[An area under curve-based nomogram to predicts vancomycin-associated nephrotoxicity in critically ill patients: a retrospective cohort study]

Zhonghua Nei Ke Za Zhi. 2022 Mar 1;61(3):291-297. doi: 10.3760/cma.j.cn112138-20211011-00688.
[Article in Chinese]

Abstract

Objective: To develop an area under curve (AUC)-based nomogram to predict vancomycin-associated nephrotoxicity in critically ill patients. Methods: This retrospective cohort study included adult patients treated with vancomycin in the intensive care unit at a tertiary teaching hospital from January 2015 to December 2017. Baseline clinical characteristics before vancomycin treatment and pharmacokinetic parameters were collected to establish a prediction model of nephrotoxicity. Univariate analysis was used to screen variables, and multivariate logistic regression analysis was used to establish the prediction model and nomogram. Results: A total of 159 patients met the inclusion criteria, sixty-four were included in the final analysis. Sixteen patients (25%, 16/64) developed vancomycin-associated nephrotoxicity. The following variables were incorporated into the prediction model: vancomycin AUC, estimated glomerular filtration rate (GFR), and combined nephrotoxic drugs. The following equation was established to calculate the probability of nephrotoxicity: logit (P)=-4.83+0.009×AUC-2.87×1 (if GFR>60 ml/min)+2.53×1 (if number of combined nephrotoxic drugs≥2). A nomogram was generated based on the equation. The receiver-operating characteristic curve demonstrated that the AUC of the prediction model was 0.927 (95%CI 0.851-1.000). The cut-off value of the probability of nephrotoxicity was 26.48%. The sensitivity and specificity were 87.5% and 87.5% respectively. Conclusion: The incidence of vancomycin-associated nephrotoxicity is high. The AUC-based nomogram can effectively predict vancomycin-associated nephrotoxicity in critically ill patients.

目的: 探讨万古霉素曲线下面积(AUC)的列线图预测重症患者万古霉素相关肾损伤的临床应用价值。 方法: 采用回顾性队列研究的方法,纳入2015年1月至2017年12月入住东南大学附属中大医院重症医学科接受经静脉使用万古霉素治疗的重症患者。收集万古霉素治疗开始时患者的临床特征及血药浓度达到稳定状态时的药代动力学参数(包括谷浓度和峰浓度)。采用单因素分析筛选变量,多元logistic回归分析建立万古霉素相关肾损伤的预测模型和列线图。 结果: 纳入64例静脉使用万古霉素治疗的重症患者,16例(25%)发生万古霉素相关肾损伤。将万古霉素AUC、肾小球滤过率(GFR)、联合使用肾毒性药物数作为预测变量行logistic回归分析,构建预测模型,建立回归方程logit(P)=-4.83+0.009×AUC(万古霉素)-2.87×a+2.53×b。若GFR>60 ml/min时,a=1,GFR≤60 ml/min时,a=0;若联合使用肾毒性药物数≥2时,b=1,联合使用肾毒性药物数<2时,b=0。绘制预测肾损伤的列线图。受测者操作特征曲线显示,预测模型预测万古霉素相关肾损伤的AUC为0.927(95%CI 0.851~1.000)。万古霉素相关肾损伤发生率的截止值为26.48%时,其敏感度为87.5%,特异度为87.5%。 结论: 重症患者万古霉素相关肾损伤的发生率高。基于万古霉素AUC的列线图能有效预测重症患者发生万古霉素相关肾损伤。.

MeSH terms

  • Adult
  • Anti-Bacterial Agents / therapeutic use
  • Area Under Curve
  • Critical Illness*
  • Humans
  • Nomograms
  • Retrospective Studies
  • Vancomycin* / adverse effects
  • Vancomycin* / pharmacokinetics

Substances

  • Anti-Bacterial Agents
  • Vancomycin