Correlation of Pharmacokinetic/Pharmacodynamic-Derived Predictions of Antibiotic Efficacy with Clinical Outcomes in Severely Ill Patients with Pseudomonas aeruginosa Pneumonia
Correlation of Pharmacokinetic/Pharmacodynamic-Derived Predictions of Antibiotic Efficacy with Clinical Outcomes in Severely Ill Patients with Pseudomonas aeruginosa Pneumonia
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DOI：
10.1002/phar.1310
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发表时间：
2013-10-01
期刊：
影响因子：
4.1
通讯作者：
Kiser, Tyree H.
中科院分区：
文献类型：
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作者：
Fish, Douglas N.;Kiser, Tyree H.
研究目的使用药代动力学/药效学（PK/PD）模型将严重感染患者的预测抗生素疗效与实际临床结果相关联。设计回顾性队列分析。设置大学医学中心。患者共182例成人重症监护铜绿假单胞菌肺炎患者，在5- 10年期间，主要研究终点是通过PK/PD模型确定的预测抗生素疗效与个体患者实际临床结局的相关性。通过使用计算的患者特异性PK参数和已知病原体最低抑制浓度确定PD指数，并通过使用Monte Carlo模拟确定预测的PD目标达到情况，进行PK/PD分析。预测达到PD目标的患者对治疗有临床应答;预测未达到PD目标的患者治疗失败。共有128例患者（70%）明显达到了预期的PD目标;然而，PK/PD模型仅正确预测了47%的患者（86/182）的实际临床结局，灵敏度为49%，特异性为43%。在发生临床应答或临床失败的患者中，明显达到PD目标的患者比例相似（分别为67% vs 74%; p=0.344）。PD目标的预测实现仅与重症监护室和住院时间的减少显著相关。单变量或多变量分析的PD目标的实现与临床反应没有显着相关性，但与疾病严重程度相关的因素与临床respons.ConclusionPK/PD建模没有准确预测临床或微生物学的成功铜绿假单胞菌肺炎患者。本研究强调了由于极端PK变异性和疾病严重程度等问题，在个体患者水平应用PK/PD建模的困难。强烈提倡基于合理的PK/PD原则的抗生素给药，但需要更多的研究来证实PK/PD模型在优化严重细菌感染患者结局中的作用。
Study Objective To use pharmacokinetic/pharmacodynamic (PK/PD) modeling to correlate predicted antibiotic efficacy with actual clinical outcomes in patients with serious infections.DesignRetrospective cohort analysis.SettingUniversity medical center.PatientsA total of 182 adult intensive care patients with Pseudomonas aeruginosa pneumonia during a 5-year period from 2000 to 2004.Measurements and Main ResultsThe primary study end point was correlation of predicted antibiotic efficacy as determined by PK/PD modeling with actual clinical outcomes in individual patients. PK/PD analyses were conducted by determination of PD indexes using calculated patient-specific PK parameters and known pathogen minimum inhibitory concentrations, and by determination of predicted PD target attainment by using Monte Carlo simulation. Patients achieving PD targets were predicted to have clinically responded to therapy; patients not achieving PD targets were predicted to have failed therapy. A total of 128 patients (70%) apparently achieved desired PD targets; however, PK/PD modeling correctly predicted actual clinical outcome in only 47% of patients (86 of 182) with sensitivity of 49% and specificity of 43%. Percentages of patients apparently achieving PD targets were similar among those experiencing clinical response or clinical failure (67% vs 74%, respectively; p=0.344). Predicted achievement of PD targets was significantly associated only with reduction in intensive care unit and hospital lengths of stay. Achievement of PD targets was not significantly associated with clinical response by univariate or multivariate analysis, but factors related to severity of illness were significantly associated with clinical response.ConclusionPK/PD modeling did not accurately predict clinical or microbiologic success in patients with P.aeruginosa pneumonia. This study highlights the difficulties in applying PK/PD modeling at the level of the individual patient due to extreme PK variability and issues such as severity of illness. Antibiotic dosing based on sound PK/PD principles is strongly advocated, but additional studies are needed to confirm the role of PK/PD modeling in optimizing outcomes of patients with serious bacterial infections.