Comparison of predictive models for postoperative nausea and vomiting
Comparison of predictive models for postoperative nausea and vomiting
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DOI：
10.1093/bja/88.2.234
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发表时间：
2002-02-01
影响因子：
9.8
通讯作者：
Roewer, N
中科院分区：
文献类型：
--
作者：
Apfel, CC;Kranke, P;Roewer, N
背景为了确定患者谁将受益于预防性amtiemetics，六个预测模型已被描述为术后恶心和呕吐（PONV）的风险评估。本研究比较了这些模型在全身麻醉患者中的有效性和实用性。数据分析了1566例患者谁经历了平衡麻醉，没有预防性止吐治疗的各种类型的手术。系统的文献检索确定了PONY的六种预测模型。这些模型进行了比较的有效性（鉴别能力和校准特性）和实用性。通过受试者工作特征曲线（AUC）下的面积测量辨别能力，并通过预测和实际PONV发生率之间的加权线性回归分析评估校准。根据模型所考虑的因素数量（因素越少越好）以及评分是否可以与先前应用的成本效益概念结合使用来评估实用性。PONV发生率为600/1566（38.1%）。使用推荐预防概念的风险类别，通过模型（根据第一作者命名）获得的区分能力（AUC）如下：Apfel，0.68; Koivuranta，0.66; Sinclair，0.66; Palazzo，0.63; Gan，0.61; Scholz，0.61。对于四种模型，绘制了以下校准曲线（表示为斜率和偏移）：Apfel，y=0.82x+0.01，r（2）=0.995; Koivuranta，y=1.13x-0.10，r（2）=0.999; Sinclair，y=0.49x+0.29，r（2）=0.789; Palazzo，y=0.30x+0.30，r（2）=0.763。要考虑的参数数量如下：Apfel，4; Koivuranta，5; Palazzo，5; Scholz，9; Sinclair，12; Gan，14。与更复杂的风险评分相比，简化的风险评分提供了更好的区分和校准特性。因此，简化的风险评分可以推荐用于临床实践中的止吐策略以及随机对照止吐试验中的组间比较。
Background. In order to identify patients who would benefit from prophylactic amtiemetics, six predictive models have been described for the risk assessment of postoperative nausea and vomiting (PONV). This study compared the validity and practicability of these models in patients undergoing general anaesthesia.Methods. Data were analysed from 1566 patients who underwent balanced anaesthesia without prophylactic antiemetic treatment for various types of surgery. A systematic literature search identified six predictive models for PONY. These models were compared with respect to validity (discriminating power and calibration characteristics) and practicability. Discriminating power was measured by the area under the receiver operating characteristic curve (AUC) and calibration was assessed by weighted linear regression analysis between predicted and actual incidences of PONV. Practicability was assessed according to the number of factors to be considered for the model (the fewer factors the better), and whether the score could be used in combination with a previously applied cost-effective concept.Results. The incidence of PONV was 600/1566 (38.1%). The discriminating power (AUC) obtained by the models (named according to the first author) using the risk classes from the recommended prophylactic concept were as follows: Apfel, 0.68; Koivuranta, 0.66; Sinclair, 0.66; Palazzo, 0.63; Gan, 0.61; Scholz, 0.61. For four models, the following calibration curves (expressed as the slope and the offset) were plotted: Apfel, y=0.82x+0.01, r(2)=0.995; Koivuranta, y=1.13x-0.10, r(2)=0.999; Sinclair, y=0.49x+0.29, r(2)=0.789; Palazzo, y=0.30x+0.30, r(2)=0.763. The numbers of parameters to be considered were as follows: Apfel, 4; Koivuranta, 5; Palazzo, 5; Scholz, 9; Sinclair, 12; Gan, 14.Conclusion. The simplified risk scores provided better discrimination and calibration properties compared with the more complex risk scores. Therefore, simplified risk scores can be recommended for antiemetic strategies in clinical practice as well as for group comparisons in randomized controlled antiemetic trials.