Henao-Martínez Andrés F, Gross Lilyana, Mcnair Bryan, McCollister Bruce, DeSanto Kristen, Montoya Jose G, Shapiro Leland, Beckham J David
Division of Infectious Diseases, Department of Medicine, University of Colorado Denver, 12700 E. 19th Avenue, Mail Stop B168, Aurora, CO, 80045, USA.
Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA.
Mycopathologia. 2016 Dec;181(11-12):807-814. doi: 10.1007/s11046-016-0048-x. Epub 2016 Aug 8.
Cryptococcal meningitis carries a high mortality. Further understanding of immune suppression factors associated with neuroinvasive infection will improve risk stratification and enhance early diagnosis and treatment with antifungal therapy. The aim of the study was to corroborate established or find novel clinical predictors for cryptococcal meningitis. We performed a matched case-control study of Cryptococcus infection in immunocompromised patients with or without cryptococcal meningitis. Data of all patients with a diagnosis of cryptococcal disease were collected at University of Colorado Hospital between 2000 and 2015 (n = 51). Thirty patients were diagnosed with cryptococcal meningitis. We built a logistic regression model for risk factors associated with cryptococcal meningitis. The single-predictor univariate model found that a positive blood culture, positive serum cryptococcal antigen, current malignancy, and headaches were significantly associated with cryptococcal meningitis (p = 0.02). In the adjusted multivariate model, central nervous system disease was significantly associated with a diagnosis of HIV infection (OR 24.45, 95 % CI 1.62-350.37; p = 0.022) and a positive serum cryptococcal antigen test (OR 42.92, 95 % CI 3.26-555.55; p = 0.0055). In patients with HIV infection or a positive serum cryptococcal antigen, the pretest probability of neuroinvasive Cryptococcus infection is increased and an aggressive diagnostic evaluation should be conducted to exclude infection and consider empiric therapy.
隐球菌性脑膜炎死亡率很高。进一步了解与神经侵袭性感染相关的免疫抑制因素将改善风险分层，并加强抗真菌治疗的早期诊断和治疗。本研究的目的是证实已有的或寻找新的隐球菌性脑膜炎临床预测指标。我们对有或无隐球菌性脑膜炎的免疫功能低下患者的隐球菌感染进行了匹配病例对照研究。2000年至2015年期间在科罗拉多大学医院收集了所有诊断为隐球菌病患者的数据（n = 51）。30例患者被诊断为隐球菌性脑膜炎。我们建立了一个与隐球菌性脑膜炎相关危险因素的逻辑回归模型。单预测因素单变量模型发现，血培养阳性、血清隐球菌抗原阳性、当前恶性肿瘤和头痛与隐球菌性脑膜炎显著相关（p = 0.02）。在调整后的多变量模型中，中枢神经系统疾病与HIV感染诊断（比值比24.45，95%可信区间1.62 - 350.37；p = 0.022）和血清隐球菌抗原检测阳性（比值比42.92，95%可信区间3.26 - 555.55；p = 0.0055）显著相关。在HIV感染或血清隐球菌抗原阳性的患者中，神经侵袭性隐球菌感染的预测试概率增加，应进行积极的诊断评估以排除感染并考虑经验性治疗。
