Abstract
Aims
Almost half of distal radius fractures (DRFs) lose threshold alignment (i.e. instability) after closed reduction and immobilization. This study aimed to investigate surgeons’ ability to estimate secondary displacement by addressing three questions: 1) What is the diagnostic accuracy of surgeons to estimate instability of DRFs on pre- and post-reduction radiographs?; 2) What is the diagnostic accuracy of surgeons to estimate instability of DRFs on post-reduction CT imaging?; and 3) What patient factors are associated with estimating instability?
Methods
We performed a scenario-based, randomized experiment with two distinct online surveys. In Part I, 116 members of the Science of Variation Group assessed radiographs of 20 initially displaced DRFs (11 ‘stable’, nine ‘unstable’), and estimated the loss of threshold alignment after closed reduction. Half viewed pre- and post-reduction radiographs, while half viewed only post-reduction radiographs. In Part II, 115 participants assessed 15 DRFs cases (six ‘stable’, nine ‘unstable’) to estimate loss of alignment. Half of the participants evaluated pre- and post-reduction radiographs, and half also received post-reduction CT imaging.
Results
In Part I, diagnostic accuracy for estimating loss of threshold alignment on pre- and post-reduction radiographs was 54% (95% CI 51% to 57%), similar to 55% (95% CI 46% to 62%) when only viewing post-reduction radiographs (p = 0.063). In Part II, the accuracy was 70% (95% CI 64% to 77%) with both radiographs and CT, compared with 67% (95% CI 61 to 67) with radiographs alone (p = 0.240). Patient factors associated with estimating instability were female sex and higher age.
Conclusion
Surgeons’ ability to detect DRF instability on both pre- and post-reduction radiographs, as well as post-reduction CT-scans, was limited, reflecting a restricted value of probability estimates for clinical decision-making. Given suboptimal estimations of alignment loss, it seems prudent to monitor adequately reduced fractures during initial immobilization. Future studies should focus on aids that can overcome this limited accuracy.
Cite this article: Bone Jt Open 2026;7(3):373–380.
Keywords: Distal radius fracture, Loss of threshold alignment, Instability, Radiographs, CT, Secondary displacement, distal radius fractures, radiographs, CT-scans, immobilization, closed reduction, Orthopaedic Surgeons, trauma, logistic regression analysis, deformities, splint
Introduction
Up to 50% of displaced distal radius fractures (DRFs) lose alignment beyond the established threshold after manual reduction and cast immobilization, according to guidelines.1-4 Surgeons may be accustomed to the terms ‘fracture instability’ and ‘fracture re-displacement’, rather than loss of threshold alignment. The terms ‘instability’ and ‘re-displacement’ imply a threshold of radiological deformity and the judgement that the alignment of the DRF has surpassed that threshold. Loss of threshold alignment includes deformities such as volar or dorsal angulation, loss of inclination, positive ulnar variance, or the occurrence of an intra-articular step-off or gap. The degree of visible deformity, impaired function, and levels of discomfort and incapability can vary substantially for a given malunion.5-7 However, the fact that radiological outcome of a distal radius fracture might have limited clinical consequences especially for the elderly patient, informed consent and shared decision-making on treatment should be based on reliable information which emphasizes the need for accurate prediction tools to estimate the risk of re-displacement in cast. Since the decision to operate or not is not only based on the presence of objective parameters (e.g. alignment) at the time of consultation, but often also on the expectation that re-displacement beyond critical thresholds might occur during the conservative management.
