Key result
A simple female-only model predicts PONV with ~0.64 AUC, matching more complex published scores.
Why the study?
The applicability and predictive accuracy of existing PONV risk scoring systems in a Taiwanese population undergoing general anaesthesia were uncertain.
Do predictive models accurately predict postoperative nausea and vomiting in a Taiwanese population undergoing general anaesthesia?
Cohort (n=992)
No
Do predictive models accurately predict postoperative nausea and vomiting in a Taiwanese population undergoing general anaesthesia?
Effect estimate: AUC 0.643
Female gender alone provides a simple predictive model for postoperative nausea and vomiting with moderate discrimination power (75% sensitivity, 54% specificity) in a Taiwanese population.
May simplify PONV risk assessment using gender alone; leaves open prospective validation beyond this cohort.
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 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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Wu et al. (2015) conducted a cohort in Postoperative nausea and vomiting (PONV) (n=992). Female gender-only predictive model vs. Published PONV risk scoring systems was evaluated on Incidence of nausea or vomiting in the first 24 hours after surgery (AUC 0.643). A simple female gender-only model predicted postoperative nausea and vomiting with an AUC of 0.643 (75% sensitivity, 54% specificity), performing similarly to more complex published scoring systems.
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