Can postoperative nausea and vomiting be predicted?

Citation
Dr. Sinclair et al., Can postoperative nausea and vomiting be predicted?, ANESTHESIOL, 91(1), 1999, pp. 109-118
Citations number
27
Categorie Soggetti
Aneshtesia & Intensive Care","Medical Research Diagnosis & Treatment
Journal title
ANESTHESIOLOGY
ISSN journal
00033022 → ACNP
Volume
91
Issue
1
Year of publication
1999
Pages
109 - 118
Database
ISI
SICI code
0003-3022(199907)91:1<109:CPNAVB>2.0.ZU;2-7
Abstract
Background: Retrospective(1) studies fail to identify predictors of postope rative nausea and vomiting (PONV). The authors prospectively studied 17,638 consecutive outpatients who had surgery to identify these predictors. Methods: Data on medical conditions, anesthesia, surgery, and PONV were col lected in the post-anesthesia care unit, in the ambulatory surgical unit, a nd in telephone interviews conducted 24 h after surgery. Multiple logistic regression with backward stepwise elimination was used to develop a predict ive model. An independent set of patients was used to validate the model. Results: Age (younger or older), sex. (female or male), smoking status (non smokers or smokers), previous PONV, type of anesthesia (general or other), duration of anesthesia (longer or shorter), and type of surgery (plastic, o rthopedic shoulder, or other) were independent predictors of PONV. A 10-yr increase in age decreased the Likelihood of PONV by 13%. The risk for men w as one third that for women. A 30-min increase in the duration of anesthesi a increased the Likelihood of PONV by 59%. General anesthesia increased the likelihood of PONV 11 times compared with other types of anesthesia. Patie nts with plastic and orthopedic shoulder surgery had a sixfold increase in the risk for PONV. The model predicted PONV accurately and yielded an area under the receiver operating characteristic curve of 0.785 +/- 0.011 using an independent validation set. Conclusions: A validated mathematical model is provided to calculate the ri sk of PONV in outpatients having surgery. Knowing the factors that predict PONV mill help anesthesiologists determine which patients will need antieme tic therapy.