Previous studies have identified several factors associated with re-displacement, including age, sex, degree of dorsal or volar comminution, ulnar variance, and dorsal angulation.1,3,4,8,9 MacKenney et al8 and Lafontaine et al10 have also proposed methods for prospectively predicting the radiological outcome of a DRF using a formula or a set of five criteria, respectively. Regarding estimating loss of threshold alignment, one study noted poor diagnostic performance of the Edinburgh equation, whereas a separate study found good performance better than surgeon opinion alone.11,12
Additionally, the context of a radiological image might contain valuable information for a decision on future instability. Pre-reduction radiographs give insight into the degree of displacement and fragmentation. These factors may disappear in post-reduction radiographs. Additionally, CT imaging may depict fragmentation, displacement, and deformity in more detail than plain radiographs, thus increasing the accuracy and reliability of estimates on loss of threshold alignment.13-17 One study found that CT scans improve interobserver agreement on treatment recommendations for DRFs with a high therapeutic uncertainty, whereas interobserver agreement decreases in DRFs with a high therapeutic certainty.18 However, the ability of surgeons to accurately estimate loss of thresholds alignment has not yet been evaluated.
Study questions
In this study, we aimed to answer the following questions: 1) What is the diagnostic accuracy of surgeons to estimate loss of threshold alignment (i.e. instability) of DRFs on plain radiographs (pre- and post-reduction)?; 2) What is the diagnostic accuracy of surgeons to estimate loss of threshold alignment of DRFs on post-reduction CT imaging?; and 3) What patient factors are associated with estimating loss of threshold alignment?
Methods
Study design
We conducted an Institutional Review Board (IRB)-approved, cross-sectional scenario-based study at the Erasmus MC, Rotterdam, Netherlands, and University Medical Center Groningen, Netherlands, in which members of the Science of Variation Group (SOVG) were invited to participate in two separate parts of the study with two different online experiments. Participating surgeons forming the SOVG were blinded from the study design and hypothesis. To assess the diagnostic accuracy, participants assessed patients with initially displaced DRFs treated with closed reduction and cast immobilization and were asked to estimate loss of alignment beyond the thresholds presented in the American Academy of Orthopaedic Surgeons (AAOS) modified Dutch guidelines, where the Dutch guidelines have some stricter thresholds, based on recent evidence.19,20 In Part I, participating surgeons were randomized 1:1 to review either post-reduction radiographs alone or pre- and post-reduction radiographs. Several months later, in Part II, participating surgeons were randomized 1:1 to review either pre- and post-reduction radiographs alone or pre- and post-reduction radiographs with additional post-reduction CT imaging (coronal and sagittal view). Participation in Part I was not required nor obliged for participation in Part II.
Participants
The SOVG is a collaborative that studies variation in healthcare. The generalizability of SOVG scenario-based experiments is determined by variation in ratings sufficient to allow measurement of statistical associations. The relationships identified in a scenario-based experiment are likely reproducible in other samples with sufficient variation, while the absolute rates observed are probably not reproducible in other samples. SOVG members are orthopaedic, plastic, and general trauma surgeons who treat fractures in their daily practice. Most members practice in the USA or Europe. While everyone, from all over the world, is invited to join, and efforts to improve diversity have been made, most participating members are white males practising academics. Members receive group authorship or acknowledgement but no financial compensation for their contribution.
Patient selection and description of experiment
Suitable fractures were retrospectively and separately selected for both parts of the survey from two different level one trauma centres. Patients from Part I were treated at the University Medical Center Groningen, Netherlands, between January 2017 and June 2020, and patients from Part II were treated at the Erasmus Medical Center, Rotterdam, Netherlands, between January 2011 and June 2020. Inclusion criteria for both surveys were: 1) reduced DRF; 2) aged ≥ 18 years at the time of injury; and 3) fracture alignment after reduction within acceptable thresholds according to the most recent AAOS modified Dutch guidelines (Table I).19 For Part I, patients were included if pre- and post-reduction radiographs and additional radiographs for a minimum of six weeks after injury were available, to determine loss of threshold alignment or not. For Part II, patients were included when pre- and post-reduction radiographs with additional post-reduction CT-scan within seven days and radiographs for a minimum of six weeks after injury, to determine loss of threshold alignment, or having a radiograph deemed to have threshold malalignment before surgery were available. The CT-scan was shown as a video in axial and sagittal view, from articular surface to the sub-methaphyseal region. Patients were excluded based on the following criteria: 1) operative treatment before losing threshold alignment; 2) prior ipsilateral DRF; 3) missing posteroanterior (PA) or lateral pre- and post-reduction radiographs; and 4) radiological obliquity impeding judgement and measurements. Patients were included by LHMD and KDON, supervised by two orthopaedic surgeons and senior authors (MW, DR), who were not involved in the treatment either. Each researcher was responsible for one Part of the study. For all cases, fracture alignment was measured at trauma, post-reduction, and follow-up, by two researchers supervised by two orthopaedic surgeons, to define whether its alignment was within acceptable limits according to the AAOS modified Dutch guidelines (Table I).19,20 If not within threshold for any of the points in the guideline, at any of the available follow-up moments, this case was defined as ‘unstable’. A total of 20 fractures were selected for Part I, of which 11 did not lose threshold alignment during follow-up (‘stable’), and nine did lose threshold alignment (‘unstable’). For Part II, 15 fractures were selected, of which nine eventually lost threshold alignment and six did not. See Table II for demographic details of cases.
