Postoperative pain in ambulatory surgery

Postoperative pain is a common reason for the delayed discharge and unanticipated hospital admission of outpatients. In this study, we examined the pattern of pain in ambulatory surgical patients and determined those factors that predict postoperative pain. Ten thousand eight consecutive ambulatory surgical patients were prospectively studied. Preoperative patient characteristics, intraoperative variables, and pain in the postanesthesia care unit (PACU) and the ambulatory surgical unit (ASU) and 24 h postoperatively were documented. The incidence of severe pain was 5.3% in the PACU, 1.7% in the ASU, and 5.3% 24 h postoperatively. In the PACU, younger male adults (36 +/- 13 vs 47 +/- 22 yr), ASA physical status I patients, and patients with a higher body mass index (26 +/- 5 vs 25 +/- 5 kg) had a higher incidence of severe pain. in the group with severe pain, the duration of anesthesia, the duration of stay in the PACU and the ASU, and the time to discharge was longer than in the group without severe pain. In the PACU, orthopedic patients had the highest incidence of pain (16.1%), followed by urologic (13.4%), general surgery (11.5%), and plastic surgery (10.0%) patients. In patients who had general anesthesia, the intraoperative dose of fentanyl was significantly smaller in the group with severe pain than in the group without severe pain when body mass index and duration of anesthesia were taken into consideration. Body mass index, duration of anesthesia, and certain types of surgery were significant predictors of severe pain in the PACU. This knowledge will allow us to identify those patients at risk of severe postoperative pain and manage them prophylactically. Implications: The pattern of pain was examined in 10,008 consecutive ambulatory surgical patients. The incidence of severe pain was 5.3% in the postanesthesia care unit, 1.7% in the ambulatory surgical unit, and 5.3% 24 h postoperatively. Body mass, duration of anesthesia, and certain types of surgery were significant predictors of pain in the postanesthesia care unit. These data will allow us to better predict those patients who need intense prophylactic analgesic therapy.