Ibounig et al.
BMC Medical Research Methodology
(2022) 22:291
https://doi.org/10.1186/s12874-022-01776-6
Open Access
RESEARCH
Minimal important difference and patient
acceptable symptom state for common
outcome instruments in patients with a closed
humeral shaft fracture - analysis of the FISH
randomised clinical trial data
Thomas Ibounig1, Joona Juurakko2, Tuomas Lähdeoja1, Bakir O. Sumrein3, Teppo L. N. Järvinen1, Mika Paavola1,
Clare L. Ardern1,4, Teemu Karjalainen2, Simo Taimela1 and Lasse Rämö1*
Abstract
Background: Two common ways of assessing the clinical relevance of treatment outcomes are the minimal important difference (MID) and the patient acceptable symptom state (PASS). The former represents the smallest change in
the given outcome that makes people feel better, while the latter is the symptom level at which patients feel well.
Methods: We recruited 124 patients with a humeral shaft fracture to a randomised controlled trial comparing surgery to nonsurgical care. Outcome instruments included the Disabilities of Arm, Shoulder, and Hand (DASH) score, the
Constant-Murley score, and two numerical rating scales (NRS) for pain (at rest and on activities). A reduction in DASH
and pain scores, and increase in the Constant-Murley score represents improvement. We used four methods (receiver
operating characteristic [ROC] curve, the mean difference of change, the mean change, and predictive modelling
methods) to determine the MID, and two methods (the ROC and 75th percentile) for the PASS. As an anchor for the
analyses, we assessed patients’ satisfaction regarding the injured arm using a 7-item Likert-scale.
Results: The change in the anchor question was strongly correlated with the change in DASH, moderately correlated
with the change of the Constant-Murley score and pain on activities, and poorly correlated with the change in pain at
rest (Spearman’s rho 0.51, -0.40, 0.36, and 0.15, respectively).
Depending on the method, the MID estimates for DASH ranged from -6.7 to -11.2, pain on activities from -0.5 to -1.3,
and the Constant-Murley score from 6.3 to 13.5.
The ROC method provided reliable estimates for DASH (-6.7 points, Area Under Curve [AUC] 0.77), the Constant-Murley Score (7.6 points, AUC 0.71), and pain on activities (-0.5 points, AUC 0.68).
The PASS estimates were 14 and 10 for DASH, 2.5 and 2 for pain on activities, and 68 and 74 for the Constant-Murley
score with the ROC and 75th percentile methods, respectively.
*Correspondence:
[email protected]
1
Finnish Centre for Evidence-Based Orthopaedics (FICEBO), Department
of Orthopaedics and Traumatology, University of Helsinki and Helsinki
University Hospital, Topeliuksenkatu 5, PL266, 00029 HUS, Helsinki, Finland
Full list of author information is available at the end of the article
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Ibounig et al. BMC Medical Research Methodology
(2022) 22:291
Page 2 of 7
Conclusion: Our study provides credible estimates for the MID and PASS values of DASH, pain on activities and the
Constant-Murley score, but not for pain at rest. The suggested cut-offs can be used in future studies and for assessing
treatment success in patients with humeral shaft fracture.
Trial registration: ClinicalTrials.gov NCT01719887, first registration 01/11/2012.
Keywords: Clinimetrics, Minimal important difference, MID, MCID, Patient accepted symptom state, PASS,
Responsiveness, Outcome measures, DASH, Constant-Murley score, Pain, Humeral shaft fracture
Background
Medical interventions should be aimed at improving
patients’ health and well-being. Accordingly, patients’
symptoms and function lie at the heart of evaluating the effects of treatments. Due to their subjective
nature, symptoms and function need to be assessed
using patient-reported outcome measures (PROMs).
Two of the most common PROMs for evaluating treatment outcome in patients with humeral shaft fractures are the Disabilities of the Arm, Shoulder, and
Hand (DASH) score and Constant-Murley score [1–3].
Patients are also usually queried about the pain they
experience.
But what is the minimal benefit that justifies use of a
medical intervention? Over the past decades, we have
witnessed increasing calls to replace statistical significance with ‘clinical relevance’ – our treatments should
generate benefits that patients consider meaningful.
To inform the magnitude of such effects on different
outcome instruments, two important concepts have
been developed: the minimal important difference
(MID) [4] and the patient acceptable symptom state
(PASS) [5].
