Predictive factors for liver abscess liquefaction degree based on clinical, laboratory, and computed tomography data
Year: 2025
Type: article
Study design: Observational Study
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.
Authors: Hong-Yu Long, Xin Yan, Jia-Xian Meng, Feng Xie
Institution: Liaoning Provincial People's Hospital
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4408933740