Risk Factors of Tumor Patients with Peripherally Inserted Central Catheter Related Thrombosis and Nursing Intervention Analysis Mediated by Algorithm-Based Ultrasound Images

Abstract

This paper aimed to explore the risk factors of peripherally inserted central catheter (PICC) related thrombosis (PICC-RT) in tumor patients mediated by ultrasound images under minimum variance (MV) algorithm and put forward the corresponding nursing intervention methods based on the risk factors. The smoothing algorithm, diagonal loading algorithm, and coherence factor algorithm were optimized via MV algorithm. The optimized algorithm was compared with other algorithms to analyze its image quality and image processing speed. Literature retrieval was conducted to analyze the risk factors of PICC-RT in tumor patients. Tumor patients who received PICC for chemotherapy in the hospital from June 2018 to December 2019 were selected. Patients who were accepted before the experiment were taken as the controls, and there were control group (89 cases) and observation group (91 cases). Exercise, average flow rate of axillary vein per unit time, and PICC-RT were compared between the two groups. The results showed that the optimized algorithm (MV-N) had better image resolution, image contrast, and calculation speed than other algorithms. Gender, body mass index (BMI), pathological type, clinical stage, disease history, fibrinogen (FIB), and use of anticoagulant drugs were risk factors for PICC-RT in tumor patients. The number of PICC-RT and complications in the observation group was notably lower in contrast to the control group ( $P<0.05$ ). It indicated that a novel algorithm was successfully established, which could increase the ultrasonic image quality and computing speed, and upper limb exercise could reduce the incidence of PICC-RT and its complications in tumor patients.