The MID is “the smallest difference in score in the
domain of interest which patients perceive as beneficial and which would mandate, in the absence of troublesome side effects and excessive cost, a change in the
patient’s management” [4]. PASS is the symptom level
above which patients consider themselves well, providing a tool for determining treatment success [5]. The
main difference between MID and PASS is that the
MID defines the smallest change in the given outcome
that makes people feel better, and PASS defines the
level at which the patient feels well.
To our knowledge, there are no previous studies
reporting PASS, and only one study reporting MID
estimates for two outcome measures (DASH and Constant-Murley score) in patients with humeral shaft
fractures [1]. Therefore, we report the MID and PASS
analyses of four outcome instruments commonly used
to assess treatment outcomes after humeral shaft fractures using data from the Finnish Shaft of the Humerus
(FISH) trial [3].
Methods
Design, setting, and participants
The FISH trial was a randomised clinical trial comparing
the effectiveness of surgical treatment with open reduction and plate fixation and non-surgical treatment with
functional bracing for closed humeral shaft fractures.
The execution of the FISH trial has been described in
detail previously [3, 6, 7]. The trial was carried out at the
Helsinki and Tampere University hospitals in Finland
between 2012 and 2018, and conducted in accordance
with the Declaration of Helsinki. Participants provided
written informed consent upon recruitment.
We included adult patients (18 years and older) with a
closed, unilateral, and displaced humeral shaft fracture.
Patients were excluded if they had a previous injury or
a condition affecting the function of the injured upper
limb, pathological fracture, other concomitant injury
affecting the same upper limb, other fracture, cognitive disabilities affecting the patient compliance, or polytrauma. Characteristics of participants 6 weeks after the
fracture are presented in Table 1.
For the MID and PASS analyses, we included data
from all 82 randomised participants and 42 participants
who declined to be randomised (opted to choose their
Table 1 Participant characteristics at 6 weeks post-injury
Characteristics
Values
Total number of participants (surgery/bracing)
124 (47/77)
Completed follow-up (%)
113 (91%)
Sex, n, Female (%)
54 (44%)
Age, years, mean (SD)
47 (17)
Fracture side, n, dominant (%)
60 (48%)
Smoker, n (%)
31 (25%)
DASH scorea, mean (SD)
46 (19)
Pain at restb, mean (SD)
1.8 (1.9)
Pain on activitiesb, mean (SD)
4.9 (2.6)
Constant-Murley scorec, mean (SD)
35 (20)
a
The Disabilities of the Arm, Shoulder, and Hand (DASH) score from 0 to 100
(0 = best)
b
Pain scores are 11-point Numerical Rating Scales with score from 0 to 10
(0 = best)
c
Constant-Murley score from 0 to 100 (100 = best)
Ibounig et al. BMC Medical Research Methodology
(2022) 22:291
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The four outcomes analysed were the DASH score, the
Constant-Murley score, and the numerical rating scale
(NRS) for pain of the upper extremity, both at rest and
on activities. DASH is a validated and responsive questionnaire of self-rated upper extremity disability and
symptoms with a score ranging from 0 to 100 (higher is
worse) [8]. The Constant-Murley score is a functional
assessment score of the shoulder consisting of patients’
estimate of pain and function in daily activities, and
measures of range of movement and upper extremity strength. The Constant-Murley score ranges from 0
to 100 (higher is better) [9]. The NRS for pain has been
widely used to evaluate clinical pain intensity [10]. Participants are asked to rate their average pain at rest and
on activities of daily living during the last 7 days on a
11-point NRS ranging from 0 to 10 (higher is worse).
As the anchor for determining both the MID and the
PASS, we used the following subjective global rating
question: “How satisfied are you with the overall condition of your injured upper limb and its effect on your
daily life?” (for methodological details, see below). The
answer options for this anchor question were from 1 to 7
in this order: “Very satisfied”, “Satisfied”, “Somewhat satisfied”, “Not satisfied nor dissatisfied”, “Somewhat dissatisfied”, “Dissatisfied”, and “Very dissatisfied”. All outcomes
were collected at 6 weeks, 3, 6, 12, and 24 months after
the injury.
