Development of a risk prediction model for subsequent infection after colonization with carbapenem-resistant Enterobacterales: a retrospective cohort study

Guanhao Zheng, Jiaqi Cai, Han Deng, Haoyu Yang, Wenling Xiong, Erzhen Chen, Hao Bai, Juan He
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Abstract

Colonization of carbapenem-resistant Enterobacterale (CRE) is considered as one of vital preconditions for infection, with corresponding high morbidity and mortality. It is important to construct a reliable prediction model for those CRE carriers with high risk of infection. A retrospective cohort study was conducted in two Chinese tertiary hospitals for patients with CRE colonization from 2011 to 2021. Univariable analysis and the Fine-Gray sub-distribution hazard model were utilized to identify potential predictors for CRE-colonized infection, while death was the competing event. A nomogram was established to predict 30-day and 60-day risk of CRE-colonized infection. 879 eligible patients were enrolled in our study and divided into training (n = 761) and validation (n = 118) group, respectively. There were 196 (25.8%) patients suffered from subsequent CRE infection. The median duration of subsequent infection after identification of CRE colonization was 20 (interquartile range [IQR], 14–32) days. Multisite colonization, polymicrobial colonization, catheterization and receiving albumin after colonization, concomitant respiratory diseases, receiving carbapenems and antimicrobial combination therapy before CRE colonization within 90 days were included in final model. Model discrimination and calibration were acceptable for predicting the probability of 60-day CRE-colonized infection in both training (area under the curve [AUC], 74.7) and validation dataset (AUC, 81.1). Decision-curve analysis revealed a significantly better net benefit in current model. Our prediction model is freely available online at https://ken-zheng.shinyapps.io/PredictingModelofCREcolonizedInfection/ . Our nomogram has a good predictive performance and could contribute to early identification of CRE carriers with a high-risk of subsequent infection, although external validation would be required.
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耐碳青霉烯类肠杆菌定植后后续感染风险预测模型的开发:一项回顾性队列研究
耐碳青霉烯类肠杆菌(CRE)定植被认为是感染的重要先决条件之一,其发病率和死亡率也相应较高。为具有高感染风险的 CRE 携带者建立一个可靠的预测模型非常重要。一项回顾性队列研究在两家中国三级甲等医院进行,研究对象为 2011 年至 2021 年期间的 CRE 定植患者。研究采用单变量分析和Fine-Gray亚分布危险模型来确定CRE定植感染的潜在预测因素,死亡则是竞争事件。建立了一个提名图来预测 30 天和 60 天的 CRE 感染风险。我们的研究共纳入了 879 名符合条件的患者,并将其分别分为训练组(761 人)和验证组(118 人)。其中有 196 例(25.8%)患者继发了 CRE 感染。在确定 CRE 定植后,后续感染的中位持续时间为 20 天(四分位距 [IQR],14-32 天)。多部位定植、多微生物定植、导管插入和定植后接受白蛋白治疗、并发呼吸道疾病、CRE定植前 90 天内接受碳青霉烯类和抗菌药物联合治疗等情况均纳入最终模型。在训练数据集(曲线下面积 [AUC],74.7)和验证数据集(曲线下面积 [AUC],81.1)中,预测 60 天 CRE 定植感染概率的模型判别和校准均可接受。决策曲线分析表明,当前模型的净效益明显更好。我们的预测模型可在 https://ken-zheng.shinyapps.io/PredictingModelofCREcolonizedInfection/ 免费在线获取。我们的提名图具有良好的预测性能,可以帮助早期识别具有后续感染高风险的 CRE 携带者,但还需要外部验证。
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