Publications by authors named "Qiufeng Wei"

Objective: Research has revealed that patients with diabetes and peripheral neuropathy exhibit significantly elevated nerve stimulation thresholds. However, the minimum stimulation thresholds of peripheral nerves in patients with diabetic foot, along with the recovery of nerve function, remain undetermined. The aim of this study is to investigate the minimum stimulation thresholds of the femoral and sciatic nerves, as well as the duration of nerve block, in patients diagnosed with diabetic foot.

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Objective: To determine the effect of esketamine in patient-controlled analgaesia after hip replacement on postoperative pain and improve sleep quality in patients.

Study Design: Randomised double-blind study. Place and Duration of the Study: Department of Anaesthesiology, The First Affiliated Hospital of Guangxi Medical University, from March 2021 to May 2022.

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Background: Perioperative anesthetic management of patients with diabetic foot undergoing surgical treatment is challenging due to their poor cardiovascular health status. According to previous literature, general anesthesia and peripheral nerve block have their own advantages and disadvantages for such patients. We reported the effect of these two anesthesia techniques on perioperative hemodynamics and prognosis in these patients.

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Purpose: In this prospective observational study, an ultrasonographic measurement of antral cross-sectional area (ACSA) was conducted to evaluate the gastric content and volume as well as to identify high-risk stomach in non-pregnant adult surgical patients adhering to preanesthetic fasting guidelines.

Patients And Methods: Fasted patients undergoing gastrointestinal endoscopy under sedation were included. Ultrasonographic measurements of ACSA were conducted in both semi-recumbent and right lateral decubitus positions before endoscopic procedures.

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Machine learning has become an important research field in genetics and molecular biology. Survival analysis using machine learning can provide an important computed-aid clinical research scheme for evaluating tumor treatment options. However, the genomic features are high-dimensional, which limits the prediction performance of the survival learning model.

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Background: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy with a rising incidence worldwide. The prognosis of HCC patients after radical resection remains poor. Radiomics is a novel machine learning method that extracts quantitative features from medical images and provides predictive information of cancer, which can assist with cancer diagnosis, therapeutic decision-making and prognosis improvement.

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Objective: Dexmedetomidine (DEX) is a potent a2-adrenoceptor agonist that has sedative, analgesic, and anxiolytic effects. Its primary clinical use is as an adjunct to general anesthesia to reduce anesthetic doses, provide analgesia and sedation in the preoperative and postoperative periods, it also used in intensive care units (ICUs). However, high concentrations of DEX may have toxic effects on neurons and cause neuronal apoptosis.

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Objective: This study was designed to evaluate the neurotoxicity of dexmedetomidine combined with ropivacaine for continuous femoral nerve block in rabbits.

Methods: Thirty New Zealand rabbits were randomly divided into 5 groups of 6 rabbits each and received a continuous femoral nerve block with saline; 0.25% ropivacaine; or 1, 2, or 3 µg/mL of dexmedetomidine added to 0.

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