Long HY, Yan X, Meng JX, Xie F. Predictive factors for liver abscess liquefaction degree based on clinical, laboratory, and computed tomography data. World J Gastrointest Surg 2025; 17(4): 104615 [DOI: 10.4240/wjgs.v17.i4.104615]
Corresponding Author of This Article
Feng Xie, Department of Interventional Medicine, Jin Qiu Hospital of Liaoning Province, No. 317 Xiaonan Road, Shenhe District, Shenyang 110016, Liaoning Province, China. 15040255877@163.com
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastrointest Surg. Apr 27, 2025; 17(4): 104615 Published online Apr 27, 2025. doi: 10.4240/wjgs.v17.i4.104615
Predictive factors for liver abscess liquefaction degree based on clinical, laboratory, and computed tomography data
Hong-Yu Long, Xin Yan, Jia-Xian Meng, Feng Xie
Hong-Yu Long, Department of Radiology, The People’s Hospital of Liaoning Province, Shenyang 110016, Liaoning Province, China
Xin Yan, Department of Imaging 1, The Rehabilitation Hospital of Shaanxi Province, Xi’an 710065, Shaanxi Province, China
Jia-Xian Meng, Department of Science and Education, The People’s Hospital of Liaoning Province, Shenyang 110016, Liaoning Province, China
Feng Xie, Department of Interventional Medicine, Jin Qiu Hospital of Liaoning Province, Shenyang 110016, Liaoning Province, China
Author contributions: Long HY was responsible for the conceptualization and design of the study, literature search, and drafting of the manuscript; Yan X was in charge of data collection, organization, and analysis; Meng JX performed the critical analysis of the study, participated in data organization, and revised the manuscript; Xie F supervised the study, provided significant guidance, and finalized the manuscript as the corresponding author; All authors have read and approved the final manuscript.
Institutional review board statement: This study has passed the ethical review by the institutional review board of The People’s Hospital of Liaoning Province (No. 2023K028).
Informed consent statement: This study is a retrospective study that exempts patients from informed consent.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: Anonymized data not presented herein is available upon reasonable request from the corresponding author on rational request by any qualified researcher.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Feng Xie, Department of Interventional Medicine, Jin Qiu Hospital of Liaoning Province, No. 317 Xiaonan Road, Shenhe District, Shenyang 110016, Liaoning Province, China. 15040255877@163.com
Received: December 28, 2024 Revised: January 24, 2025 Accepted: February 20, 2025 Published online: April 27, 2025 Processing time: 93 Days and 2 Hours
Abstract
BACKGROUND
Effective management of liver abscess depends on timely drainage, which is influenced by the liquefaction degree. Identifying predictive factors is crucial for guiding clinical decisions.
AIM
To investigate the predictive factors of liver abscess liquefaction and develop a predictive model to guide optimal timing of percutaneous drainage.
METHODS
This retrospective study included 110 patients with pyogenic liver abscesses who underwent percutaneous catheter drainage. Patients were divided into a poor liquefaction group (n = 28) and a well liquefaction group (n = 82) based on the ratio of postoperative 24-hour drainage volume to abscess volume, using a cutoff value of 0.3. Clinical characteristics, laboratory indicators, and computed tomography imaging features were compared. A predictive model was constructed using logistic regression and evaluated using receiver operating characteristic curves and five-fold cross-validation.
RESULTS
Independent predictive factors for good liquefaction included the absence of diabetes [odds ratio (OR) = 0.339, P = 0.044], absence of pneumonia (OR = 0.218, P = 0.013), left-lobe abscess location (OR = 4.293, P = 0.041), cystic features (OR = 5.104, P = 0.025), and elevated preoperative serum alanine aminotransferase (ALT) levels (OR = 1.013, P = 0.041). The logistic regression model based on these factors demonstrated an area under the curve of 0.814, with a sensitivity of 90.24% and specificity of 67.86%. Five-fold cross-validation yielded an average accuracy of 83.61% and a kappa coefficient of 0.5209.
CONCLUSION
Pneumonia, diabetes, abscess location, abscess composition, and preoperative serum ALT levels are significant predictors of liver abscess liquefaction. The model can guide clinical decision-making.
Core Tip: This study identifies key clinical, laboratory, and imaging factors associated with the degree of liquefaction in pyogenic liver abscesses. A predictive model was developed based on these factors to assess the degree of liquefaction, providing valuable guidance for optimizing the timing of clinical aspiration and drainage, thereby improving patient outcomes.
