Published online Nov 14, 2022. doi: 10.3748/wjg.v28.i42.6045
Peer-review started: July 1, 2022
First decision: August 1, 2022
Revised: August 13, 2022
Accepted: October 14, 2022
Article in press: October 14, 2022
Published online: November 14, 2022
Assessment of liver reserve function (LRF) is essential for predicting the prognosis of patients with chronic liver disease (CLD) and determines the extent of liver resection in patients with hepatocellular carcinoma.
To establish noninvasive models for LRF assessment based on liver stiffness measurement (LSM) and to evaluate their clinical performance.
A total of 360 patients with compensated CLD were retrospectively analyzed as the training cohort. The new predictive models were established through logistic regression analysis and were validated internally in a prospective cohort (132 patients).
Our study defined indocyanine green retention rate at 15 min (ICGR15) ≥ 10% as mildly impaired LRF and ICGR15 ≥ 20% as severely impaired LRF. We constru
The new models had a good predictive performance for LRF and could replace the indocyanine green (ICG) clearance test, especially in patients who are unable to undergo ICG testing.
Core Tip: This study aimed to establish predictive models of liver stiffness measurement (LSM) in patients with compensated chronic liver disease based on LSM and evaluate their clinical value. The results showed that the new models had a good predictive performance for liver reserve function (LRF). The area under the curve of the models was higher than that of the model for end-stage liver disease, albumin-bilirubin grade and prothrombin time international normalized ratio to albumin ratio. Moreover, the predictive performance of the new models was validated in a prospective cohort. We believe that these models could replace the indocyanine green (ICG) clearance test to assess LRF, especially in patients who are unable to undergo ICG testing.