碳青霉烯类耐药肺炎克雷伯菌致血流感染风险预测模型的构建
R969.3; 目的 构建碳青霉烯类耐药肺炎克雷伯菌(CRKP)致血流感染(BSI)风险预测模型.方法 回顾性分析秦皇岛市第一医院2019年1月-2022年6月253例肺炎克雷伯菌致BSI患者的临床资料,将2019年1月-2021年12月收治的患者(223例)作为模型组,2022年1-6月收治的患者(30例)作为验证组.根据是否检出CRKP将模型组患者分为CRKP亚组(56例)和碳青霉烯类敏感肺炎克雷伯菌(CSKP)亚组(167例),对两亚组患者性别、年龄、合并基础疾病等基本信息进行单因素分析和多因素Logistic分析,筛选CRKP致BSI的独立危险因素并构建风险预测模型;以验证组患者为对象...
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| Published in | 中国药房 Vol. 35; no. 1; pp. 75 - 79 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
秦皇岛市第一医院药学部,河北 秦皇岛 066000
2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-0408 |
| DOI | 10.6039/j.issn.1001-0408.2024.01.13 |
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| Abstract | R969.3; 目的 构建碳青霉烯类耐药肺炎克雷伯菌(CRKP)致血流感染(BSI)风险预测模型.方法 回顾性分析秦皇岛市第一医院2019年1月-2022年6月253例肺炎克雷伯菌致BSI患者的临床资料,将2019年1月-2021年12月收治的患者(223例)作为模型组,2022年1-6月收治的患者(30例)作为验证组.根据是否检出CRKP将模型组患者分为CRKP亚组(56例)和碳青霉烯类敏感肺炎克雷伯菌(CSKP)亚组(167例),对两亚组患者性别、年龄、合并基础疾病等基本信息进行单因素分析和多因素Logistic分析,筛选CRKP致BSI的独立危险因素并构建风险预测模型;以验证组患者为对象,对所建模型进行验证.结果 患者入住重症监护病房(ICU)、使用免疫抑制剂和经验性抗感染治疗中使用碳青霉烯类抗菌药物、抗革兰氏阳性球菌药物是CRKP致BSI的独立危险因素(比值比分别为3.749、3.074、2.909、9.419,95%置信区间分别为1.639～8.572、1.292～7.312、1.180～7.717、2.877～30.840,P＜0.05);所建风险预测模型的P值为0.365,模型受试者工作特征曲线的曲线下面积(AUC)为0.848(95%置信区间为0.779～0.916,P＜0.001),分值临界值为6.5.用于验证组患者时,模型预测的总体准确率为86.67%,其生存曲线的AUC为0.926(95%置信区间为0.809～1.000,P＜0.001).结论 患者入住ICU、使用免疫抑制剂和经验性抗感染治疗中使用碳青霉烯类抗菌药物、抗革兰氏阳性球菌药物是CRKP致BSI的独立危险因素;基于上述因素所建的CRKP致BSI风险预测模型的预测准确性良好. |
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| AbstractList | R969.3; 目的 构建碳青霉烯类耐药肺炎克雷伯菌(CRKP)致血流感染(BSI)风险预测模型.方法 回顾性分析秦皇岛市第一医院2019年1月-2022年6月253例肺炎克雷伯菌致BSI患者的临床资料,将2019年1月-2021年12月收治的患者(223例)作为模型组,2022年1-6月收治的患者(30例)作为验证组.根据是否检出CRKP将模型组患者分为CRKP亚组(56例)和碳青霉烯类敏感肺炎克雷伯菌(CSKP)亚组(167例),对两亚组患者性别、年龄、合并基础疾病等基本信息进行单因素分析和多因素Logistic分析,筛选CRKP致BSI的独立危险因素并构建风险预测模型;以验证组患者为对象,对所建模型进行验证.结果 患者入住重症监护病房(ICU)、使用免疫抑制剂和经验性抗感染治疗中使用碳青霉烯类抗菌药物、抗革兰氏阳性球菌药物是CRKP致BSI的独立危险因素(比值比分别为3.749、3.074、2.909、9.419,95%置信区间分别为1.639～8.572、1.292～7.312、1.180～7.717、2.877～30.840,P＜0.05);所建风险预测模型的P值为0.365,模型受试者工作特征曲线的曲线下面积(AUC)为0.848(95%置信区间为0.779～0.916,P＜0.001),分值临界值为6.5.用于验证组患者时,模型预测的总体准确率为86.67%,其生存曲线的AUC为0.926(95%置信区间为0.809～1.000,P＜0.001).结论 患者入住ICU、使用免疫抑制剂和经验性抗感染治疗中使用碳青霉烯类抗菌药物、抗革兰氏阳性球菌药物是CRKP致BSI的独立危险因素;基于上述因素所建的CRKP致BSI风险预测模型的预测准确性良好. |
