Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA.
Drug Saf. 2012 Aug 1;35(8):645-53. doi: 10.1007/BF03261961.
Pharmacovigilance algorithms are used to assess the likelihood of adverse drug reaction (ADR) occurrence. The preferred instrument for use in the intensive care unit (ICU) is not established.
The primary objective of this study was to compare the agreement between the Kramer algorithm, Naranjo criteria and Jones algorithm for the evaluation of ADRs in the ICU. A secondary objective was to compare the agreement between the same pharmacovigilance algorithms for ADR determination when applied in a retrospective versus concurrent fashion in the ICU.
There were two phases in this study. Phase I was the retrospective evaluation (i.e. after the patient was discharged from the hospital) conducted in patients admitted during July 2005 to June 2006. Phase II was the concurrent phase (i.e. while the patient was in the hospital) conducted over 6 weeks in 2008. Both phases were conducted at the University of Pittsburgh Medical Center and included adult patients admitted to the medical ICU.
In phase I, a random sample of 261 medication signals were evaluated individually for potential ADRs using the Kramer algorithm, Naranjo criteria and Jones algorithm. In phase II, an active medication monitoring system was used to detect five abnormal laboratory values, resulting in a random sample of 253 signals that were evaluated using the same three algorithms.
Percentage agreement among the algorithms for all levels of causality was estimated using a kappa statistic for both phases of the study.
For phase I, the kappa values were all >0.7 ranging from 0.721 to 0.855 between instruments, with Naranjo versus Kramer having the highest kappa, which is considered excellent agreement. The kappa statistic between individual instruments for phase II are <0.7 ranging from 0.423 to 0.635, which is considered moderate agreement, with Naranjo versus Jones displaying the lowest kappa while still exhibiting moderate agreement. For phase II, the Kramer algorithm had better agreement with both the Naranjo criteria and the Jones algorithm.
These instruments demonstrated similar results for evaluating ADRs in the ICU retrospectively, suggesting that instrument selection with any of the three instruments is reasonable. For concurrent ADR evaluations, there is greater variability in the level of causality obtained among pharmacovigilance algorithms and Kramer displayed better agreement with its comparators. A suggestion for a more definitive concurrent ADR assessment is to use more than one algorithm. This may be challenging in daily clinical practice; however, it is a reasonable expectation for research.
药物警戒算法用于评估不良反应（ADR）发生的可能性。在重症监护病房（ICU）中使用的首选工具尚未确定。
本研究的主要目的是比较 Kramer 算法、Naranjo 标准和 Jones 算法在 ICU 中评估 ADR 的一致性。次要目的是比较相同的药物警戒算法在 ICU 中回顾性和同时性应用时确定 ADR 的一致性。
本研究分为两个阶段。第一阶段是 2005 年 7 月至 2006 年 6 月期间入院患者的回顾性评估（即患者出院后）。第二阶段是 2008 年的 6 周同期阶段，在匹兹堡大学医学中心进行，包括入住内科 ICU 的成年患者。
在第一阶段，使用 Kramer 算法、Naranjo 标准和 Jones 算法对 261 种随机药物信号进行个体评估，以确定潜在的 ADR。在第二阶段，使用主动药物监测系统检测五个异常实验室值，产生 253 个随机信号，使用相同的三种算法进行评估。
使用kappa 统计量估计两个研究阶段所有因果关系水平的算法之间的一致性百分比。
对于第一阶段，kappa 值均>0.7，范围为 0.721 至 0.855，仪器之间的 Naranjo 与 Kramer 的 kappa 值最高，被认为是极好的一致性。第二阶段各仪器之间的 kappa 统计值<0.7，范围为 0.423 至 0.635，被认为是中度一致性，其中 Naranjo 与 Jones 的 kappa 值最低，但仍表现出中度一致性。对于第二阶段，Kramer 算法与 Naranjo 标准和 Jones 算法的一致性更好。
这些工具在回顾性评估 ICU 中的 ADR 时表现出相似的结果，表明使用这三种工具中的任何一种进行工具选择都是合理的。对于同时性 ADR 评估，药物警戒算法之间因果关系的水平存在更大的差异，Kramer 与比较者的一致性更好。对于更明确的同时性 ADR 评估的建议是使用不止一种算法。这在日常临床实践中可能具有挑战性；然而，这是对研究的合理期望。
