Predictive factors for liver abscess liquefaction degree based on clinical, laboratory, and computed tomography data

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

Institutions

Publication Details

Journal
World Journal of Gastrointestinal Surgery
Published
2025-03-29
DOI
https://doi.org/10.4240/wjgs.v17.i4.104615
Citations
1
Primary Topic
Amoebic Infections and Treatments
Type
article
Field-Weighted Citation Impact
1.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predictive factors for liver abscess liquefaction degree based on clinical, laboratory, and computed tomography data

Hongyu Long, Feng Xie, Xin Yan, Jie Meng
1 citations
World Journal of Gastrointestinal Surgery
Amoebic Infections and Treatments
1.40
article

Predictive factors for liver abscess liquefaction degree based on clinical, laboratory, and computed tomography data

Hongyu Long, Feng Xie, Xin Yan, Jie Meng
article en
1 citations

Abstract

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.

World Journal of Gastrointestinal SurgeryVol. 17(4)
Shanxi Medical University (CN), Liaoning Provincial People's Hospital (CN), Shaanxi Provincial Hospital of Traditional Chinese Medicine (CN), Shanxi Provincial People’s Hospital (CN)
Openalex Percentile: Top 23%
Amoebic Infections and Treatments
1.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.