The effect of patient and prosthesis factors on revision rates after total knee replacement using a multi-registry meta-analytic approach

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background and purpose

Characteristics of patients receiving total knee arthroplasty (TKA) and prostheses used vary between regions and change with time. How these practice variations influence revision remains unclear. We combined registry data for better understanding of the impact of variation, which could potentially improve revision rates.

Patients and methods

We used data from 2003 to 2019 for primary TKA from arthroplasty registries of Sweden (SKAR), Australia (AOANJRR), and Kaiser Permanente (KPJRR). We included 1,072,924 TKA procedures for osteoarthritis. Factors studied included age, sex, ASA class, BMI category, prosthesis constraint, fixation, bearing mobility, patellar resurfacing, and polyethylene type. Cumulative percentage revision (CPR) was calculated using Kaplan–Meier estimates, and unadjusted Cox hazard ratios were used for comparisons. Random-effects generic inverse-variance meta-analytic methods were used to determine summary effects.

Results

We found similarities in age and sex, but between-registry differences occurred in the other 7 factors studied. Patients from Sweden had lower BMI and ASA scores compared with other registries. Use of cement fixation was similar in the SKAR and KPJRR, but there were marked differences in patellar resurfacing and posterior stabilized component use. Meta-analysis results regarding survivorship favored patients aged ≥ 65 years and minimally stabilized components. There were inconsistent results with time for sex, fixation, and bearing mobility, and no differences for the patellar resurfacing or polyethylene type comparisons.

Interpretation

Marked practice variation was found. Use of minimally stabilized and possibly also cemented and fixed bearing prostheses is supported.

Related collections

Most cited references 54

Record: found
Abstract: found
Article: not found

An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

Peter C Austin (2011)

The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing score: conditional on the propensity score, the distribution of observed baseline covariates will be similar between treated and untreated subjects. I describe 4 different propensity score methods: matching on the propensity score, stratification on the propensity score, inverse probability of treatment weighting using the propensity score, and covariate adjustment using the propensity score. I describe balance diagnostics for examining whether the propensity score model has been adequately specified. Furthermore, I discuss differences between regression-based methods and propensity score-based methods for the analysis of observational data. I describe different causal average treatment effects and their relationship with propensity score analyses.

0 comments Cited 1918 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Knee replacement

Andrew J Price, Abtin Alvand, Anders Troelsen … (2018)

Knee replacement surgery is one of the most commonly done and cost-effective musculoskeletal surgical procedures. The numbers of cases done continue to grow worldwide, with substantial variation in utilisation rates across regions and countries. The main indication for surgery remains painful knee osteoarthritis with reduced function and quality of life. The threshold for intervention is not well defined, and is influenced by many factors including patient and surgeon preference. Most patients have a very good clinical outcome after knee replacement, but multiple studies have reported that 20% or more of patients do not. So despite excellent long-term survivorship, more work is required to enhance this procedure and development is rightly focused on increasing the proportion of patients who have successful pain relief after surgery. Changing implant design has historically been a target for improving outcome, but there is greater recognition that improvements can be achieved by better implantation methods, avoiding complications, and improving perioperative care for patients, such as enhanced recovery programmes. New technologies are likely to advance future knee replacement care further, but their introduction must be regulated and monitored with greater rigour to ensure patient safety.

0 comments Cited 234 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

How long does a knee replacement last? A systematic review and meta-analysis of case series and national registry reports with more than 15 years of follow-up

Jonathan Evans, Robert Walker, Jonathan Evans … (2019)

Summary Background Knee replacements are the mainstay of treatment for end-stage osteoarthritis and are effective. Given time, all knee replacements will fail and knowing when this failure might happen is important. We aimed to establish how long a knee replacement lasts. Methods In this systematic review and meta-analysis, we searched MEDLINE and Embase for case series and cohort studies published from database inception until July 21, 2018. Articles reporting 15 year or greater survival of primary total knee replacement (TKR), unicondylar knee replacement (UKR), and patellofemoral replacements in patients with osteoarthritis were included. Articles that reviewed specifically complex primary surgeries or revisions were excluded. Survival and implant data were extracted, with all-cause survival of the knee replacement construct being the primary outcome. We also reviewed national joint replacement registry reports and extracted the data to be analysed separately. In the meta-analysis, we weighted each series and calculated a pooled survival estimate for each data source at 15 years, 20 years, and 25 years, using a fixed-effects model. This study is registered with PROSPERO, number CRD42018105188. Findings From 4363 references found by our initial search, we identified 33 case series in 30 eligible articles, which reported all-cause survival for 6490 TKRs (26 case series) and 742 UKRs (seven case series). No case series reporting on patellofemoral replacements met our inclusion criteria, and no case series reported 25 year survival for TKR. The estimated 25 year survival for UKR (based on one case series) was 72·0% (95% CI 58·0–95·0). Registries contributed 299 291 TKRs (47 series) and 7714 UKRs (five series). The pooled registry 25 year survival of TKRs (14 registries) was 82·3% (95% CI 81·3–83·2) and of UKRs (four registries) was 69·8% (67·6–72·1). Interpretation Our pooled registry data, which we believe to be more accurate than the case series data, shows that approximately 82% of TKRs last 25 years and 70% of UKRs last 25 years. These findings will be of use to patients and health-care providers; further information is required to predict exactly how long specific knee replacements will last. Funding The National Joint Registry for England, Wales, Northern Ireland, and Isle of Man and the Royal College of Surgeons of England.

0 comments Cited 138 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): Acta Orthop

Journal ID (iso-abbrev): Acta Orthop

Journal ID (publisher-id): ActaO

Title: Acta Orthopaedica

Publisher: Medical Journals Sweden, on behalf of the Nordic Orthopedic Federation

ISSN (Print): 1745-3674

ISSN (Electronic): 1745-3682

Publication date (Electronic): 01 February 2022

Publication date Collection: 2022

Volume: 93

Pages: 284-293

Affiliations

[1 ]Australian Orthopaedic Association National Joint Replacement Registry, South Australian Health and Medical Research Institute, Adelaide, SA Australia

[2 ]Swedish Knee Arthroplasty Register, Lund, Sweden

[3 ]Lund University, Faculty of Medicine, Clinical Science Lund, Department of Orthopedics, Lund, Sweden

[4 ]Surgical Outcomes and Analysis, Kaiser Permanente, San Diego, CA, USA

Author notes

Correspondence: plewis@ 123456aoanjrr.org.au

[†]

Otto Robertsson died October 2nd 2021. Dr Michael Dunbar, an old friend to Otto, wrote an obituary for the Knee Society, see postscript on page 293.

Article

Publisher ID: ActaO-93-1997

DOI: 10.2340/17453674.2022.1997

PMC ID: 8808477

PubMed ID: 35113168

SO-VID: 3ac21bed-14b9-416b-8571-d1bf31777a64

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( https://creativecommons.org/licenses/by-nc/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for non-commercial purposes, provided proper attribution to the original work.

The effect of patient and prosthesis factors on revision rates after total knee replacement using a multi-registry meta-analytic approach

Read this article at

Abstract

Background and purpose

Patients and methods

Results

Interpretation

Related collections

Orthopedics

Most cited references 54

An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies

Knee replacement

How long does a knee replacement last? A systematic review and meta-analysis of case series and national registry reports with more than 15 years of follow-up

Author and article information

Journal

Affiliations

Author notes

Article

History

Categories

Comments

Comment on this article

Similar content 146

Cited by 2

Most referenced authors 505