Department of Internal Medicine, University and Polytechnic La Fe Hospital, Valencia, Spain.
Unit of Infectious Diseases, University and Polytechnic La Fe Hospital, Valencia, Spain.
Clin Microbiol Infect. 2020 Nov;26(11):1507-1513. doi: 10.1016/j.cmi.2020.02.001. Epub 2020 Mar 10.
Candida auris is an emerging multidrug-resistant fungus that has been associated with nosocomial outbreaks with high rates of mortality and transmission. The aim of this study was to perform a retrospective cohort analysis of risk factors and to build a scoring method for estimating the risk of candidaemia in colonized critically ill patients.
We performed a retrospective observational cohort study of patients aged ≥15 years colonized by C. auris in the 3-year period between March 2016 and March 2019. Epidemiological, clinical, laboratory and microbiological data were collected. We developed a predictive model for candidaemia using elastic net multivariable logistic regression techniques, assessed its discriminative capacity, and internally validated it using bootstrap resampling.
Two-hundred and six patients were enrolled in the cohort for derivation and internal validation. Thirty-seven out of 206 patients developed candidaemia. Total parenteral nutrition was the foremost risk factor (adjusted OR 3.73); previous surgery (adjusted OR 1.03), sepsis (adjusted OR 1.75), previous exposure to antifungal agents (adjusted OR 1.17), arterial catheters (adjusted OR 1.46), central venous catheters (adjusted OR 1.21), presence of advanced chronic kidney disease (adjusted OR 1.35) and multifocal colonization (adjusted OR of unifocal colonization 0.46) were proven to be independent predictors of candidaemia in our cohort. The corresponding area under the curve (AUC) of the elastic net regularized predictive model was 0.89 (95%CI 0.826; 0.951). After performing the internal validation by generating 500 bootstrap replications, the model still showed great accuracy, with a resulting AUC of 0.84.
Our study provides evidence on the independent predisposing factors for candidaemia. It may help predict its estimated risk and may identify a high-risk population that could benefit from early or prophylactic antifungal treatment after external validation in other cohorts.
耳念珠菌是一种新兴的耐多药真菌,与医院内暴发的高死亡率和高传播率有关。本研究的目的是对危险因素进行回顾性队列分析,并建立一种评分方法来估计定植于危重症患者的念珠菌血症的风险。
我们对 2016 年 3 月至 2019 年 3 月期间 3 年内定植于耳念珠菌的年龄≥15 岁的患者进行了回顾性观察性队列研究。收集了流行病学、临床、实验室和微生物学数据。我们使用弹性网络多变量逻辑回归技术开发了一种念珠菌血症预测模型,评估了其区分能力,并使用自举重采样对内进行了验证。
该队列共纳入 206 例患者进行推导和内部验证。206 例患者中有 37 例发生了念珠菌血症。全胃肠外营养是最重要的危险因素(调整后的 OR 3.73);先前的手术(调整后的 OR 1.03)、脓毒症(调整后的 OR 1.75)、先前使用抗真菌药物(调整后的 OR 1.17)、动脉导管(调整后的 OR 1.46)、中心静脉导管(调整后的 OR 1.21)、存在晚期慢性肾脏病(调整后的 OR 1.35)和多灶定植(调整后的单灶定植 OR 0.46)被证明是本队列中念珠菌血症的独立预测因素。弹性网络正则化预测模型的相应曲线下面积(AUC)为 0.89(95%CI 0.826;0.951)。通过生成 500 次自举复制进行内部验证后,该模型仍具有很高的准确性,AUC 为 0.84。
本研究提供了与念珠菌血症相关的独立危险因素的证据。它可以帮助预测其估计风险,并可能在其他队列中进行外部验证后,确定可能受益于早期或预防性抗真菌治疗的高危人群。