(between better and not better in subjective global rating) were determined by ROC analysis using the closest
point to top left corner method to maximise specificity
and sensitivity [11]. Nonparametric bootstrapping with
1000 replications were used to calculate the 95% confidence interval for ROC MID values [12]. To measure
discrimination ability of the obtained cut-off, we calculated the area under the ROC curve (AUC) with 95%
CIs by DeLong’s method by bootstrapping 2000 samples [13].
For the mean difference of the change method, we
calculated the difference in outcomes between participants who had improved one point in the subjective
global rating from those who had not improved from
the previous follow-up.
For the mean change method, we calculated the mean
change with 95% confidence intervals (CIs) for the population whose response to the anchor question (subjective global rating) was one point higher than in the
previous follow-up point.
For the predictive modelling method, we used logistic regression analysis to calculate MIDs as described
by Terluin et al. [14] In this method, a logistic regression model is used to determine an MID value that
optimally predicts the probability of belonging to the
improved group. We dichotomised the anchor question as better and not better as described above with
the ROC method.
To assess the correlation of anchor and target outcome
measures, we calculated Spearman’s rho for the change of
the anchor and 1) the change in each of the outcomes,
2) prescores, and 3) postscores [15]. The 95% CIs were
defined by bootstrapping 1000 samples.
Data handling and analyses
Minimal important difference (MID)
Patient acceptable symptom state (PASS)
preferred treatment) but gave consent for prospective
follow-up using the same outcomes as for the FISH trial.
Accordingly, the study sample for the analyses consisted
of data from 124 participants.
Outcomes
MIDs for improvement by of each of the four outcome
measures were determined using four methods.
For the three anchor-based methods, we calculated
change in each outcome for each previous follow-up
point by deducting the earlier score from the later score,
thus a negative change in DASH and pain NRS represents improvement and conversely, a negative change in
the Constant-Murley score indicates worsening.
For the receiver operating characteristic (ROC)
method, we dichotomised the anchor question between
better than the previous follow-up point (e.g., from
‘somewhat dissatisfied’ to ‘not satisfied nor dissatisfied’) and not better than the previous follow-up point.
The change in the outcome score was calculated always
from the previous follow-up time point to the next follow-up point (i.e., change between each follow-up). The
optimal discrimination values for the outcome scores
For PASS estimates, we used the ROC method and the
75th percentile method. For the ROC method, we dichotomised the participants based on their responses to the
subjective global rating anchor question: those responding “Very satisfied” and “Satisfied” on a 7-item Likert
scale were deemed to have reached to a patient acceptable symptom state (PASS) while those responding anything between “Somewhat satisfied” to “Very dissatisfied”
were deemed not to have reached the PASS. Determination of the optimal cut off and 95% CIs was carried out in
the same way as for the MID.
For the 75th percentile method, we calculated the PASS
as the 25th percentile score for the Constant-Murley
score, and the 75th percentile score for the DASH score
and for the pain-NRS (at rest and on activities) in participants who responded either “Very satisfied” or “Satisfied”
on the subjective global rating question.
Ibounig et al. BMC Medical Research Methodology
(2022) 22:291
Primary and secondary analyses
For the primary analysis, we performed the MID and
PASS analyses by combining all the different time points
into one analysis to obtain a sufficient number of anchor–
outcome pairs. We also determined the MID values separately for every follow-up point as a secondary analysis
(Tables S1 and S2 of the supplementary appendix).
Results
In the FISH trial, 82 of 140 eligible patients were randomised to surgical (n = 38) or functional bracing
(n = 44) groups. Of 58 who declined randomisation, 42
consented to follow-up (declined cohort), providing
us with data from 124 participants (Table 1). Of the 42
patients in the declined cohort, nine participants chose
surgery and 33 chose functional bracing. Missing data
varied from 6 to 14 items at the different follow-up time
points [3].
Correlations
A change in the anchor question had good correlation
with a change in the DASH score (0.51; 95% CI, 0.44 to
0.59). The change in the Constant-Murley score (-0.40;
95% CI, -0.50 to -0.31) was moderately correlated to the
anchor. The correlation to pain NRS on activities (0.36;
95% CI, 0.26 to 0.47) was moderate, and poor for pain
Page 4 of 7
NRS at rest (0.15; 95% CI, 0.06 to 0.25). Correlations
between the postscore of the outcomes and the change
of the anchor ranged between -0.01 and 0.06. Correlation
between the prescore of the outcomes and the change in
the anchor was negative for the DASH score, pain NRS at
rest, and pain NRS on activities. The correlation was positive for the Constant-Murley score (Table 2). The correlations at each time point are given in the supplementary
appendix Tables S3, S4 and S5.