Table I.
Threshold for acceptable alignment according to the Dutch guidelines. A fracture has lost threshold alignment if one of the following measurements has been reached.
| Threshold |
| < 10° of dorsal angulation of the articular surface on a lateral radiograph |
| < 20° of volar angulation of the articular surface on a lateral radiograph |
| < 15° of ulnarward inclination of the articular surface on the PA view (often referred to as radial inclination) |
| < 3 mm of ulnar positive variance |
| < 2 mm intra-articular step-off |
| No significant translation and intact radiocarpal alignment on the lateral radiograph |
| No significant translation on the PA radiograph |
PA, posteroanterior.
Table II.
Demographic details of cases.
| Variable | Part I | Part II |
|---|---|---|
| No. | 20 | 15 |
| Female, n (%) | 14 (70) | 9 (60) |
| Mean age at trauma onset, yrs (SD) | 58 (17) | 53 (20) |
| Side of trauma, n (%) | ||
| Left | 11 (55) | 8 (53) |
| Right | 9 (4) | 7 (47) |
| Fall mechanism, n (%) | ||
| Fall on wrist | 15 (75) | 9 (60) |
| Fall from height | 4 (20) | 2 (13) |
| Fall from bycicle | 1 (5) | 4 (26) |
| Surgical stabilization for DRF, n (%) | ||
| Yes | 4 (20) | 5 (33) |
| No | 16 (80) | 10 (67) |
DRF, distal radius fracture.
Response variables
All surgeons who participated reviewed the AAOS modified Dutch guidelines for acceptable alignment at the start of the online experiment.19,20 For each of the fractures, the age at the time of trauma and sex (female or male) of the patient were presented. In Part II, the trauma mechanism was shown in the survey. Participants were asked, in their best estimate, if the fracture would lose alignment beyond the thresholds in the guidelines (i.e. deemed unstable) as a binary question (yes/no). No instructions were given on how to conclude on this prediction.
Explanatory variables
Explanatory participant variables were sex, continent where a surgeon practices, years of practice, whether a surgeon supervises surgical trainees, and sub-specialty. In Part I, 116 participants completed the questionnaire, with 92% (107/116) being male, 43% (50/116) residing in the USA, and 36% (42/116) residing in Europe (Table III). In Part II, 115 participants completed the questionnaire, with 90% (103/115) being male, 48% (55/115) residing in the USA, and 34% (41/115) residing in Europe (Table III).
Table III.
Part I and Part II: demographic details of participants.
| Variable | Part I | Part II |
|---|---|---|
| No. | 116 | 115 |
| Male, n (%) | 107 (92) | 103 (90) |
| Continent, n (%) | ||
| USA | 50 (43) | 55 (48) |
| Europe | 42 (36) | 41 (35) |
| Other | 24 (21) | 19 (17) |
| Years of practice, n (%) | ||
| 0 to 5 | 29 (25) | 26 (23) |
| 6 to 10 | 25 (22) | 22 (19) |
| 11 to 20 | 35 (30) | 38 (33) |
| 21 to 30 | 27 (23) | 29 (25) |
| Supervising | 95 (82) | 92 (80) |
| Subspecialty, n (%) | ||
| Fracture surgeons | 50 (43) | 43 (37) |
| Upper limb surgeons | 52 (44) | 56 (49) |
| Other | 14 (12) | 16 (15) |
| Randomization groups, n (%) | ||
| Group 1* | 60 (52) | 64 (56) |
| Group 2† | 56 (48) | 51 (44) |
In Part I, participants in this group were shown only post-reduction radiographs, and in Part II of pre-and post-reduction radiographs.
