Abstract
OBJECTIVE: To estimate whether a rapid recovery program would reduce length of stay among patients undergoing laparotomy on a gynecologic oncology service. METHODS: We conducted a prospective, randomized, controlled trial comparing an enhanced recovery after surgery protocol with routine postoperative care among women undergoing laparotomy on the gynecologic oncology service. Protocol elements included: preoperative counseling, regional anesthesia, intraoperative fluid restriction, and early postoperative ambulation and feeding. A sample size of 50 per group (N=100) was planned to achieve 80% power to detect a two-day difference in our primary outcome, length of hospital stay; secondary outcomes included: total daily narcotics used, time to postoperative milestones, and complications. RESULTS: A total of 112 women were enrolled between 2013 and 2015. Nine patients did not undergo laparotomy and were excluded, leaving 52 and 51 patients in the control and intervention groups, respectively. There was no difference in length of stay between the two groups (median 3.0 in both groups; P=.36). Enhanced recovery after surgery patients used less narcotics on day 0 (10.0 compared with 5.5 morphine equivalents in the control and intervention arms, respectively, P5.09) and day 2 (10.0 compared with 7.5 morphine equivalents, respectively; P=.05); however, there was no statistically significant difference between groups in any of the secondary outcomes. Post hoc analysis based on actual anesthesia received also failed to demonstrate a difference in time to discharge. CONCLUSION: When compared with usual care, introducing a formal enhanced recovery after surgery protocol did not significantly reduce length of stay.
Original language | English (US) |
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Pages (from-to) | 355-362 |
Number of pages | 8 |
Journal | Obstetrics and gynecology |
Volume | 129 |
Issue number | 2 |
DOIs | |
State | Published - 2017 |
Bibliographical note
Funding Information:Supported by the National Institutes of Health (NIH) T-32 training grant 5T32-CA132715 and NIH grant P30 CA77598 utilizing the Biostatistics and Bioinformatics Core shared resource of the Masonic Cancer Center, University of Minnesota, and by the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health