Evaluation of three risk scores to predict postoperative nausea and vomiting |
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Authors: | Eberhart L H Högel J Seeling W Staack A M Geldner G Georgieff M |
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Affiliation: | Department of Anaesthesiology, University of Ulm, Germany. leopold.eberhart@medizin.uni-ulm.de |
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Abstract: | BACKGROUND: So far there are three different scores to predict postoperative vomiting (PV: Apfel et al., 1998) or postoperative nausea and vomiting (PONV: Koivuranta et al., 1997; Palazzo and Evans, 1993). All three scores used logistic regression analysis to identify and create weights for the risk factors for PV or PONV. In short, these were sex, age, history of previous PONV, motion sickness, duration of anaesthesia, and use of postoperative opioids. However, an external evaluation and a comparison of these scores has not been performed so far. METHODS: Patients undergoing a variety of surgical procedures under general anaesthesia were studied prospectively. Preoperatively, they completed a questionnaire concerning potential risk factors for the occurrence of PV or PONV implemented in the three risk scores. Balanced anaesthesia (induction agent, nondepolarising neuromuscular blocker, opioid, and inhalation agent in nitrous oxide/oxygen) was performed. No intravenous anaesthesia or any antiemetic prophylaxis was applied. Postoperatively, the patients were observed in the recovery room for the occurrence of PV and PONV and were visited twice on the ward within the 24-h observation period. Both the patients and the nursing staff were asked whether PV or PONV was present. The severity of PONV was categorised using a standardised scoring algorithm. A total of 1,444 patients was finally included into the analysis. Using information of the predicted risk for the individual patients and the actual occurrence of PV or PONV, Receiver Operator Characteristics (ROC-curves) were drawn. The area under each ROC-curve was calculated as a means of the predictive properties of each score and was compared for statistical differences. RESULTS: For prediction of PONV (any severity) the AUC-values (AUC=area under the curve) and the corresponding 95%-confidence intervals were: Apfel: 0.70 (0.67-0.72); Koivuranta: 0.71 (0.69-0.73); Palazzo: 0.68 (0.65-0.70). For prediction of PV: Apfel: 0.73 (0.71-0.75); Koivuranta: 0.73 (0.70-0.75); Palazzo: 0.68 (0.65-0.70). Thus, all three scores appeared to have a moderate accuracy as measured by the AUC. The score of Koivuranta predicts PONV (P=0.007) and also PV (P=0.002) significantly better than Palazzo's score. Furthermore, for predicting of PV the score of Apfel was also superior to Palazzo's score (P=0.005). All three scores predict PV with the same accuracy as PONV. CONCLUSION: The occurrence of PV and PONV in patients undergoing surgery under balanced anaesthesia can be predicted with moderate but acceptable accuracy using one of the available risk scores, regardless of local surgical or anaesthesiological circumstances. For clinical practice, we recommend the score published by Koivuranta, since its calculation is very simple. |
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Keywords: | Risk score risk factors logistic regression analysis postoperative vomiting postoperative nausea and vomiting (PONV) receiver operator characteristics (ROC) |
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