Appendix 1. OPCS-4 codes used in analysis
Arthroscopic procedure
Meniscal surgery – debridement or repair
W82.1-.3, .8-.9
Microfracturing
W83.1, W84.5
Removal of loose body
Replacement procedure
Partial knee replacement –
unicondylar or patello-femoral joint
replacement
W52.1, W53.1, W54.1
Total knee replacement
W40.1, W41.1, W42.1
W85.1, W86.1
Ligament reconstruction
W72.1-.6, .8-.9, W73.1-.4, .8-.9, W74.1-.3,
.8-.9, W75.1-.2, W84.1-.2
Unspecified therapeutic procedure –
including cartilage shaving and
debridement, elective irrigation
W83.3-.6, .8-.9, W84.3, .6, .8-.9, W85.2,
.8-.9, W86.8, W87.1, .8-.9, W88.8-.9
OPCS-4 – Office of Population, Censuses and Surveys Classification of Surgical Operations and
Procedures (4th revision)
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Appendix 2. Patient covariates used in the event analyses
Covariant
Description
Age
Continuous variable describing age of case at arthroscopy
Gender
Binary variable (male:female)
Hypertension
Binary variable
Chronic IHD
Binary variable
IDDM
Binary variable
Inflammatory arthritis
Binary variable
NIDDM
Binary variable
COPD
Binary variable
Charlson
An ordinal scaled variable describing comorbidities
Surgical centre
Frailty (or random effect)
RHB
Nominal variable
Socioeconomic class
Ordinal variable
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Appendix 3. Test of proportional hazards for effects of case age on risk of progression from
arthroscopy to knee replacement for cases aged ≥60 years. Beta represents the time dependent
coefficient for age. A lowess line shows the trend in Beta with time (days) since arthroscopy
(Note that confidence intervals on lowess line cross Beta=0.0 at approximately 400 days after
arthroscopy, at which point we can assume that the risk of knee replacement associated with
age at arthroscopy is no longer significant)
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Appendix 4. Regression diagnostics for best logistic regression model (GLM) relating type of
replacement total=1 and partial =0 to patient characteristics amongst patient receiving
intervention
Estimate
Standard error
Z value
Pr(>|z|)
-1.499106
0.350831
-4.273
1.93e-05
Age
0.052025
0.005946
8.750
< 2e-16
Charlson score >0
0.705279
0.217530
3.242
0.00119
(Intercept)
Null deviance: 1884.1 on 2169 degrees of freedom
Residual deviance: 1791.1 on 2167 degrees of freedom
AIC: 1797.1
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Appendix 5. Regression diagnostics for best logistic mixed effects model (GLMM) relating
type of replacement total=1 and partial =0 to patient characteristics amongst patient receiving
intervention, with centre where intervention was undertaken included as a random effect..
Estimate
Standard error
Z value
Pr(>|z|)
-1.48915
0.373094
-3.991
6.57e-05
Age
0.05385
0.006291
8.560
0.00e+00
Charlson score >0
0.72886
0.224039
3.253
1.14e-03
(Intercept)
Scale parameter in mixing distribution: 0.5392 gaussian
Std. Error: 0.1037
Likelihood ratio test p-value for centre random effect=0: sigma=0: p= 5.217e-05
Residual deviance: 1776 on 2166 degrees of freedom; AIC: 1784
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