Dan Seejil, Shah Ansal, Justo Julie Ann, Bookstaver P Brandon, Kohn Joseph, Albrecht Helmut, Al-Hasan Majdi N
Department of Medicine, Palmetto Health Richland, Columbia, South Carolina, USA.
Department of Medicine, Palmetto Health Richland, Columbia, South Carolina, USA Department of Medicine, Division of Infectious Diseases, University of South Carolina School of Medicine, Columbia, South Carolina, USA.
Antimicrob Agents Chemother. 2016 Mar 25;60(4):2265-72. doi: 10.1128/AAC.02728-15. Print 2016 Apr.
Increasing rates of fluoroquinolone resistance (FQ-R) have limited empirical treatment options for Gram-negative infections, particularly in patients with severe beta-lactam allergy. This case-control study aims to develop a clinical risk score to predict the probability of FQ-R in Gram-negative bloodstream isolates. Adult patients with Gram-negative bloodstream infections (BSI) hospitalized at Palmetto Health System in Columbia, South Carolina, from 2010 to 2013 were identified. Multivariate logistic regression was used to identify independent risk factors for FQ-R. Point allocation in the fluoroquinolone resistance score (FQRS) was based on regression coefficients. Model discrimination was assessed by the area under receiver operating characteristic curve (AUC). Among 824 patients with Gram-negative BSI, 143 (17%) had BSI due to fluoroquinolone-nonsusceptible Gram-negative bacilli. Independent risk factors for FQ-R and point allocation in FQRS included male sex (adjusted odds ratio [aOR], 1.97; 95% confidence intervals [CI], 1.36 to 2.98; 1 point), diabetes mellitus (aOR, 1.54; 95% CI, 1.03 to 2.28; 1 point), residence at a skilled nursing facility (aOR, 2.28; 95% CI, 1.42 to 3.63; 2 points), outpatient procedure within 30 days (aOR, 3.68; 95% CI, 1.96 to 6.78; 3 points), prior fluoroquinolone use within 90 days (aOR, 7.87; 95% CI, 4.53 to 13.74; 5 points), or prior fluoroquinolone use within 91 to 180 days of BSI (aOR, 2.77; 95% CI, 1.17 to 6.16; 3 points). The AUC for both final logistic regression and FQRS models was 0.73. Patients with an FQRS of 0, 3, 5, or 8 had predicted probabilities of FQ-R of 6%, 22%, 39%, or 69%, respectively. The estimation of patient-specific risk of antimicrobial resistance using FQRS may improve empirical antimicrobial therapy and fluoroquinolone utilization in Gram-negative BSI.
氟喹诺酮耐药率(FQ-R)的不断上升限制了革兰氏阴性菌感染的经验性治疗选择,尤其是在对β-内酰胺类药物严重过敏的患者中。本病例对照研究旨在建立一种临床风险评分,以预测革兰氏阴性血流感染分离株中FQ-R的可能性。确定了2010年至2013年在南卡罗来纳州哥伦比亚市帕尔梅托健康系统住院的成年革兰氏阴性血流感染(BSI)患者。采用多因素逻辑回归分析确定FQ-R的独立危险因素。氟喹诺酮耐药评分(FQRS)中的分值分配基于回归系数。通过受试者操作特征曲线下面积(AUC)评估模型的辨别能力。在824例革兰氏阴性BSI患者中,143例(17%)的BSI是由对氟喹诺酮不敏感的革兰氏阴性杆菌引起的。FQ-R的独立危险因素及FQRS中的分值分配包括男性(调整后的优势比[aOR],1.97;95%置信区间[CI],1.36至2.98;1分)、糖尿病(aOR,1.54;95%CI,1.03至2.28;1分)、居住在专业护理机构(aOR,2.28;95%CI,1.42至3.63;2分)、30天内进行门诊手术(aOR,3.68;95%CI,1.96至6.78;3分)、90天内曾使用氟喹诺酮(aOR,7.87;95%CI,4.53至13.74;5分)或在BSI发生前91至180天内曾使用氟喹诺酮(aOR,2.77;95%CI,1.17至6.16;3分)。最终逻辑回归模型和FQRS模型的AUC均为0.73。FQRS为0、3、5或8的患者预测的FQ-R概率分别为6%、22%、39%或69%。使用FQRS评估患者特异性抗菌药物耐药风险可能会改善革兰氏阴性BSI的经验性抗菌治疗和氟喹诺酮的使用。