CONUT Score Predicts Early Morbidity After Liver Transplantation: A Collaborative Study

Area of Science:

• Hepatology
• Surgical Outcomes
• Nutritional Assessment

Background:

• Liver transplantation (LT) is associated with significant post-operative morbidity.
• Proactive identification of high-risk patients is crucial for optimizing perioperative resource allocation.
• The Controlling Nutritional Status (CONUT) score, a validated tool in surgery, assesses nutritional status using lymphocyte count, serum albumin, and cholesterol.

Purpose of the Study:

• To evaluate the predictive capability of the pre-operative CONUT score for early complications (within 90 days) following liver transplantation.
• To determine if the CONUT score can identify patients at risk for severe post-LT morbidity, defined by a Comprehensive Complication Index (CCI) ≥42.1.

Main Methods:

• Retrospective analysis of 209 liver transplant recipients with pre-operative CONUT scores.
• Utilized Inverse Probability Treatment Weighting to control for potential confounding factors.
• Assessed the diagnostic ability of the CONUT score using Area Under the Curve (AUC) and identified independent risk factors for complications.

Main Results:

• Patients with severe complications (CCI ≥42.1) exhibited significantly higher CONUT scores (median 7 vs. 5, P<0.0001).
• The CONUT score demonstrated good predictive accuracy for post-LT morbidity (AUC = 0.72, P<0.0001).
• The CONUT score was the sole independent predictor of a complicated post-LT course (OR = 1.39, P<0.0001), with higher scores linked to lower 90-day survival rates (87.5% vs. 98.8%).

Conclusions:

• The pre-operative CONUT score serves as a valuable and independent tool for identifying liver transplant candidates at increased risk of post-operative complications.
• The CONUT score is associated with predicting early morbidity and survival outcomes after liver transplantation.
• Further prospective studies are recommended to refine the CONUT score's composition for the specific liver transplant population.