We developed and validated a prediction rule for the occurrence of early postoperative severe pain in surgical inpatients, using predictors that can be easily documented in a preoperative setting. A cohort of surgical inpatients (n=1416) undergoing various procedures except cardiac surgery and intracranial neurosurgery in a University Hospital were studied. Preoperatively the following predictors were collected: age, gender, type of scheduled surgery, expected incision size, blood pressure, heart rate, Quetelet index, the presence and severity of preoperative pain, health-related quality of life the (SF-36), Spielberger's State-Trait Anxiety Inventory (STAI) and the Amsterdam Preoperative Anxiety and Information Scale (APAIS). The outcome was the presence of severe postoperative pain (defined as Numeric Rating Scale > or =8) within the first hour postoperatively. Multivariate logistic regression in combination with bootstrapping techniques (as a method for internal validation) was used to derive a stable prediction model. Independent predictors of severe postoperative pain were younger age, female gender, level of preoperative pain, incision size and type of surgery. The area under the receiver operator characteristic (ROC) curve was 0.71 (95% CI: 0.68-0.74). Adding APAIS scores (measures of preoperative anxiety and need for information), but not STAI, provided a slightly better model (ROC area 0.73). The reliability of this extended model was good (Hosmer and Lemeshow test p-value 0.78). We have demonstrated that severe postoperative pain early after awakening from general anesthesia can be predicted with a scoring rule, using a small set of variables that can be easily obtained from all patients at the preoperative visit. Before this internally validated preoperative prediction rule can be applied in clinical practice to support anticipatory pain management, external validation in other clinical settings is necessary.

Propofol TIVA results in a clinically relevant reduction of postoperative nausea and vomiting compared with isoflurane-nitrous oxide anesthesia (number needed to treat = 6). Both anesthetic techniques were otherwise similar. Anesthesia costs were more than three times greater for propofol TIVA, without economic gains from shorter stay in the postanesthesia care unit

SummaryWe quantified the accuracy of trained nurses to correctly assess the pre-operative health status of surgical patients as compared to anaesthetists. The study included 4540 adult surgical patients. Patients' health status was first assessed by the nurse and subsequently by the anaesthetist. Both needed to answer the question: 'is this patient ready for surgery without additional work-up, Yes ⁄ No?' (primary outcome). The secondary outcome was the time required to complete the assessment. Anaesthetists and nurses were blinded for each other's results. The anaesthetists' result was the reference standard. In 87% of the patients, the classifications by nurses and anaesthetists were similar. The sensitivity of the nurses' assessment was 83% (95% CI: 79-87%) and the specificity 87% (95% CI: 86-88%). In 1.3% (95% CI: 1.0-1.6%) of patients, nurses classified patients as 'ready' whereas anaesthetists did not. Nurses required 1.85 (95% CI: 1.80-1.90) times longer than anaesthetists. By allowing nurses to serve as a diagnostic filter to identify the subgroup of patients who may safely undergo surgery without further diagnostic workup or optimisation, anaesthetists can focus on patients who require additional attention before surgery.