title: Predictive models for post-operative nausea and vomiting in patients using patient-controlled analgesia.
abstract: This study identified predictive factors for post-operative nausea and vomiting (PONV) in patients using patient-controlled analgesia (PCA) and developed five predictive model pathways to calculate the probability of PONV using decision tree analysis. The sample consisted of 1181 patients using PCA. Data were collected using: a specifically designed check-off form to collect patient-, surgery-, anaesthesia- and post-operation-related data; the Beck Anxiety Inventory to measure pre-operative anxiety; and a visual analogue scale, to measure post-operative pain. The incidence of PONV was 27.7%. Nine factors were highly predictive of PONV in our five model pathways: gender, obesity, anxiety, history of previous PONV, history of motion sickness, inhalation of nitrous oxide during operation, use of inhalational agents, starting oral fluid/food intake after operation, and post-operative pain. With these five predictive model pathways, we can predict the probability of PONV in an individual patient according to their individual characteristics.
authors: Postanaesthetic Care Unit, Asan Medical Centre, Songpa-Gu, Seoul, Korea.
authors: Y Y
authors: YY
authors: Lee
authors: K H
authors: KH
authors: Kim
authors: Y H
authors: YH
authors: Yom
mesh_terms: D000293:Adolescent; D016058:Analgesia, Patient-Controlled; D002648:Child; D002675:Child, Preschool; D003663:Decision Trees; D005260:Female; D006801:Humans; D007723:Korea / Q000453:epidemiology; D008297:Male; D015233:Models, Statistical; D020250:Postoperative Nausea and Vomiting / Q000453:epidemiology* / Q000517:prevention & control; D015995:Prevalence; D018570:Risk Assessment / Q000379:methods*