文章摘要
胡爱玲.肝脓肿病原菌分布、耐药性及并发脓毒症风险预测模型的构建[J].安徽医药,待发表.
肝脓肿病原菌分布、耐药性及并发脓毒症风险预测模型的构建
投稿时间:2024-04-22  录用日期:2024-05-20
DOI:
中文关键词: 肝脓肿  脓毒症  危险因素  风险预测模型
英文关键词: 
基金项目:秦皇岛市科学技术研究与发展计划
作者单位地址
胡爱玲* 秦皇岛市第一医院 秦皇岛市第一医院药学部
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中文摘要:
      目的 了解秦皇岛市第一医院肝脓肿病原菌分布、耐药性;探讨影响肝脓肿并发脓毒症的危险因素,并构建预测模型。方法 顾性分析2018年1月至2023年12月在秦皇岛市第一医院确诊为肝脓肿的病人临床资料,将2018年1月至2022年12月收治的患者作为模型组(n=270),2023年1月至12月收治的患者作为验证组(n=71),模型组患者根据是否发生脓毒症分为脓毒症组(n=67)和非脓毒症组(n=203)。采用logistic回归分析发生肝脓肿脓毒症的独立危险因素,并建立肝脓肿并发脓毒症风险预测模型。再将模型应用于验证组,比较模型预测结果与实际情况的符合度。采用受试者操作特征曲线(ROC曲线)评估预测模型的性能。结果 5年来共收集菌株251株,革兰阴性菌217株占86.5%,革兰氏阳性菌12.3%。其中排前两位的是肺炎克雷伯菌(68.3%)和大肠埃希菌(6.0%)。肺炎克雷伯菌对临床常用的15种抗生素敏感性高达90%以上。大肠埃希菌对头孢呋辛、头孢曲松、复方新诺明、喹诺酮类耐药性均超过50%。对比肺炎克雷伯菌肺,大肠埃希菌炎克对临床常用的15种抗生素的敏感性具有显著差异,呈现多重耐药。多因素logistic回归分析显示,降钙素原、血糖×100/钠离子、肌酐异常升高、胸腔积液为肝脓肿并发脓毒症的独立危险因素(OR=1.019、1.138、28.208、2.576,P<0.05)。模型组ROC曲线下面积(AUC)为0.789(95%CI=0.721~0.856,P<0.001)。对应的灵敏度为64.2%,特异度为85.7 %。验证组的AUC为0.813,(95%CI=0.692~0.935,P<0.001),敏感度为83.3%,特异度为75.5%。结论 基于降钙素原、血糖×100/钠离子、肌酐异常升高、胸腔积液构建的预测模型对肝脓肿并发脓毒症发生具有较好的预测价值。
英文摘要:
      Objective To investigate the distribution and drug resistance of pathogenic bacteria in liver abscess in the First Hospital of Qinhuangdao. To investigate the risk factors of hepatic abscess with sepsis, and build a prediction model. Methods Clinical data of patients diagnosed with liver abscess in the First Hospital of Qinhuangdao from January 2018 to December 2023 were analyzed retrospectively. Patients admitted from January 2018 to December 2022 were selected as the model group (n=270), and patients admitted from January to December 2023 were selected as the validation group (n=71). Patients in the model group were divided into sepsis group (n=67) and non-sepsis group (n=203) according to whether sepsis occurred. Logistic regression was used to analyze the independent risk factors of hepatic abscess with sepsis, and the risk prediction model of hepatic abscess with sepsis was established. Then the model is applied to the verification group to compare the agreement between the model prediction results and the actual situation. Receiver operating characteristic curve (ROC curve) was used to evaluate the performance of the prediction model. Results A total of 251 strains were collected in the past 5 years, of which 86.5% were Gram-negative and 12.3% were Gram-positive. The top two were Klebsiella pneumoniae (68.3%) and Escherichia coli (6.0%). Klebsiella pneumoniae is more than 90% sensitive to 15 commonly used antibiotics. The resistance of Escherichia coli to cefuroxime, ceftriaxone, cotrimoxazole and quinolone was more than 50%. Compared with Klebsiella pneumoniae, the sensitivity of Escherichia coli to 15 commonly used antibiotics was significantly different, showing multiple drug resistance. Multivariate logistic regression analysis showed that procalcitonin, blood glucose×100/sodium ions, abnormal creatinine increase and pleural effusion were independent risk factors for hepatic abscess complicated with sepsis (OR=1.019, 1.138, 28.208, 2.576, P<0.05). The area under ROC curve (AUC) of the model group was 0.789 (95%CI= 0.721-0.856, P < 0.001). The corresponding sensitivity was 64.2% and the specificity was 85.7%. The AUC of the verification group was 0.813 (95%CI=0.692~0.935, P < 0.001), the sensitivity was 83.3%, and the specificity was 75.5%. Conclusion The prediction model based on procalcitonin, blood glucose×100/sodium ions, abnormal creatinine increase and pleural effusion has a good value in predicting the occurrence of hepatic abscess complicated with sepsis.
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