Wilson Varsha, Kantan Velayudhan Kunnothara, Rao Harshavardhan, Velickakathu Sukumaran Sheejamol
Internal Medicine, Amrita Institute of Medical Sciences and Research, Kochi, IND.
Gastroenterology, Amrita Institute of Medical Sciences and Research, Kochi, IND.
Cureus. 2021 Jan 11;13(1):e12643. doi: 10.7759/cureus.12643.
Introduction Chronic liver disease (CLD) or Cirrhosis is one of the most common causes of morbidity as well as mortality. Child-Turcotte-Pugh (CTP) score and the model for end-stage liver disease (MELD) are useful to assess the long-term prognosis of a patient with CLD. When a patient with CLD is admitted with an acute illness leading to systemic inflammatory response syndrome (SIRS), these scores may not be reliable to predict the short-term prognosis and survival. Absolute eosinophils count (AEC) allows the rapid identification of patients at increased risk for sepsis-related mortality in patients. Methods This was a cross-sectional study conducted among patients in a tertiary care hospital in South India during a period of one and a half years between October 2018 and April 2020. Cirrhotic patients with SIRS aged between 16 years and 80 years were included in the study. AEC was measured as a part of automated complete blood counts. Patient demographics, lab parameters, and outcomes in terms of mortality were studied. Continuous variables were expressed as mean ± SD/median and categorical variables were expressed in frequency. Receiver operating characteristic (ROC) curve analysis was used to find an ideal cutoff for AEC in predicting hospital mortality. Multi-variate Cox regression analysis was performed to find predictors of mortality. Results A total of 100 patients who fit the pre-determined criteria for cirrhosis with SIRS were enrolled in the study. Sixteen (16%) patients died at the end of the study while 84 (84%) were alive. Using a ROC curve, the area under the curve (AUC) was 0.716 with 95% CI of AUC (0.564-0.867), the p-value was found to 0.006, a cut-off of eosinophil count of 198.5 cells/uL was found to be the cut-off for the prediction of in-hospital mortality in this subset of patients with cirrhosis and sepsis with SIRS, with a sensitivity of 75% and specificity of 38.1%. In a multi-variate Cox regression analysis, only age (hazard ratio {HR}: 1.175, 95%CI, 1.084 to 1.275, p<0.001) , CRP (HR : 1.008, 95%CI, 1.00 to 1.015, p=0.042) values, total leukocyte counts (TLC) (HR: 1.226, 95%CI, 1.116 to 1.346, p<0.001) and AEC (HR: 0.993, 95%CI, 0.987 to 0.999, p=0.016) were found to be statistically significant independent predictors of mortality. Conclusions The presence of eosinopenia may be considered as an in-expensive warning biomarker for poorer clinical outcomes in the form of in-hospital mortality in hospitalized cirrhotic patients. Other biomarkers such as CRP and TLC could also play a role both independently and in conjunction with AEC to predict outcomes and mortality in cirrhotic patients with sepsis and SIRS.
引言 慢性肝病（CLD）或肝硬化是发病和死亡的最常见原因之一。Child-Turcotte-Pugh（CTP）评分和终末期肝病模型（MELD）有助于评估CLD患者的长期预后。当CLD患者因急性疾病入院导致全身炎症反应综合征（SIRS）时，这些评分可能无法可靠地预测短期预后和生存率。绝对嗜酸性粒细胞计数（AEC）有助于快速识别脓毒症相关死亡风险增加的患者。方法 这是一项横断面研究，于2018年10月至2020年4月在印度南部一家三级护理医院的患者中进行，为期一年半。纳入年龄在16岁至80岁之间患有SIRS的肝硬化患者。AEC作为自动全血细胞计数的一部分进行测量。研究了患者的人口统计学、实验室参数以及死亡率方面的结局。连续变量以均值±标准差/中位数表示，分类变量以频率表示。采用受试者工作特征（ROC）曲线分析来确定AEC预测医院死亡率的理想临界值。进行多变量Cox回归分析以寻找死亡率的预测因素。结果 共有100例符合肝硬化合并SIRS预定标准的患者纳入研究。16例（16%）患者在研究结束时死亡，84例（84%）存活。使用ROC曲线，曲线下面积（AUC）为0.716，AUC的95%置信区间为（0.564 - 0.867），p值为0.006，发现嗜酸性粒细胞计数198.5个/微升为该组肝硬化合并脓毒症及SIRS患者住院死亡率预测的临界值，敏感性为75%，特异性为38.1%。在多变量Cox回归分析中，仅年龄（风险比{HR}：1.175，95%置信区间，1.084至1.275，p<0.001）、CRP（HR：1.008，95%置信区间，1.00至1.015，p = 0.042）值、总白细胞计数（TLC）（HR：1.226，95%置信区间，1.116至1.346，p<0.001）和AEC（HR：0.993，95%置信区间，0.987至0.999，p = 0.016）被发现是死亡率的统计学显著独立预测因素。结论 嗜酸性粒细胞减少的存在可被视为住院肝硬化患者院内死亡这一较差临床结局的廉价警示生物标志物。其他生物标志物如CRP和TLC也可单独或与AEC共同发挥作用，以预测肝硬化合并脓毒症及SIRS患者的结局和死亡率。
