View clinical trials related to Liver Injury.
Filter by:The goal of this observational study is to investigate the risk factors of PD-1/PD-L1 inhibitor-associated liver injury, to construct a prediction model for the occurrence of liver injury. The main questions it aims to answer are: - Exploring risk factors for liver injury. - Constructing a Predictive Model for the Occurrence of Liver Injury in PD-1/PD-L1 Inhibitor-Related Liver Injury. - Improving immunotherapy protocols for lung cancer patients.
Searching for new targets for the diagnosis and treatment of liver ischemia-reperfusion injury.
Sepsis is a clinical syndrome with high morbidity and high fatality rate in emergency department. Patients with acute liver or kidney injury are more likely to develop Multiple Organ Dysfunction Syndrome(MODS) secondary to the non-hepatic injury group, and the prognosis deteriorates significantly. At present, there is no unified diagnostic criteria for acute liver injury associated with sepsis, and the commonly used prognostic evaluation system is rarely included in liver injury indicators, which is not good for practicality.
Heat stroke is a clinical syndrome with high incidence and high fatality rate in summer. Patients with liver, kidney, and brain damage are prone to secondary MODS, and the prognosis is poor due to high medical costs. At present, there is no unified diagnostic criteria for acute liver injury associated with heat stroke, and the commonly used prognosis scores are rarely included in liver injury indicators, which is not good for practicality.
Unrecognized abdominal and pelvic injuries can result in catastrophic disability and death. Sporadic reports of "occult" injuries have generated concern, and physicians, fearing that they may miss such an injury, have adopted the practice of obtaining computed tomography on virtually all patients with significant blunt trauma. This practice exposes large numbers patients to dangerous radiation at considerable expense, while detecting injuries in a small minority of cases. Existing data suggest that a limited number of criteria can reliably identify blunt injury victims who have "no risk" of abdominal or pelvic injuries, and hence no need for computed tomography (CT), without misidentifying any injured patient. It is estimated that nationwide implementation of such criteria could result in an annual reduction in radiographic charges of $75 million, and a significant decrease in radiation exposure and radiation induced malignancies. This study seeks to determine whether "low risk" criteria can reliably identify patients who have sustained significant abdominal or pelvic injuries and safely decrease CT imaging of blunt trauma patients. This goal will be accomplished in the following manner: All blunt trauma victims undergoing computed tomography of the abdomen/pelvis in the emergency department will undergo routine clinical evaluations prior to radiographic imaging. Based on these examinations, the presence or absence of specific clinical findings (i.e. abdominal/pelvic/flank pain, abdominal/pelvic/flank tenderness, bruising abrasions, distention, hip pain, hematuria, hypotension, tachycardia, low or falling hematocrit, intoxication, altered sensorium, distracting injury, positive FAST imaging, dangerous mechanism, abnormal x-ray imaging) will be recorded for each patient, as will the presence or absence of abdominal or pelvic injuries. The clinical findings will serve as potential imaging criteria. At the completion of the derivation portion of the study the criteria will be examined to find a subset that predicts injury with high sensitivity, while simultaneously excluding injury, and hence the need for imaging, in the remaining patients. These criteria will then be confirmed in a separate validation phase of the study. The criteria will be considered to be reliable if the lower statistical confidence limit for the measured sensitivity exceeds 98.0%. Potential reductions in CT imaging will be estimated by determining the proportion of "low-risk" patients that do not have significant abdominal or pelvic injuries.
Assessing the volume of the liver before surgery, predicting the volume of liver remaining after surgery, detecting primary or secondary lesions in the liver parenchyma are common applications that require optimal detection of liver contours, and therefore liver segmentation. Several manual and laborious, semi-automatic and even automatic techniques exist. However, severe pathology deforming the contours of the liver (multi-metastatic livers...), the hepatic environment of similar density to the liver or lesions, the CT examination technique are all variables that make it difficult to detect the contours. Current techniques, even automatic ones, are limited in this type of case (not rare) and most often require readjustments that make automatisation lose its value. All these criteria of segmentation difficulties are gathered in the livers of hepatorenal polycystosis, which therefore constitute an adapted study model for the development of an automatic segmentation tool. To obtain an automatic segmentation of any lesional liver, by exceeding the criteria of difficulty considered, investigators have developed a convolutional neural network (artificial intelligence - deep learning) useful for clinical practice.
The most common toxicity of TP (docetaxel and cisplatin) chemotherapy is chemotherapy-induced liver injury. However, patients don't always experience same chemotherapy-induced liver injury for the same drugs. Therefore, the investigators designed the present study to clarify risk factors associated with the development of severe hepatotoxicity after therapy with docetaxel and cisplatin for nasopharyngeal carcinoma (NPC).
This is an open , multicenter, interventional clinical trial to conform the role of of miR-122 a real-time detection biomarker of drug-induced liver injury by chemotherapy.
This purpose of this study is to evaluate the evaluate the efficacy of Magnesium Isoglycyrrhizinate Injection in the prevention of antineoplastic chemotherapy related acute liver injury.