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MELD 3.0 Score and Time to Discharge After Pericardiectomy: A Competing Risks Analysis in Tuberculous Constrictive
Xiaoqiang Gao1, Shuzhen Wang1, Xin Zhang2,3,4
1Department of Cardiovascular Medicine, The Third People's Hospital of Chengdu, Chengdu 610031, China.
Journal of Clinical Medicine
|August 13, 2026
Summary
The Model for End-Stage Liver Disease (MELD) 3.0 score predicts longer hospital stays for patients undergoing pericardiectomy for tuberculous constrictive pericarditis (TCP). This score helps assess systemic congestion and perioperative risk, guiding patient management.
Area of Science:
- Cardiology
- Infectious Diseases
- Surgical Outcomes
Background:
- Tuberculous constrictive pericarditis (TCP) causes systemic venous congestion and multi-organ dysfunction.
- The prognostic value of the Model for End-Stage Liver Disease (MELD) 3.0 score in TCP is not well-established.
- Assessing preoperative risk factors is crucial for managing patients with TCP.
Purpose of the Study:
- To evaluate the preoperative MELD 3.0 score as a predictor of hospital discharge time in TCP patients undergoing pericardiectomy.
- To determine if MELD 3.0 can stratify perioperative risk in this patient population.
Main Methods:
- Analysis of 190 patients who underwent pericardiectomy for TCP (2018-2024).
- Fine-Gray competing risks regression used to assess the association between MELD 3.0 and discharge time, accounting for mortality.
- Models adjusted for age, albumin, and anti-tuberculosis therapy.
Main Results:
- Each MELD 3.0 unit increase correlated with higher operative mortality (OR 1.21, p=0.013).
- High preoperative MELD 3.0 (>9.6) independently predicted delayed discharge for total, postoperative, and ICU stays (sHRs ranging from 0.606 to 0.665).
- Preoperative albumin levels also predicted faster discharge.
Conclusions:
- The preoperative MELD 3.0 score is an independent predictor of delayed hospital discharge following pericardiectomy for TCP.
- MELD 3.0 serves as a practical tool for quantifying systemic congestion and stratifying perioperative risk in TCP patients.
- These findings can inform clinical decision-making and resource allocation for TCP management.
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