Literature DB >> 35436805

Adductor Canal Block Does not Confer Better Immediate Postoperative Pain Relief after Total Knee Arthroplasty.

Akshay Padki1, Vishnu Vemula2, Glen Purnomo1,3, Jason Beng Teck Lim1, Lincoln Ming Han Liow1, Seng Jin Yeo1, Jerry Yongqiang Chen1.   

Abstract

The adductor canal block (ACB) is a useful adjunct to control postoperative pain in total knee arthroplasty (TKA). The aim of our study was to compare postoperative day 1 (POD1) pain scores, ambulation distance, range of motion, active straight leg raise (SLR), and length of stay (LOS) in TKA patients receiving no ACB (NACB), ACB by surgeon (ACBS), or ACB by anesthetist (ACBA). After obtaining institutional ethics approval, a retrospective review of 135 patients who underwent TKA between September 2020 and March 2021 was performed. All patients underwent TKA by the same surgeon and received the same standardized postoperative rehabilitation. Operating theater time was shortest in the NACB group with 129.3 ± 23.1 minutes compared with 152.4 ± 31.6 minutes in ACBA and 139.2 ± 29.4 minutes in ABCS (p = 0.001). For the POD1 pain score after therapy, the NACB group scored 4.9 ± 3.1 compared with 3.5 ± 2.2 and 3.9 ± 1.8 scored by the ACBA and ACBS groups, respectively (p = 0.302). The mean POD1 ambulation distance was 21.1 ± 15.2 m in the NACB group compared with 15.4 ± 1.3 and 17.8 ± 13.2 m in the ACBA and ACBS groups (all p > 0.05), respectively. There were no significant differences in the median LOS between three groups or ability to perform active SLR (all p > 0.05). Our study found no significant differences when comparing ACBS and ACBA by POD1 pain score, ambulation distance, range of motion, and LOS. We recommend against the use of ACB and instead recommend surgeons to perform an adequate periarticular cocktail injection. Thieme. All rights reserved.

Entities:  

Year:  2022        PMID: 35436805     DOI: 10.1055/s-0042-1743495

Source DB:  PubMed          Journal:  J Knee Surg        ISSN: 1538-8506            Impact factor:   2.757


  3 in total

1.  Can machine learning models predict failure of revision total hip arthroplasty?

Authors:  Christian Klemt; Wayne Brian Cohen-Levy; Matthew Gerald Robinson; Jillian C Burns; Kyle Alpaugh; Ingwon Yeo; Young-Min Kwon
Journal:  Arch Orthop Trauma Surg       Date:  2022-05-04       Impact factor: 3.067

2.  The utility of machine learning algorithms for the prediction of patient-reported outcome measures following primary hip and knee total joint arthroplasty.

Authors:  Christian Klemt; Akachimere Cosmas Uzosike; John G Esposito; Michael Joseph Harvey; Ingwon Yeo; Murad Subih; Young-Min Kwon
Journal:  Arch Orthop Trauma Surg       Date:  2022-06-29       Impact factor: 3.067

3.  Predicting surgical operative time in primary total knee arthroplasty utilizing machine learning models.

Authors:  Ingwon Yeo; Christian Klemt; Christopher M Melnic; Meghan H Pattavina; Bruna M Castro De Oliveira; Young-Min Kwon
Journal:  Arch Orthop Trauma Surg       Date:  2022-08-22       Impact factor: 2.928

  3 in total

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