MID estimates
Depending on the method used, the MID estimates
ranged from -6.7 to -11.2 for DASH, from 6.3 to 13.5
for the Constant-Murley score, and from -0.5 to -1.3 for
pain-NRS on activities (Tables 3–4). Estimating MID
for the pain-NRS at rest would not have been appropriate because the correlation with the anchor was too low.
The MID estimates from the ROC method for DASH and
the Constant-Murley score proved acceptable discrimination, while the corresponding estimates for pain-NRS
on activities discriminated poorly (Table 3). The total
number of anchor – outcome data pairs are shown in
Table 3, and at each follow-up time point in supplementary appendix Table S4. The distribution of responses to
the anchor question at different time points are shown in
Fig. S1 of the supplementary appendix. The ROC curves
Table 2 Correlations between the change in the anchor question and outcomes
Correlation between
DASH
Pain at rest
Pain on activities
Constant-Murley score
Postscore
0.04
(-0.05 to 0.14)
0.04
(-0.06 to 0.14)
0.06
(-0.04 to 0.15)
-0.01
(-0.10 to 0.09)
Change of the outcome
0.51
(0.44 to 0.59)
0.15
(0.06 to 0.25)
0.36
(0.26 to 0.47)
-0.40
(-0.50 to -0.31)
Prescore
-0.27
(-0.36 to -0.18)
-0.09
(-0.19 to 0.01)
-0.23
(-0.32 to -0.14)
0.20
(0.11 to 0.30)
Values are Spearman’s rho with 95% CIs
DASH Disabilities of the Arm, Shoulder, and Hand score
Table 3 MIDa estimates from the ROCb analyses
Outcome
MID (95% CI)
Sensitivity
Specificity
AUCf (95% CI)
Ng
DASHc
-6.7 (-7.9 to -5.4)
0.71
0.74
0.77 (0.73 to 0.82)
420 (172/248)
Pain on activitiesd
-0.5 (-0.5 to -0.5)
0.62
0.69
0.68 (0.63 to 0.73)
427 (178/249)
Constant-Murley scoree
7.6 (7.4 to 13.2)
0.61
0.71
0.71 (0.66 to 0.76)
416 (172/244)
a
Minimal important difference
b
Receiving operating characteristics, graphs shown in Fig. S2 of the supplementary appendix
c
The Disabilities of the Arm, Shoulder, and Hand (DASH) score from 0 to 100 (0 = optimal outcome)
d
Pain score is 11-point Numerical Rating Scales with score from 0 to 10 (0 = optimal outcome)
e
Constant-Murley score from 0 to 100 (100 = optimal outcome)
f
Area under the curve
g
N = count of anchor–outcome pairs used in the analysis (improved / not improved between consecutive time points)
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Table 4 MIDa values calculated by mean difference of change, mean change, and predictive methods
Method
Mean difference of change
Mean change
Predictiveg
Outcome
MID (95% CI)
MID (95% CI)
MID (95% CI)
N1e
N2f
DASH
b
-6.8 (-9.2 to -4.3)
-11.2 (-13.3 to -9.1)
-9.4 (-10.5 to -8.3)
105
248
Pain activec
-0.9 (-1.4 to -0.5)
-1.3 (-1.6 to -0.9)
-1.0 (-1.2 to -0.8)
108
249
Constant-Murley scored
6.3 (3.2 to 9.4)
13.5 (10.9 to 16.2)
12.1 (10.8 to 13.4)
104
244
a
MID Minimal important difference. Values are MIDs with 95% CIs
b
The Disabilities of the Arm, Shoulder, and Hand (DASH) score from 0 to 100 (0 = optimal outcome)
c
Pain score is 11-point Numerical Rating Scales with score from 0 to 10 (0 = optimal outcome)
d
Constant-Murley score from 0 to 100 (100 = optimal outcome)
e
N1 = number of patients whose condition was one point better than at the previous follow-up using the 7-point Likert-scale
f
N2 = number of patients whose condition was not better (same or worse) than at the previous follow-up using the 7-point Likert-scale
g
Number of anchor–outcome pairs used in the predictive method are the same than with the ROC method in Table 3
and the MID estimates at all follow-up time points are
shown in Fig. S2 and Tables S4 and S5 of the supplementary appendix.
