, transient ischemic attack, myocardial infarction, pulmonary embolism, and deep venous thrombosis). The participants will be randomized in a 1:1 manner to early-start group (start antiplatelet therapy at 3 days after operation) and normal-start group (start antiplatelet therapy at 30 days after operation). The early-start group will receive aspirin 100 mg daily. The control group will not receive antithrombotic therapy until 30 days after operation. The efficacy endpoint is the incidence of MACCPE, and the safety endpoint is the incidence of intracranial re-hemorrhage. DISCUSSION: The Early-Start antiplatelet therapy after operation in patients with spontaneous intracerebral hemorrhage trial (E-start) is the first randomized trial about early start antiplatelet therapy for operated sSICH patients with a high risk of ischemic events. This study will provide a new strategy and evidence for postoperative management in the future. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, identifier NCT04820972; Available at: https://clinicaltrials.gov/ct2/show/NCT04820972?term=NCT04820972&draw=2&rank=1. Chinese Clinical Trial Registry, identifier ChiCTR2100044560; Available at: http://www.chictr.org.cn/showproj.aspx?proj=123277

Superpixel-based time-series reconstruction for optical images incorporating SAR data using autoencoder networks

Time-series reconstruction for cloud/shadow-covered optical satellite images has great significance for enhancing the data availability and temporal change analysis. In this study, we proposed a superpixel-based prediction transformation-fusion (SPTF) time-series reconstruction method for cloud/shadow-covered optical images. Central to this approach is the incorporation between intrinsic tendency from multi-temporal optical images and sequential transformation information from synthetic aperture radar (SAR) data, through autoencoder networks (AE). First, a modified superpixel algorithm was applied on multi-temporal optical images with their manually delineated cloud/shadow masks to generate superpixels. Second, multi-temporal optical images and SAR data were overlaid onto superpixels to produce superpixel-wise time-series curves with missing values. Third, these superpixel-wise time series were clustered by an AE-LSTM (long short-term memory) unsupervised method into multiple clusters (searching similar superpixels). Four, for each superpixel-wise cluster, a prediction-transformation-based reconstruction model was established to restore missing values in optical time series. Finally, reconstructed data were merged with cloud-free regions to produce cloud-free time-series images. The proposed method was verified on two datasets of multi-temporal cloud/shadow-covered Landsat OLI images and Sentinel-1A SAR data. The reconstruction results, showing an improvement of greater than 20% in normalized mean square error compared to three state-of-the-art methods (including a spatially and temporally weighted regression method, a spectral–temporal patch-based method, and a patch-based contextualized AE method), demonstrated the effectiveness of the proposed method in time-series reconstruction for multi-temporal optical images

Clinical practice guidelines for the diagnosis and treatment of adult diffuse glioma‐related epilepsy

Abstract Background Glioma‐related epilepsy (GRE) is defined as symptomatic epileptic seizures secondary to gliomas, it brings both heavy financial and psychosocial burdens to patients with diffuse glioma and significantly decreases their quality of life. To date, there have been no clinical guidelines that provide recommendations for the optimal diagnostic and therapeutic procedures for GRE patients. Methods In March 2017, the Joint Task Force for GRE of China Association Against Epilepsy and Society for Neuro‐Oncology of China launched the guideline committee for the diagnosis and treatment of GRE. The guideline committee conducted a comprehensive review of relevant domestic and international literatures that were evaluated and graded based on the Oxford Centre for Evidence‐Based Medicine Levels of Evidence, and then held three consensus meetings to discuss relevant recommendations. The recommendations were eventually given according to those relevant literatures, together with the experiences in the diagnosis and treatment of over 3000 GRE cases from 24 tertiary level hospitals that specialize in clinical research of epilepsy, glioma, and GRE in China. Results The manuscript presented the current standard recommendations for the diagnostic and therapeutic procedures of GRE. Conclusions The current work will provide a framework and assurance for the diagnosis and treatment strategy of GRE to reduce complications and costs caused by unnecessary treatment. Additionally, it can serve as a reference for all professionals involved in the management of patients with GRE