the influences of anesthesia methods on some complications after orthopedic surgery: a bayesian network meta-analysis

the influences of anesthesia methods on some complications after orthopedic surgery: a bayesian network meta-analysis

;Yuqing Zeng;Junming Wan;Haiyong Ren;Jianwei Lu;Fuhua Zhong;Shu Deng
american journal of emergency medicine 2019 Vol. 19 pp. 1-11
307
zeng2019bmcthe

Abstract

Abstract Background Although several anesthesia procedures have been explored for orthopedic surgery, the complications of anesthesia remain not well resolved. This study aimed to explore the influence of different anesthesia methods on the complications after orthopedic surgery. Methods According to the searching strategy, anesthesia associated studies in orthopedic surgery were screened from Pubmed, Embase, and the Cochrane Library up to Mar. 10th, 2018. Then, complications and demographic data were extracted and quality of studies was assessed using Cochrane Collaboration recommendations. ADDIS software was used to perform the network meta-analysis. Pooled effect size was calculated using random effective model or consistency model, and presented with odds ratio (OR) and 95% confidence interval (CI). Results According to the selective criteria, a total of 23 studies with 2393 patients were enrolled in this study. Quality assessment revealed all studies had an ordinary quality. Network meta-analyses revealed that nerve block analgesia (NBA) presented a lower effect on the occurrence of post-operative nausea or vomiting (PONV; OR = 0.17, 95% CI: 0.06–0.39) and urine retention (OR = 0.07, 95% CI: 0.01–0.37) compared with epidural anesthesia (EA). Interscalene block (ISB) and local infiltration analgesia (LIA) could significantly reduce the occurrence of back pain compared with EA (OR = 0.00, 95% CI = 0.00–0.30; OR = 0.00, 95% CI = 0.00–0.25). Conclusion NBA presented an effective role in reliving the occurrence of PONV and urine retention, and ISB and LIA relieved the back pain compared with EA after orthopedic surgery.

Citation

ID: 146463
Ref Key: zeng2019bmcthe
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
146463
Unique Identifier:
10.1186/s12871-019-0701-2
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet