Predictive scoring systems for postoperative nausea and vomiting in ambulatory surgery have moderate accuracy, highlighting the importance of multimodal prophylactic strategies to reduce incidence.
Moderate predictive accuracy cautions against sole reliance on scoring systems; leaves open refinement of ambulatory PONV models while supporting multimodal prophylaxis.
Nausea and vomiting are distinctly unpleasant symptoms that may occur after surgery and anesthesia, and high priority is given to their prevention by patients. Research in this area is plentiful and has focused on event prediction and pharmacological prophylaxis but despite this, postoperative nausea and vomiting (PONV) typically occurs in 20%–30% of patients in contemporary practice. Prediction of postoperative and postdischarge nausea and vomiting is particularly important in the ambulatory surgical population as these symptoms may occur following discharge from hospital and continue for up to one week when access to antiemetic therapies is limited. Many of the existing predictive scoring systems are based on data from inpatient populations and limited to the first 24 hours after surgery. Scoring systems based on data from ambulatory surgical populations to predict PONV are only moderately good. The best-performing systems in ambulatory patients are those of Sinclair and Sarin with an area under the receiver operating characteristic curve of 0.78 and 0.74, respectively, but are limited by the short duration of follow-up and a greater emphasis on nausea than vomiting. Given that the ability to predict both PONV and postdischarge nausea and vomiting is clearly limited, emphasis has been placed on prophylactic strategies that incorporate antiemetic medication, intravenous hydration, and nonnarcotic analgesia. PONV has been reduced to <10% in institutions using multimodal approaches. Scoring systems may facilitate “risk tailoring” in which patient risk profile is used as a stratification method for pharmacointervention.
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McCaul et al. (2016) studied this question.
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