Liu Jia, Zhang Haixiao, Feng Dan, Wang Jiali, Wang Mingyang, Shen Biao, Cao Yigeng, Zhang Xiaoyu, Lin Qingsong, Zhang Fengkui, Zheng Yizhou, Xiao Zhijian, Zhu Xiaofan, Zhang Lei, Wang Jianxiang, Pang Aiming, Han Mingzhe, Feng Sizhou, Jiang Erlie
State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, People's Republic of China.
Infect Drug Resist. 2023 Mar 6;16:1297-1312. doi: 10.2147/IDR.S400939. eCollection 2023.
Patients with hematological diseases are at high risk of carbapenem-resistant Enterobacteriaceae (CRE) infection, and CRE-related bloodstream infection (BSI) is associated with high mortality risk. Therefore, developing a predictive risk model for subsequent BSI in hematological patients with CRE isolated from perianal swabs could be used to guide preventive strategies.
This was a single-center retrospective cohort study at a tertiary blood diseases hospital, including all hematological patients hospitalized from 10 October 2017 to 31 July 2021. We developed a predictive model using multivariable logistic regression and internally validated it using enhanced bootstrap resampling.
Of 421 included patients with CRE isolated from perianal swabs, BSI due to CRE occurred in 59. According to the multivariate logistic analysis, age (OR[odds ratio]=1.04, 95% CI[confidence interval]: 1.01-1.06, =0.004), both meropenem and imipenem minimal inhibitory concentration (MIC) of the isolate from perianal swabs>8ug/mL (OR=5.34, 95% CI: 2.63-11.5, <0.001), gastrointestinal symptoms (OR=3.67, 95% CI: 1.82-7.58, <0.001), valley absolute neutrophil count (10/L)>0.025 (OR=0.07, 95% CI: (0.02-0.19, <0.001) and shaking chills at peak temperature (OR=6.94, 95% CI: (2.60-19.2, <0.001) were independently associated with CRE BSI within 30 days and included in the prediction model. At a cut-off of prediction probability ≥ 21.5% the model exhibited a sensitivity, specificity, positive predictive value and negative predictive value of 79.7%, 85.6%, 96.27% and 47.47%. The discrimination and calibration of the prediction model were good on the derivation data (C-statistics=0.8898; Brier score=0.079) and enhanced bootstrapped validation dataset (adjusted C-statistics=0.881; adjusted Brier score=0.083). The risk prediction model is freely available as a mobile application at https://liujia1992.shinyapps.io/dynnomapp/.
A prediction model based on age, meropenem and imipenem MIC of isolate, gastrointestinal symptoms, valley absolute neutrophil count and shaking chills may be used to better inform interventions in hematological patients with CRE isolated from perianal swabs.
血液系统疾病患者发生耐碳青霉烯类肠杆菌科细菌（CRE）感染的风险较高，且CRE相关血流感染（BSI）与高死亡风险相关。因此，建立一个针对从肛周拭子中分离出CRE的血液系统疾病患者后续发生BSI的预测风险模型，可用于指导预防策略。
这是一项在三级血液疾病医院进行的单中心回顾性队列研究，纳入了2017年10月10日至2021年7月31日期间住院的所有血液系统疾病患者。我们使用多变量逻辑回归开发了一个预测模型，并使用增强型自助重抽样进行内部验证。
在421例从肛周拭子中分离出CRE的纳入患者中，59例发生了CRE所致的BSI。根据多变量逻辑分析，年龄（比值比[OR]=1.04，95%置信区间[CI]：1.01-1.06，P=0.004）、肛周拭子分离株的美罗培南和亚胺培南最低抑菌浓度（MIC）均>8μg/mL（OR=5.34，95%CI：2.63-11.5，P<0.001）、胃肠道症状（OR=3.67，95%CI：1.82-7.58，P<0.001）、谷值绝对中性粒细胞计数（×10⁹/L）>0.025（OR=0.07，95%CI：0.02-0.19，P<0.001）以及体温峰值时寒战（OR=6.94，95%CI：2.60-19.2，P<0.001）与30天内CRE BSI独立相关，并纳入预测模型。在预测概率≥21.5%的截断值时，该模型的敏感性、特异性、阳性预测值和阴性预测值分别为79.7%、85.6%、96.27%和47.47%。该预测模型在推导数据（C统计量=0.8898；Brier评分=0.079）和增强型自助验证数据集（调整后的C统计量=0.881；调整后的Brier评分=0.083）上的区分度和校准效果良好。该风险预测模型可作为移动应用程序在https://liujia1992.shinyapps.io/dynnomapp/上免费获取。
基于年龄、分离株的美罗培南和亚胺培南MIC、胃肠道症状、谷值绝对中性粒细胞计数和寒战的预测模型，可用于更好地指导对从肛周拭子中分离出CRE的血液系统疾病患者的干预措施。
