To unlock this feature and to subscribe to our weekly evidence emails, please create a FREE orthoEvidence account.

SIGNUP

Already Have an Account?

Loading...
Visit our Evidence-Based Covid-19 Website and Stay Up to Date with the latest Research.
Ace Report Cover

AAOS2017: Assessing liposomal bupivacaine in TKR

Download
Share
Reprints
Cite This
About
+ Favorites
Share
Reprints
Cite This
About
+ Favorites
Ace Report Cover
March 2017

AAOS2017: Assessing liposomal bupivacaine in TKR

Vol: 6| Issue: 3| Number:50| ISSN#: 2564-2537
Study Type:Randomized Trial
OE Level Evidence:N/A
Journal Level of Evidence:N/A

Liposomal Bupivicaine Utilization in Total Knee Replacement Does Not Decrease Length of Hospital Stay: A Preliminary Report

Contributing Authors:
G Blaylock J Mann J Sloboda C Cdebaca M Wolfe G Wood M Stover

Did you know you're eligible to earn 0.5 CME credits for reading this report? Click Here

CONFERENCE ACE REPORTS

This ACE Report is a summary of a conference presentation or abstract. The information provided has limited the ability to provide an accurate assessment of the risk of bias or the overall quality. Please interpret the results with caution as trials may be in progress and select results may have been presented.

Synopsis

100 patients scheduled for total knee arthroplasty under spinal anesthesia were randomized to one of three groups: 1) liposomal bupivacaine for wound infiltration at the end of the procedure, 2) standard bupivacaine for wound infiltration at the end of the procedure and with the addition of a spinal narcotic, or 3) standard bupivacaine for wound infiltration at the end of the procedure without the...

CME Image

Did you know that you’re eligible to earn 0.5 CME credits for reading this report!

LEARN MORE

Join the Conversation

Please Login or Join to leave comments.

Learn about our AI Driven
High Impact Search Feature

High Impact Icon

Our AI driven High Impact metric calculates the impact an article will have by considering both the publishing journal and the content of the article itself. Built using the latest advances in natural language processing, OE High Impact predicts an article’s future number of citations better than impact factor alone.

Continue