RESEARCH FOR CLINICAL CHARACTERISTICS, IMAGES AND CORRELATION BETWEEN COMPUTED TOMOGRAPHY IN THE DIAGNOSIS OF LIVER INJURY ACCORDING TO AAST 2018 AND SELECTION OF TREATMENT METHODS AT CAN THO CENTRAL GENERAL HOSPITAL IN 2022-2024
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Abstract
Background: Liver injury is a common emergency in abdominal trauma. Early diagnosis and accurate assessment of the extent of injury are essential to choosing the most appropriate treatment method. Computed tomography is an imaging tool that has many advantages in diagnosing the extent of liver injury and accompanying damage. Objectives: To describe the clinical characteristics, imaging and correlation between computed tomography in diagnosing the severity of liver injury according to AAST 2018 and choosing treatment methods. Materials and methods: Cross-sectional descriptive study on 112 patients with liver injury diagnosed on computed tomography and had a treatment methods at Can Tho Central General Hospital from July 2022 to April 2024. Results: Objective characteristics: Male 72.3%, female 27.7%, male/female=2.6/1; the average age 36.3±14.8; common age <60 accounted for 94.6%; The most common cause was traffic accidents, accounted for 91.1%. Abdominal pain and abdominal wall signs were the most constant clinical symptoms. Most of the lesions were located in the right liver, accounted for 91,1%; the most common form on computed tomography was liver parenchymal hematoma with 72 cases, accounted for 64.3%. In 70.5% of cases, no associated abdominal organ damage was recorded. Abdominal free fluid in liver injury with a rate of 88.4%. Grading of liver injury according to AAST 2018: grade III accounted for the highest rate of 46.4%; grade V accounted for the lowest rate of 2.8%. Conservative medical treatment accounts for the highest rate of 83.9%, embolization interventions 3.6%, surgery 12.5%. Conclusion: Computed tomography plays an important role in diagnosing and grading liver injury, helping the clinic to come up with the most optimal treatment plan.
Keywords
liver injury, computed tomography, AAST 2018 classification
Article Details
References
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