| Abstract_FL | OBJECTIVE To construct a risk prediction model for bloodstream infection(BSI)induced by carbapenem-resistant Klebsiella pneumoniae(CRKP).METHODS Retrospective analysis was conducted for clinical data from 253 patients with BSI induced by K.pneumoniae in the First Hospital of Qinhuangdao from January 2019 to June 2022.Patients admitted from January 2019 to December 2021 were selected as the model group(n=223),and patients admitted from January 2022 to June 2022 were selected as the validation group(n=30).The model group was divided into the CRKP subgroup(n=56)and the carbapenem-sensitive K.pneumoniae(CSKP)subgroup(n=167)based on whether CRKP was detected or not.The univariate and multivariate Logistic analyses were performed on basic information such as gender,age and comorbid underlying diseases in two subgroups of patients;independent risk factors were screened for CRKP-induced BSI,and a risk prediction model was constructed.The established model was verified with patients in the validation group as the target.RESULTS Admissioning to intensive care unit(ICU),use of immunosuppressants,empirical use of carbapenems and empirical use of antibiotics against Gram-positive coccus were independent risk factors of CRKP-induced BSI(ORs were 3.749,3.074,2.909,9.419,95%CIs were 1.639-8.572,1.292-7.312,1.180-7.717,2.877-30.840,P＜0.05).Based on this,a risk prediction model was established with a P value of 0.365.The AUC of the receiver operating characteristic(ROC)curve of the model was 0.848[95%CI(0.779,0.916),P＜0.001],and the critical score was 6.5.In the validation group,the overall accuracy of the prediction under the model was 86.67%,and the AUC of ROC curve was 0.926[95%CI(0.809,1.000],P＜0.001].CONCLUSIONS Admission to ICU,use of immunosuppressants,empirical use of carbapenems and empirical use of antibiotics against Gram-positive coccus are independent risk factors of CRKP-induced BSI.The CRKP-induced BSI risk prediction model based on the above factors has good prediction accuracy. |
| Author | 宋萍萍 魏颖 于小杰 杨文明 王娜 |
| AuthorAffiliation | 秦皇岛市第一医院药学部,河北 秦皇岛 066000 |
| AuthorAffiliation_xml | – name: 秦皇岛市第一医院药学部,河北 秦皇岛 066000 |
| Author_FL | YU Xiaojie YANG Wenming WEI Ying WANG Na SONG Pingping |
| Author_FL_xml | – sequence: 1 fullname: YU Xiaojie – sequence: 2 fullname: YANG Wenming – sequence: 3 fullname: SONG Pingping – sequence: 4 fullname: WEI Ying – sequence: 5 fullname: WANG Na |
| Author_xml | – sequence: 1 fullname: 于小杰 – sequence: 2 fullname: 杨文明 – sequence: 3 fullname: 宋萍萍 – sequence: 4 fullname: 魏颖 – sequence: 5 fullname: 王娜 |
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| Keywords | 血流感染 风险预测模型 risk prediction model risk factors 危险因素 carbapenem-resistant Klebsiella pneumoniae 碳青霉烯类耐药肺炎克雷伯菌 bloodstream infection |
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| Title | 碳青霉烯类耐药肺炎克雷伯菌致血流感染风险预测模型的构建 |
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