摘要
目的探讨恶性肿瘤患者医院感染情况、病原菌分布、抗菌药物耐药性、危险因素及对临床转归的影响。方法回顾性分析扬州大学附属泰州第二人民医院2022年3月至2024年3月住院治疗的320例恶性肿瘤患者的临床资料,统计患者医院感染发生情况。采集患者痰液、尿液、血液等标本,采用全自动微生物鉴定仪鉴定感染患者病原菌分布情况;采用纸片琼脂扩散法(Kirby-Bauer,K-B法)和稀释法测定最小抑菌浓度(minimum inhibitory concentration,MIC)法进行药敏试验。采用多因素Logistic回归分析探讨恶性肿瘤患者医院感染的危险因素,并构建其风险预测模型。随访至2025年6月30日,记录患者临床转归情况,统计死亡率。结果320例恶性肿瘤患者中,医院感染者85例,占26.56%。感染部位分布以呼吸系统为主,占64.71%。85例医院感染患者,分离病原菌91株,其中革兰氏阴性菌占62.64%,革兰氏阳性菌占30.77%,真菌占6.59%。革兰氏阴性菌中,肺炎克雷伯菌对氨苄西林和复方新诺明耐药率较高,分别为89.47%和84.21%;大肠埃希菌对氨苄西林耐药率较高,为94.12%;铜绿假单胞菌对复方新诺明和氨苄西林耐药率较高,分别为92.31%和84.62%。革兰氏阳性菌中,金黄色葡萄球菌对青霉素G和红霉素耐药率较高,分别为100%和87.50%。单因素分析显示,感染组与未感染组性别、体重指数、吸烟史、高血压、冠心病、高血脂、肿瘤类型、靶向治疗和免疫检查点抑制剂治疗比例比较差异均无统计学意义(均P>0.05);感染组年龄、糖尿病比例、Ⅲ~Ⅳ期、放疗+化疗比例、侵入性操作比例、不合理使用抗菌药物比例均显著高于未感染组(均P<0.05),住院时间显著长于未感染组(P<0.05)。多因素Logistic回归分析显示,年龄、糖尿病、TNM分期、放化疗情况、侵入性操作、住院时间和不合理使用抗菌药物均为恶性肿瘤患者医院感染的独立危险因素(均P<0.05)。经验证分析,受试者操作特征曲线(receiver operator characteristic curve,ROC曲线)曲线下面积为0.895(95%CI:0.838~0.951),敏感度为68.00%,特异度为92.10%。校准曲线可见该模型实际概率和预测概率与理想曲线接近,说明该模型具有良好的拟合优度。感染组死亡率显著高于未感染组(P<0.05)。结论恶性肿瘤医院感染患者以革兰氏阴性菌病原菌为主,对复方新诺明和氨苄西林耐药率较高,且受多因素影响,需采取针对性防控策略以降低医院感染发生率。
Objective Explore the hospital infection status and pathogen distribution,antibiotic resistance,risk factors,and their impact on clinical outcomes in patients with malignant tumors.Method Retrospective analysis of clinical data of 320 malignant tumor patients admitted to Taizhou Second People's Hospital affiliated to Yangzhou University from March 2022 to March 2024,and statistical analysis of hospital acquired infections in patients.Collect samples such as sputum,urine,and blood from patients,and use a fully automatic microbiological analyzer to identify the distribution of pathogens in infected patients;The paper agar diffusion method Kirby-Bauer(K-B)and dilution method were used to determine the minimum inhibitory concentration(MIC)for drug susceptibility testing.Using multiple logistic regression analysis to explore the risk factors affecting hospital acquired infections in patients with malignant tumors,and constructing a risk prediction model for them.Follow up until June 30,2025,recorded the clinical outcomes of patients and calculate the mortality rate.Result Among 320 patients with malignant tumors,85 were hospital acquired infections,accounting for 26.56%.The distribution of infection sites is mainly in the respiratory system,accounting for 64.71%.The 85 patients with hospital acquired infections,91 strains of pathogenic bacteria were isolated,of which Gram negative bacteria accounted for 62.64%,Gram positive bacteria accounted for 30.77%,and fungi accounted for 6.59%.Among Gram negative bacteria,Klebsiella pneumoniae has a higher resistance rate to ampicillin and compound sulfamethoxazole,with rates of 89.47%and 84.21%,respectively;the resistance rate of Escherichia coli to ampicillin is relatively high,at 94.12%;Pseudomonas aeruginosa has a high resistance rate to compound sulfamethoxazole and ampicillin,with rates of 92.31%and 84.62%,respectively.Among Gram positive bacteria,Staphylococcus aureus has a higher resistance rate to penicillin G and erythromycin,with rates of 100%and 87.50%,respectively.Univariate analysis showed that there was no statistically significant difference in gender,body mass index,smoking history,hypertension,coronary heart disease,hyperlipidemia,tumor type,targeted therapy,and immune checkpoint inhibitor treatment ratio between the infected and uninfected groups(all P>0.05);the age,the proportion of diabetes,stageⅢ-Ⅳ,the proportion of radiotherapy+chemotherapy,the proportion of invasive operations,and the proportion of irrational use of antibiotics in the infected group were significantly higher than those in the uninfected group(all P<0.05),and the hospital stay was significantly longer than that in the uninfected group(P<0.05).Multivariate Logistic regression analysis showed that age,diabetes,tumor node metastasis stage,radiotherapy and chemotherapy,invasive procedures,length of hospital stay and unreasonable use of antibiotics were all independent risk factors for hospital infection in patients with malignant tumors(all P<0.05).After verification and analysis,the area under the receiver operator characteristic curve(ROC curve)was 0.895(95%CI:0.838-0.951),with a sensitivity of 68.00%and a specificity of 92.10%.The calibration curve shows that the actual probability and predicted probability of the model are close to the ideal curve,indicating that the model has good goodness of fit.The mortality rate of the infected group was significantly higher than that of the uninfected group(P<0.05).Conclusion Malignant tumor hospital infection patients are mainly caused by Gram negative pathogenic bacteria,with high resistance to compound sulfamethoxazole and ampicillin,and are influenced by multiple factors.Targeted prevention and control strategies need to be adopted to reduce the occurrence of hospital infections.
作者
李娟
宗秋梅
李嵘嵘
许康睿
石志祥
薛芹
花春旺
全媛
Li Juan;Zong Qiumei;Li Rongrong;Xu Kangrui;Shi Zhixiang;Xue Qin;Hua Chunwang;Quan Yuan(Department of Infection Management,Taizhou Second People's Hospital Affiliated to Yangzhou University,Taizhou 225500,Jiangsu,China)
出处
《肿瘤综合治疗电子杂志》
2025年第5期25-32,共8页
Journal of Multidisciplinary Cancer Management(Electronic Version)
基金
江苏省卫生健康委2023年度医学科研项目(248)
泰州市科技项目(TS202316)。
关键词
恶性肿瘤
医院感染
病原菌
抗菌药物
耐药性
危险因素
临床转归
Malignant tumors
Hospital acquired infections
Pathogenic bacteria
Antibacterial drugs
Drug resistance
Risk factors
Clinical outcome