PASS estimates
PASS values showed excellent discrimination in the
DASH and Constant-Murley scores in the ROC analysis.
PASS values discriminated well for pain NRS on activities. It was not appropriate to define PASS value for the
pain-NRS at rest due to poor correlation with the anchor.
PASS values defined by the 75th percentile method were
closer to the best possible score of the outcomes than the
estimates obtained from the ROC method (Table 5).
Discussion
We calculated the MID and PASS estimates for three outcomes in adult patients with closed humeral shaft fractures. We used four methods to calculate the MID and
two methods to calculate PASS.
Our MID estimates varied depending on the method
used. The change in DASH score had a good correlation, and the change of Constant-Murley score and pain
on activities had moderate correlations with the change
in anchor question. Pain at rest did not correlate with
the anchor question and therefore we were not able to
estimate MID or PASS for pain at rest. Taken together,
these results indicated credible MID estimates. The ROC
method for cut-off values of the MID of both DASH (-6.7
points) and Constant-Murley (7.6 points) scores had an
acceptable discrimination. Pain on activities (-0.5 points)
discriminated poorly with the ROC method.
The PASS values with the ROC method for DASH (14
points) and Constant-Murley score (68 points) had excellent discrimination. The discrimination was good with
the pain on activities (2.5 points). The 75th percentile
method yielded more stringent limits for PASS in all the
outcomes (DASH, 10 points; the Constant-Murley score,
74 points; pain on activities, 2 points).
We suggest that differences smaller than the smallest
point estimates of the MIDs from this study are unlikely
to be clinically meaningful. Conversely, differences above
the upper limits are very likely to be clinically important to patients. Depending on the potential benefits
and inherent risks of treatment methods, researchers
may choose either the lower or upper limit of the suggested MID when interpreting the clinical relevance of
Table 5 PASS estimates from 75th percentile method and ROC analysis
Outcome
75th percentile
method
ROC method
PASS
PASS
Sensitivity
Specificity
AUC (95% CI)
DASHa
10
14
0.87
0.87
0.94 (0.92 to 0.95)
Pain on activitiesb
2.0
2.5
0.87
0.78
0.89 (0.86 to 0.91)
74
68
0.85
0.83
0.90 (0.88 to 0.93)
Constant-Murley score
a
c
Disabilities of the Arm, Shoulder, and Hand (DASH) score from 0 to 100 (0 = optimal outcome)
b
Pain score is 11-point Numerical Rating Scales with score from 0 to 10 (0 = optimal outcome)
c
Constant-Murley score from 0 to 100 (100 = optimal outcome)
PASS Patient acceptable symptom state
ROC Receiver operating characteristic
Ibounig et al. BMC Medical Research Methodology
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treatment effects. For PASS, the upper point estimate
depicts the cut-off above which the patients are very
likely to be satisfied with the treatment outcome and conversely, the lower point estimate reflects the level below
which the patients are unlikely to be satisfied.
We identified one previous prospective comparative
study on the MID of two different outcomes in patients
with humeral shaft fractures reporting the MID of 6.7
points for DASH and 6.1 points for the Constant-Murley
score [1]. We could not identify a previous study reporting PASS estimates for patients with humeral shaft fractures. Our estimate for the MID for pain on activities is
smaller than in degenerative shoulder conditions [16, 17].
However, due to moderate correlation in pain on activities, our result should be interpreted with caution.
We decided to use a prospective anchor question for
our analyses (i.e., patients reported their current symptom state using the subjective global rating as opposed
to comparing it to baseline status), which is the method
used often in the MID analyses for degenerative conditions. In a trauma setting, it is not possible to obtain reliable baseline data prior the injury. Our approach may be
less susceptible to recall bias as the participants did not
have to remember their symptoms state several months
ago—a task that people tend to fail in [18, 19].
