There are about 36818 clinical studies being (or have been) conducted in China. The country of the clinical trial is determined by the location of where the clinical research is being studied. Most studies are often held in multiple locations & countries.
Currently, 18F-fluorodeoxyglucose (18F-FDG) is the most widely used tumor imaging agent in clinical practice. However, the production of 18F requires accelerators and is associated with relatively high diagnostic costs, which to some extent limits its widespread clinical application. In comparison to Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT) devices are more abundant and offer lower diagnostic expenses. With the utilization of Cadmium Zinc Telluride (CZT) crystals in SPECT and advancements in image reconstruction techniques, the resolution and sensitivity of SPECT is continually improving. Therefore, the development of a simplified and cost-effective novel SPECT tumor imaging agent holds significant practical significance. This study involved the design and synthesis of a glucose-derived ligand with a linker containing seven methylene units and an isonitrile group (CN7DG). The CN7DG ligand was labeled with 99mTc to prepare a more lipophilic 99mTc-CN7DG complex, aiming to investigate a novel SPECT imaging agent for tumor imaging.
Along with aging population, cancer incidence and mortality are increasing. However, despite advances in oncology and surgery, long-term survival of cancer patients is far from optimal. Dexmedetomidine is a highly selective alpha 2 adrenergic receptor agonist with sedative, analgesic, and anxiolytic effects. Studies showed that perioperative use of dexmedetomidine reduces delirium and some non-delirium complications after surgery. In long-term follow-up studies of older patients who, for other reasons, were randomized to receive either dexmedetomidine or placebo during intra- or postoperative period, dexmedetomidine use was associated with improved long-term survival. This multicenter randomized trial aims to investigate the effect of perioperative dexmedetomidine on long-term outcomes in older patients undergoing cancer surgery.
Autism Spectrum Disorder (ASD) is a group of serious neurodevelopmental disorders. Intestinal microbial disturbance is common in children with ASD. A great deal of evidence shows that intestinal microbes can influence the brain to play its role through "gut-brain-microbiota axis". We intend to explore the role of Washed Microbiota Transplantation in improving symptoms of children in autism spectrum disorder; To study the potential etiological mechanism of autism spectrum disorder.
Recent evidences have demonstrated improved diagnostic accuracy for detecting coronary artery disease (CAD) when myocardial blood flow (MBF) is quantified in absolute terms using single photon emission tomography (SPECT) compared to conventional myocardial perfusion imaging (MPI). However, there are no uniformly accepted cutoff values of MBF and MFR derived from SPECT for diagnosing hemodynamically significant CAD. Particularly, the diagnostic performance for quantitative SPECT has not been validated using fractional flow reserve (FFR). The aim of this prospective study is to determine optimal cutoff values of absolute MBF and MFR derived from NaI (Tl)-based SPECT and to evaluate the diagnostic efficacy of this quantitative technology utilizing invasive coronary angiography (ICA) in combination with FFR results as the reference standard in patients with suspected or known CAD.
This is a multicenter, open-label, Randomized, phase Ib/II clinical study to evaluate the anti-tumor efficacy, safety, tolerability, and PK of IN10018 in combination with anti-PD-1/L1 monoclonal antibody (Tislelizumab is proposed as the combination drug) and chemotherapy (platinum and etoposide) as the first-line treatment in Extensive-stage small cell lung cancer (ES-SCLC).
Providing more theoretical basis for the prediction of the efficacy of advanced HCC and helping select better advantaged population of HCC immunotherapy to maximize the benefits of patients By exploring the relationship between the changes of PD-1 expression in peripheral blood T lymphocytes and the clinical efficacy before and after the use of PD-1 / PD-L1 inhibitors.
Single-arm, open-label, multicenter phase II clinical study
Subtype diagnosis is crucial for the treatment of primary aldosteronism (PA), which conducts the appropriate treatment strategy. Currently, adrenal venous sampling (AVS) serves as the gold standard for subtyping of PA. At present, almost all medical centers use the femoral vein approach for AVS, and most studies report that the success rate is 30%-80%. Our research team is the first in the world to conduct AVS via an antecubital approach. The aim of this study is to compare the success rate and safety of AVS via antecubital and femoral approach.
The main objective of this study was to validate the clinical effectiveness of interbody fusion with a one-segment extension for the treatment of adjacent segmental space discs in the surgical treatment of lumbar degeneration.
Nowadays, artificial intelligence technology with machine learning as the main means has been increasingly applied to the oral field, and has played an increasingly important role in the examination, diagnosis, treatment and prognosis assessment of oral diseases. Among them, machine learning is an important branch of artificial intelligence, which refers to the system learning specific statistical patterns in a given data set to predict the behavior of new data samples [8]. Machine learning is divided into two main categories: Supervised learning and Unsupervised learning. Whether there is supervision depends on whether the data entered is labeled or not. If the input data is labeled, it is supervised learning. Unlabeled learning is unsupervised. Supervised learning is a kind of learning algorithm when the correct output of the data set is known. Because the input and output are known, it means that there is a relationship between the input and output, and the supervised learning algorithm is to discover and summarize this "relationship". Unsupervised learning refers to a class of learning algorithms for unlabeled data. The absence of label information means that patterns or structures need to be discovered and summarized from the data set.