CHINAT-CD4 Score Predicts Transplant-Free Survival in Patients with Acute-on-Chronic Liver Failure

Chenlu Huang1, Weixia Li2, Chong Chen2

  • 1Department of Liver Disease, Shanghai Public Health Clinical Center, Fudan University, Shanghai, People's Republic of China.

Insights

A new score incorporating CD4+ T cell count accurately predicts 28- and 90-day mortality in acute-on-chronic liver failure (ACLF) patients. This prognostic tool aids in early evaluation and management of ACLF, potentially reducing mortality rates.

Area of Science:

  • Hepatology
  • Immunology
  • Prognostic Biomarkers

Background:

  • Early prognosis evaluation is critical for reducing mortality in acute-on-chronic liver failure (ACLF).
  • Existing prognostic scores may require enhancement for improved accuracy in diverse ACLF populations.

Purpose of the Study:

  • To develop and validate a novel prognostic score for predicting mortality in patients with ACLF.
  • To assess the predictive performance of the new score compared to existing models.

Main Methods:

  • A prognostic score was developed using a derivation set of 408 patients with hepatitis B virus-related ACLF (HBV-ACLF).
  • The score was validated in separate cohorts of HBV-ACLF (209 patients) and non-HBV-ACLF (195 patients).
  • The score incorporates factors including creatinine, hepatic encephalopathy, international normalized ratio, neutrophils, aspartate aminotransferase, total bilirubin, and CD4+ T cell count.

Main Results:

  • The novel score demonstrated strong predictive performance for 28-day and 90-day mortality, with C-indices of 0.810 and 0.806, respectively.
  • Its predictive accuracy surpassed seven other established prognostic scores.
  • Validation cohorts confirmed the score's efficacy, showing C-indices around 0.79-0.80 for both HBV-ACLF and non-HBV-ACLF groups.

Conclusions:

  • The novel prognostic score, integrating CD4+ T cell count, accurately predicts short-term and mid-term mortality in ACLF patients.
  • This score offers a valuable tool for clinical decision-making and patient management in ACLF.
Abstract

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