A strength of our study is high internal validity as we
used prospective homogenous data from a randomised
clinical trial performed by experienced research personnel with little missing data. We also used the most
common outcome instruments to assess the outcome of
treatment in patients with upper extremity injuries and
the methods for obtaining several MID and PASS estimates. In addition, our determination to analyse the MID
and PASS was published in the protocol article, prior to
any access to trial data [7].
tool for future trial sample size calculations. However,
when contemplating different treatment methods during shared decision-making in clinical settings, the concept of PASS may be more understandable for patients
[21]. The clinician might consider informing the patient
about the probable proportion of patients reaching
PASS (i.e., feeling well, with an experience of successful
treatment) with different treatment options.
Limitations
Acknowledgements
We thank all the patients who participated in the FISH trial as well as the
physical therapists and all other collaborators at the hospital sites and in the
community who were involved in conducting the trial.
An obvious limitation of our study is that the results are
obtained from a randomised clinical trial with stringent
inclusion and exclusion criteria (i.e., adult patients with
closed, unilateral humeral shaft fracture without severe
comorbidities or compliance problems). Thus, our results
may not be directly applicable to all patients with this
injury. Second, the ROC analyses can be biased if the
proportion of improved participants is markedly different from 50% [20]. However, in our study there were
about 420 follow-up intervals and in approximately 250
intervals the patients did not experience improvement,
making a marked bias in the estimates unlikely.
Future directions
Both the MID and PASS are valuable tools both in medical research and clinical practice. The MID provides a
Conclusions
We provide credible estimates for the MID and PASS
for adult patients with humeral shaft fractures including several of the most used methods and outcomes.
Depending on the application, the upper or lower
limit of the established MIDs and PASS values should
be chosen. The MID might be more useful especially
for scientific purposes (i.e., sample size calculation),
whereas the PASS concept is—in addition to scientific
applications—more understandable to patients, and
accordingly, we advocate its use as a more appropriate
measure for gauging treatment success in patients with
a humeral shaft fracture.
Abbreviations
AUC: Area under curve; CI: Confidence interval; DASH: the Disabilities of
arm, Shoulder, and Hand score; FISH: Finnish Shaft of the Humerus trial; MID:
Minimal important difference; NRS: Numerical rating scale; PASS: Patient
acceptable symptom state; PROM: Patient-reported outcome measure; ROC:
Receiver operating characteristic.
Supplementary Information
The online version contains supplementary material available at https://doi.
org/10.1186/s12874-022-01776-6.
Additional file 1.
Authors’ contributions
TI, TL, TJ, MP, CA, TK, ST, and LR conceived and designed the study, TI, TL, BS,
MP, and LR collected the data, JJ and TK executed data analyses, TI, JJ, TL, TJ,
CA, TK, ST, and LR drafted and revised the article. All authors contributed to
final data interpretation and contributed to and approved the final draft of the
manuscript.
Funding
This study was supported by the state funding for university-level health
research in Finland. The funder had no role in the design and conduct of
the study; collection, management, analysis, and interpretation of the data;
preparation, review, or approval of the manuscript; and decision to submit the
manuscript for publication.
Availability of data and materials
FISH trial data are not publicly available owing to data privacy issues, but
access to the anonymised dataset can be obtained from the corresponding
author on reasonable request.
Ibounig et al. BMC Medical Research Methodology
(2022) 22:291
Declarations
Ethics approval and consent to participate
The study protocol was approved by the Institutional Review Board of the
Helsinki and Uusimaa Hospital District (118/13/03/02/2012; May 14, 2012) and
informed consent was obtained from all participants prior to inclusion in the
study. The trial was conducted in accordance with the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1
Finnish Centre for Evidence-Based Orthopaedics (FICEBO), Department of
Orthopaedics and Traumatology, University of Helsinki and Helsinki University
Hospital, Topeliuksenkatu 5, PL266, 00029 HUS, Helsinki, Finland. 2Finnish Centre
for Evidence-Based Orthopaedics (FICEBO), Department of Hand Surgery,
Central Finland Central Hospital, Keskussairaalantie 19, 40620 Jyväskylä, Finland.
3
Department of Orthopaedics and Traumatology, University of Tampere
and Tampere University Hospital, Elämänaukio 2, 33520 Tampere, Finland.
4
Department of Family Practice, University of British Columbia, 5950 University
Boulevard, Vancouver V6T 1Z3, Canada.
Received: 26 March 2022 Accepted: 26 October 2022
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