Background

Liver cirrhosis is associated with immune deficiency, which causes these patients to be susceptible to various infections, including cryptococcus infection. Mortality in cirrhotic patients with cryptococcosis has increased. The present study was to explore the risk factors of mortality and the predictive ability of different prognostic models.

Methods

Forty-seven cirrhotic patients with cryptococcosis at a tertiary care hospital were included in this retrospective study. Data on demographics, clinical parameters, laboratory exams, diagnostic methods, medication during hospitalization, severity scores and prognosis were collected and analyzed. Student's t test and Mann-Whitney test were used to compare characteristics of survivors and non-survivors at a 90-day follow-up and cerebrospinal fluid (CSF) manifestations of cryptococcal meningitis. Multivariate Cox regression analysis was used to identify the independent risk factors for mortality. Kaplan-Meier curves were used to analyze patient survival. Receiver operating characteristic (ROC) curves were used to evaluate the different prognostic factors.

Results

The 30- and 90-day survival rates were 93.6% and 80.9%, respectively, in cirrhotic patients with cryptococcosis. Cryptogenic liver diseases [hazard ratio (HR) = 7.567, 95% confidence interval (CI): 1.616-35.428, P = 0.010], activated partial thromboplastin time (APTT) (HR = 1.117, 95% CI: 1.016-1.229, P = 0.022) and Child-Pugh score (HR = 2.146, 95% CI: 1.314-3.504, P = 0.002) were risk factors for 90-day mortality in cirrhotic patients with cryptococcosis. Platelet count (HR = 0.965, 95% CI: 0.940-0.991, P = 0.008) was a protective factor. APTT (HR = 1.120, 95% CI: 1.044-1.202, P = 0.002) and Child-Pugh score (HR = 1.637, 95% CI: 1.086-2.469, P = 0.019) were risk factors for 90-day mortality in cirrhotic patients with cryptococcal meningitis. There was significant difference in the percentage of lymphocytes in CSF between survivors and non-survivors [60.0 (35.0-75.0) vs. 95.0 (83.8-97.2), P < 0.001]. The model of end-stage liver disease-sodium (MELD-Na) score was more accurate for predicting 30-day mortality both in patients with cryptococcosis [area under curve (AUC): 0.826, 95% CI: 0.618-1.000] and those with cryptococcal meningitis (AUC: 0.742, 95% CI: 0.560-0.924); Child-Pugh score was more useful for predicting 90-day mortality in patients with cryptococcosis (AUC: 0.823, 95% CI: 0.646-1.000) and those with cryptococcal meningitis (AUC: 0.815, 95% CI: 0.670-0.960).

Conclusions

These results showed that cryptogenic liver diseases, APTT and Child-Pugh score were associated with mortality in cirrhotic patients with cryptococcosis and cryptococcal meningitis. MELD-Na score was important for predicting 30-day mortality, and Child-Pugh score was critical for predicting 90-day mortality.

中文翻译：

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肝硬化患者的隐球菌病：死亡危险因素和预后模型的预测价值

背景

肝硬化与免疫缺陷有关，这导致这些患者容易受到各种感染，包括隐球菌感染。患有隐球菌病的肝硬化患者的死亡率有所增加。本研究旨在探讨死亡率的危险因素和不同预后模型的预测能力。

方法

这项回顾性研究纳入了一家三级医院的 47 名患有隐球菌病的肝硬化患者。收集和分析人口统计学、临床参数、实验室检查、诊断方法、住院期间用药、严重程度评分和预后的数据。学生t检验和 Mann-Whitney 检验用于比较 90 天随访中幸存者和非幸存者的特征以及隐球菌性脑膜炎的脑脊液 (CSF) 表现。多变量 Cox 回归分析用于确定死亡的独立危险因素。Kaplan-Meier 曲线用于分析患者存活率。受试者工作特征（ROC）曲线用于评估不同的预后因素。

结果

肝硬化隐球菌病患者的 30 天和 90 天生存率分别为 93.6% 和 80.9%。隐源性肝病 [风险比 (HR) = 7.567, 95% 置信区间 (CI): 1.616-35.428, P  = 0.010]，活化部分促凝血酶原激酶时间 (APTT) (HR = 1.117, 95% CI: 1.016-1.229, P  = 0.022) 和 Child-Pugh 评分 (HR = 2.146, 95% CI: 1.314-3.504, P  = 0.002) 是肝硬化隐球菌病患者 90 天死亡率的危险因素。血小板计数 (HR = 0.965, 95% CI: 0.940-0.991, P  = 0.008) 是一个保护因素。APTT (HR = 1.120, 95% CI: 1.044-1.202, P  = 0.002) 和 Child-Pugh 评分 (HR = 1.637, 95% CI: 1.086-2.469, P = 0.019) 是隐球菌性脑膜炎肝硬化患者 90 天死亡率的危险因素。幸存者和非幸存者的 CSF 中淋巴细胞百分比存在显着差异 [60.0 (35.0-75.0) 与 95.0 (83.8-97.2)，P < 0.001]。终末期肝病钠 (MELD-Na) 评分模型更准确地预测隐球菌病患者的 30 天死亡率 [曲线下面积 (AUC): 0.826, 95% CI: 0.618-1.000] 和那些患有隐球菌性脑膜炎（AUC：0.742，95% CI：0.560-0.924）；Child-Pugh 评分对于预测隐球菌病患者（AUC：0.823，95% CI：0.646-1.000）和隐球菌性脑膜炎患者（AUC：0.815，95% CI：0.670-0.960）的 90 天死亡率更有用。

结论

这些结果表明，隐源性肝病、APTT 和 Child-Pugh 评分与隐球菌病和隐球菌性脑膜炎肝硬化患者的死亡率相关。MELD-Na 评分对于预测 30 天死亡率很重要，而 Child-Pugh 评分对于预测 90 天死亡率至关重要。