Center for Access and Delivery Research and Evaluation, Iowa City Veterans Affairs Health Care System, Iowa City, Iowa, USA.
Department of Internal Medicine, University of Iowa, Iowa City, Iowa, USA.
Clin Infect Dis. 2023 Nov 30;77(11):1492-1500. doi: 10.1093/cid/ciad467.
Many clinical guidelines recommend that clinicians use antibiograms to inform empiric antimicrobial therapy. However, hospital antibiograms are typically generated by crude aggregation of microbiologic data, and little is known about an antibiogram's reliability in predicting antimicrobial resistance (AMR) risk at the patient-level. We aimed to assess the diagnostic accuracy of antibiograms as a tool for selecting empiric therapy for Escherichia coli and Klebsiella spp. for individual patients.
We retrospectively generated hospital antibiograms for the nationwide Veterans Health Administration (VHA) facilities from 2000 to 2019 using all clinical culture specimens positive for E. coli and Klebsiella spp., then assessed the diagnostic accuracy of an antibiogram to predict resistance for isolates in the following calendar year using logistic regression models and predefined 5-step interpretation thresholds.
Among 127 VHA facilities, 1 484 038 isolates from 704 779 patients for E. coli and 671 035 isolates from 340 504 patients for Klebsiella spp. were available for analysis. For E. coli and Klebsiella spp., the discrimination abilities of hospital-level antibiograms in predicting individual patient AMR were mostly poor, with the areas under the receiver operating curve at 0.686 and 0.715 for ceftriaxone, 0.637 and 0.675 for fluoroquinolones, and 0.576 and 0.624 for trimethoprim-sulfamethoxazole, respectively. The sensitivity and specificity of the antibiogram varied widely by antimicrobial groups and interpretation thresholds with substantial trade-offs.
Conventional hospital antibiograms for E. coli and Klebsiella spp. have limited performance in predicting AMR for individual patients, and their utility in guiding empiric therapy may be low.
许多临床指南建议临床医生使用药敏谱来指导经验性抗菌治疗。然而,医院药敏谱通常是通过对微生物数据的粗略汇总生成的,对于药敏谱在预测患者个体水平的抗菌药物耐药性(AMR)风险方面的可靠性知之甚少。我们旨在评估药敏谱作为一种工具,用于选择针对个体患者的大肠埃希菌和肺炎克雷伯菌经验性治疗的诊断准确性。
我们使用 2000 年至 2019 年全国退伍军人健康管理局(VHA)所有临床培养标本中阳性的大肠埃希菌和肺炎克雷伯菌,回顾性地生成医院药敏谱,然后使用逻辑回归模型和预定义的 5 步解释阈值,评估下一年度药敏谱预测分离株耐药性的诊断准确性。
在 127 个 VHA 机构中,有 704779 名患者的 1274038 株大肠埃希菌和 340504 名患者的 671035 株肺炎克雷伯菌分离株可供分析。对于大肠埃希菌和肺炎克雷伯菌,医院水平药敏谱预测个体患者 AMR 的区分能力大多较差,头孢曲松的受试者工作特征曲线下面积分别为 0.686 和 0.715,氟喹诺酮类药物为 0.637 和 0.675,复方磺胺甲噁唑为 0.576 和 0.624。药敏谱的敏感性和特异性因抗菌药物种类和解释阈值而异,差异很大。
针对大肠埃希菌和肺炎克雷伯菌的传统医院药敏谱在预测个体患者的 AMR 方面表现不佳,其在指导经验性治疗方面的实用性可能较低。