ArticleTurkish journal of medical sciences2020
A new predictor of bleeding based on ultrasonographic features in percutaneous liver mass biopsy
Article in Turkish journal of medical sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors at 3 institutions in 1 country.
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Abstract
Background/aim: An ultrasound-guided liver mass biopsy is a method frequently used in determining the diagnosis and treatment plan.The aim of this study was to evaluate the potential new predictors of bleedingbased on ultrasonographic features in liver mass biopsies, which are frequently applied in routine clinical practice. Materials and methods: The images and data of patients aged over 18years,who underwent an imaging-guided percutaneous liver mass biopsy between January 2018 and December 2019 with various indications, were retrospectively reviewed. Liver size, liver steatosis status, parenchyma appearance, and mass vascularity on Doppler ultrasonography before the procedure, and hemoglobin (Hb) values before and after the procedure were recorded. Results: A total of 176 patients were included in the study. Ninety-six patients were male (54.5%) and 80 were female (45.5%). The mean age of the patients was 64 ± 12.3 years. The mean hemoglobin values of the patients were 11.5 ± 1.9 gr/dL before the procedure and 11.4 ± 1.5 gr/dL after the procedure. While 144 of the patients had less than 10% hemoglobin decrease (81.8%), 32 had more than 10% decrease (8.2%). In 56 patients, a heterogeneous and coarse granular pattern was observed in the liver parenchyma (31.8%). The decrease in the Hb rate was significantly higher in patients with heterogeneous and coarse granular liver parenchyma (8.7%) than in patients with normal parenchyma (6.6%) (P = 0.036). Conclusion: In our study, it was shown for the first time in the literature that the ultrasonographic appearance of the liver (heterogeneous and coarse granular parenchyma) may also be one of the parameters that can help to predict the risk of bleeding.
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