López de Toro Martín Consuegra I, Sánchez Casado M, Rodríguez Villar S, Raigal Caño A, López Reina Torrijos P, Velasco Ramos A, Sánchez Rodríguez P, Cabezas Martín H
Unidad de Cuidados Intensivos, Hospital Virgen de la Salud, Toledo, España.
Med Intensiva. 2010 May;34(4):246-53. doi: 10.1016/j.medin.2009.11.007. Epub 2010 Jan 21.
To evaluate eosinopenia as an early marker of infection.
Retrospective cohort study.
Medical-surgical ICU patients with high severity scores.
Data on days 1-5: Demographic data, diagnosis, clinical repercussion, mechanical ventilation, clinical development, length of stay, APACHE II, leukocytes, SOFA and lactate. Patients divided into two groups: with and without infection. ROCs (receiver operator characteristic) curves were plotted and best point for discriminative values determined.
244 patients were included: 22.5% with infection. 52.9% medical, 22.5% surgical and 24.6% polytrauma patients. APACHE II: 14.9+/-8.9. In a logistic regression model of infection (dependent variable infection), the independent variables were: APACHE II, SOFA, monocytes and eosinophils. The ROC curve for eosinophils on the first day: area of 0.72; the best cut off value is 10 eosinophils/microl, with sensitivity (S): 64.8% and specificity (Sp): 70.9%. In medical patients, the area under curve is 0.80, with ideal cut off value of 9 eosinophils/microl; in surgical patients is 0.53, with a cut off ideal value of 54. We combined eosinophils and monocytes: a cut-off value of 9 eosinophils/microl in medical patients with >400 monocytes/microl, has: S: 86.7%, Sp: 74.7%, a positive predictive value (PPV) of 40.6% and a negative predictive value (NPV) 96.6%; in postsurgical patients with <400 monocytes/microl and a cut-off value of 54 eosinophils: S: 100%, Sp: 20%, PPV: 52.9% and NPV: 100%.
In a medical-surgical ICU, the capacity to discriminate infection through examining eosinopenia is not high. It could be useful to rule out infection if we combined eosinopenia with monocytes count.
评估嗜酸性粒细胞减少作为感染的早期标志物。
回顾性队列研究。
具有高严重程度评分的内科-外科重症监护病房患者。
第1 - 5天的数据：人口统计学数据、诊断、临床影响、机械通气、临床进展、住院时间、急性生理与慢性健康状况评分系统II（APACHE II）、白细胞、序贯器官衰竭评估（SOFA）和乳酸。患者分为两组：有感染和无感染。绘制受试者工作特征（ROC）曲线并确定鉴别值的最佳点。
纳入244例患者：22.5%有感染。52.9%为内科患者，22.5%为外科患者，24.6%为多发伤患者。APACHE II评分为14.9±8.9。在感染的逻辑回归模型（因变量为感染）中，自变量为：APACHE II、SOFA、单核细胞和嗜酸性粒细胞。第一天嗜酸性粒细胞的ROC曲线：面积为0.72；最佳截断值为每微升10个嗜酸性粒细胞，敏感性（S）为64.8%，特异性（Sp）为70.9%。在内科患者中，曲线下面积为0.80，理想截断值为每微升9个嗜酸性粒细胞；在外科患者中为0.53，理想截断值为54。我们将嗜酸性粒细胞和单核细胞结合起来：内科患者中每微升嗜酸性粒细胞9个且单核细胞>400/微升时，敏感性为86.7%，特异性为74.7%，阳性预测值（PPV）为40.6%，阴性预测值（NPV）为96.6%；外科术后患者单核细胞<400/微升且嗜酸性粒细胞截断值为54时，敏感性为100%，特异性为20%，PPV为52.9%，NPV为100%。
在内科-外科重症监护病房，通过检查嗜酸性粒细胞减少来鉴别感染的能力不高。如果将嗜酸性粒细胞减少与单核细胞计数相结合，可能有助于排除感染。
