Applicability of risk scores for postoperative nausea and vomiting in a Taiwanese population undergoing general anaesthesia

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Abstract

Five popular scoring systems for postoperative nausea and vomiting (PONV) were validated and compared with two new predictive models in a Taiwanese population. Nine hundred and ninety-two patients receiving general anaesthesia in a tertiary hospital were investigated in a prospective observational cohort study. Patient demographic data and the incidence of nausea or vomiting in the first 24 hours after surgery were recorded. The overall incidence of PONV was 42%. The area under the curve (AUC) of the five published PONV risk scoring systems was 0.62 to 0.67. Logistic regression analysis in this study cohort showed that female sex and a history of PONV/car sickness were the only statistically significant independent risk factors for PONV (likelihood ratio test P <0.001). The AUCs of our two-predictor and gender-only models were 0.668 and 0.643, respectively (Nagelkerke R2=0.122 and 0.109). Goodness-of-fit showed that a two-predictor model predicted an outcome that was in agreement with the observed outcome (P=0.973). Both the two-predictor model and the Apfel score had a similar AUC that was significantly different from the AUCs of the other models. The AUC for the gender-only model in our population was similar to that of the simplified Koivuranta and the Palazzo and Evans scores (AUC=0.659 and 0.632; P=0.137 and 0.513 respectively). All AUCs had only moderate discrimination power but our female gender-only model was much simpler. Using female gender as the only predictor of PONV had predictive power with 75% sensitivity and 54% specificity.

Original languageEnglish
Pages (from-to)473-478
Number of pages6
JournalAnaesthesia and Intensive Care
Volume43
Issue number4
Publication statusPublished - 2015 Jul 1

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Postoperative Nausea and Vomiting
General Anesthesia
Area Under Curve
Population
Cohort Studies
Motion Sickness
Incidence
Tertiary Care Centers
Nausea
Vomiting
Observational Studies
Logistic Models
Regression Analysis
Demography
Sensitivity and Specificity

All Science Journal Classification (ASJC) codes

  • Critical Care and Intensive Care Medicine
  • Anesthesiology and Pain Medicine

Cite this

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title = "Applicability of risk scores for postoperative nausea and vomiting in a Taiwanese population undergoing general anaesthesia",
abstract = "Five popular scoring systems for postoperative nausea and vomiting (PONV) were validated and compared with two new predictive models in a Taiwanese population. Nine hundred and ninety-two patients receiving general anaesthesia in a tertiary hospital were investigated in a prospective observational cohort study. Patient demographic data and the incidence of nausea or vomiting in the first 24 hours after surgery were recorded. The overall incidence of PONV was 42{\%}. The area under the curve (AUC) of the five published PONV risk scoring systems was 0.62 to 0.67. Logistic regression analysis in this study cohort showed that female sex and a history of PONV/car sickness were the only statistically significant independent risk factors for PONV (likelihood ratio test P <0.001). The AUCs of our two-predictor and gender-only models were 0.668 and 0.643, respectively (Nagelkerke R2=0.122 and 0.109). Goodness-of-fit showed that a two-predictor model predicted an outcome that was in agreement with the observed outcome (P=0.973). Both the two-predictor model and the Apfel score had a similar AUC that was significantly different from the AUCs of the other models. The AUC for the gender-only model in our population was similar to that of the simplified Koivuranta and the Palazzo and Evans scores (AUC=0.659 and 0.632; P=0.137 and 0.513 respectively). All AUCs had only moderate discrimination power but our female gender-only model was much simpler. Using female gender as the only predictor of PONV had predictive power with 75{\%} sensitivity and 54{\%} specificity.",
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N2 - Five popular scoring systems for postoperative nausea and vomiting (PONV) were validated and compared with two new predictive models in a Taiwanese population. Nine hundred and ninety-two patients receiving general anaesthesia in a tertiary hospital were investigated in a prospective observational cohort study. Patient demographic data and the incidence of nausea or vomiting in the first 24 hours after surgery were recorded. The overall incidence of PONV was 42%. The area under the curve (AUC) of the five published PONV risk scoring systems was 0.62 to 0.67. Logistic regression analysis in this study cohort showed that female sex and a history of PONV/car sickness were the only statistically significant independent risk factors for PONV (likelihood ratio test P <0.001). The AUCs of our two-predictor and gender-only models were 0.668 and 0.643, respectively (Nagelkerke R2=0.122 and 0.109). Goodness-of-fit showed that a two-predictor model predicted an outcome that was in agreement with the observed outcome (P=0.973). Both the two-predictor model and the Apfel score had a similar AUC that was significantly different from the AUCs of the other models. The AUC for the gender-only model in our population was similar to that of the simplified Koivuranta and the Palazzo and Evans scores (AUC=0.659 and 0.632; P=0.137 and 0.513 respectively). All AUCs had only moderate discrimination power but our female gender-only model was much simpler. Using female gender as the only predictor of PONV had predictive power with 75% sensitivity and 54% specificity.

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