CD4+、CD8+T细胞监测在ICU重症患者并发获得性真菌感染临床评估中的价值分析

Value of CD4 and CD8T cell monitoring in the clinical evaluation of ICU patients with acquired fungal infection

目的:探讨重症监护室(intensive care unit,ICU)内的重症患者获得性真菌感染的特点,以及分化簇(cluster of differentiation,CD)4+、CD8+T细胞免疫功能对获得性真菌感染临床评估中的价值。方法:纳入2017年1月至2019年12月入住重庆医科大学附属第一医院重症医学科并送检标本培养出真菌阳性的患者。根据诊断标准分为真菌感染组(49例)与定植组(37例)。记录并分析急性生理学与慢性健康状况评分系统Ⅱ(acute physiology and chronic health evaluationⅡ,APACHEⅡ)评分,ICU住院时间,是否合并脓毒症、进行深静脉置管、机械通气、使用激素及广谱抗生素。收集标本取样48 h内患者体温、呼吸频率、脉率等生命体征,CD4+T细胞百分比、CD8+T细胞百分比、CD4+/CD8+比值等T细胞检测值。采用二元logistic回归进行感染危险因素分析并建立预测模型,同时获得预测概率。运用受试者工作特征(receiver operating characteristic,ROC)曲线分析上述指标对诊断真菌感染价值进行评价。结果:感染组中,APACHEⅡ评分(P=0.045)、合并脓毒症例数(P=0.049)、机械通气例数(P=0.011)、体温(P=0.049)明显高于定植组,差异具有统计学意义(P<0.05)。其余指标在评估真菌感染与定植的比较中没有统计学意义(P>0.05)。对首次培养结果不同的菌株种类进行亚组分析,发现各组别间T细胞检测值无统计学差异(P>0.05)。进行logistic回归分析感染组与定植组中T细胞检测值建立预测模型一,对其预测概率进行分析(P=0.013);再对合并脓毒症例数与T细胞检测值分析所得的预测概率(预测模型二)进行分析(P=0.024);对ICU入住时间、APACHEⅡ评分、合并脓毒症、进行深静脉置管、机械通气、使用激素、使用广谱抗生素、T细胞检测值分析所得预测概率(预测模型三)进行分析(P=0.025)。根据ROC曲线分析APACHEⅡ评分[曲线下面积(area under curve,AUC)=0.577]、体温(AUC=0.487)、CD4+T细胞(AUC=0.515)、CD8+T细胞(AUC=0.565)及CD4+/CD8+比值(AUC=0.438)。预测模型一(AUC=0.611)及预测模型二(AUC=0.653)对评估获得性真菌感染的诊断价值较低。预测模型三(AUC=0.757)对评估获得性真菌感染的诊断价值更高。结论:ICU重症患者中合并脓毒症、机械通气者更易感染真菌;合并脓毒症的患者结合CD4+T细胞、CD8+T细胞检测值,对获得性真菌感染的诊断具有提示性作用;且当脓毒症患者入住ICU时存在诸如侵入性操作、激素及广谱抗生素使用等危险因素后,更容易发生获得性真菌感染。

Objective:To explore the characteristics of acquired fungal infections in critically ill patients in the intensive care unit(ICU),and the value of CD4+ and CD8+T cell immune function in the clinical evaluation of acquired fungal infections. Methods:The fungus-positive patients admitted to the Department of Critical Care Medicine of The First Affiliated Hospital of Chongqing Medical University from January 2017 to December 2019 were included in the study. According to the diagnostic criteria,they were divided into fungal infection group(49 cases) and colonization group(37 cases). The acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)scores,days of ICU,whether there was complication of sepsis,deep venous catheterization,mechanical ventilation,the use of hormones and broad-spectrum antibiotics were recorded and analyzed. The patients’ vital signs such as body temperature,respiratory rate and pulse rate,and the test values of T cells such as the percentage of CD4+T cells,CD8+T cells percentage and the ratio of CD4+/CD8+were collected from specimens within 48 h. Binary logistic regression was used to analyze the risk factors of infection and establish a prediction model,meanwhile the predictive probability was obtained. The receiver operating characteristic(ROC) curve was used to analyze the above indicators and evaluate the diagnostic value of fungal infections. Results :In the infection group,the APACHE Ⅱ score(P =0.045),the number of cases with sepsis(P=0.049),the number of mechanical ventilation cases(P=0.011),and the body temperature(P=0.049)were significantly higher than those in the colonization group. It is statistically significant(P <0.05). The other indicators were not statistically significant in evaluating the comparison of fungal infection and colonization(P >0.05). According to the subgroup analysis of different strains of the first culture results,it was found that there was no statistical difference in the T cell detection value among different groups(P>0.05). Logistic regression analysis was carried out to analyze the T cell detection values in the infection group and the colonization group and to establish a prediction model 1,and its prediction probability was analyzed(P=0.013);then the prediction probability(prediction model 2) of the number of patients complicated with sepsis and the T cell detection value was analyzed(P=0.024);the predicted probability of ICU duration,APACHE Ⅱ scores,sepsis complication,deep venous catheterization,mechanical ventilation,use of hormones,use of broad-spectrum antibiotics,and T cell detection values(prediction model 3) were analyzed(P=0.025). According to ROC curve analysis,the area under curve(AUC) of APACHE Ⅱ scores was 0.577,body temperature(0.487),CD4+T cells(0.515),CD8+T cells(0.565) and CD4+/CD8+ratio(0.438). Prediction model 1(AUC =0.611) and prediction model 2(AUC=0.653) were of low value in evaluating the diagnosis of acquired fungal infections. Prediction model 3(AUC=0.757)was of higher diagnostic value for evaluating acquired fungal infection. Conclusion :Severe ICU patients with sepsis or mechanical ventilation are more susceptible to fungal infection;while patients with sepsis combined with the detection of CD4+T cells and CD8+T cells,it has a suggestive effect on the diagnosis of acquired fungal infection;and when patients with sepsis are admitted to the ICU and have risk factors of fungal infection such as invasive procedures,hormones and broad-spectrum antibiotics,they are more susceptible to fungal infections.