Researchers developed a multivariable model to predict clinically relevant posthepatectomy liver failure grade B and C, grade C, and 90-day mortality prediction.
By Neha MathurNov 6 2023Reviewed by Danielle Ellis, B.Sc. In a recent article published in the Annals of Surgery Journal, researchers developed a multivariable model to predict clinically relevant posthepatectomy liver failure grade B and C , grade C, and 90-day mortality prediction.
About the study Previously, researchers compared the predictive potential of the combined aspartate aminotransferase/platelet ratio index and albumin-bilirubin grade scores to APRI and ALBI alone for PHLF and found it had higher predictive potential. Moreover, combined APRI+ALBI scores better predicted chronic liver diseases by comprehensively evaluating different liver functions.
Another subcohort of 620 patients derived from the validation cohort was then used to directly compare how APRI+ALBI MVM trained on the NSQIP cohort performed against other models based on liver function tests, such as ALICE, ICG-clearance, and FIB4 concerning PHLF B+C prediction by comparing their respective areas under the curve . Notably, these tests are more expensive, time-consuming, and sometimes invasive.
Related StoriesFurthermore, APRI+ALBI-based MVM, trained in a cohort of 12,056 patients, demonstrated equal predictive potential for PHLF B+C as other prediction models based on more time-consuming and expensive liver function tests, e.g., ICG clearance and ALICE. This study relied on crude and poorly validated cutoffs for volumetry , which likely led to an underestimation of the relevance of quantifying hepatic function.
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