In Part I, participants in this group were shown pre- and post-reduction radiographs, and in Part II of pre-and post-reduction radiographs with CT imaging.
Statistical analysis
Accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were reported to describe participants' ability to predict loss of threshold alignment. An accuracy below 60% was considered poor, 60% to 70% moderate, 70% to 90% good, and above 90% excellent.21 The accuracy was calculated by comparing the online experiment outcomes (predicted instability yes/no) to the alignment on the follow-up radiographs (proven instability present/absent), measured according to the Dutch guidelines.19 A mixed multilevel logistic regression analysis was used to evaluate patient factors (sex, fall mechanism, and age) associated with dichotomous prediction of threshold loss of alignment accounting for nesting by surgeons. Statistical significance was set at p < 0.05.
Results
Part I: Accuracy in estimation of loss of threshold alignment on radiographs
Participants assessing pre- and post-reduction radiographs demonstrated an accuracy of 54% (95% CI 46 to 62). Sensitivity was 56% (95% CI 53 to 59), specificity was 31% (95% CI 28 to 34), with a PPV of 49% (95% CI 46% to 52%) and a NPV of 37% (95% CI 34% to 40%) (Table IV). When only post-reduction radiographs were evaluated, the diagnostic accuracy was 55% (95% CI 51% to 57%), with no significant differences compared with viewing both pre-and post-reduction radiographs (p = 0.062). Sensitivity was 44% (95% CI 42% to 47%), specificity was 45% (95% CI 42% to 48%), with an PPV of 50% (95% CI 47% to 52%) and a NPV of 40% (95% CI 37% to 43%) (Table IV). The logistic regression model confirmed that viewing both pre- and post-reduction radiographs was not associated with a more accurate estimation of loss of threshold alignment (odds ratio (OR) 0.81; 95% CI 0.65 to 1.0; p = 0.063).
Table IV.
Part I Performance metrics of estimating loss of threshold alignment on radiographs.
| Variable | Accuracy, % (95% CI)* | Sensitivity, % (95% CI) | Specificity, % (95% CI) | Positive predictive value, % (95% CI) | Negative predictive value, % (95% CI) |
|---|---|---|---|---|---|
| Pre- and post-reduction radiographs | 54 (46 to 62) | 56 (53 to 59) | 31 (28 to 34) | 49 (46 to 52) | 37 (34 to 40) |
| Post-reduction radiographs | 55 (51 to 57) | 44 (42 to 47) | 45 (42 to 48) | 50 (47 to 52) | 40 (37 to 43) |
Value displayed as a percentage with total amount of correct predictions/total amount of predictions.
Part II: Accuracy in estimation of loss of threshold alignment on additional CT
For this second question, participants demonstrated an accuracy of 70% (95% CI 64% to 77%) in estimating loss of threshold alignment in DRFs when pre- and post-reduction radiographs with additional CT is available. Sensitivity was 74% (95% CI 70% to 77%), specificity was 45% (95% CI 39% to 47%), with a PPV of 74% (95% CI 70% to 77%) and a NPV of 37% (95% CI 33% to 41%) (Table V). When participants only viewed pre- and post-reduction radiographs of these cases, the diagnostic accuracy was 64% (95% CI 61% to 67%), showing a higher specificity (51%; 95% CI 48% to 54%) with a higher NPV of 45% (95% CI 41% to 48%) (Table V). The logistic regression model confirmed that additionally viewing CT imaging was not associated with a more accurate estimation of loss of threshold alignment (OR 1.1; 95% CI 0.91 to 1.4; p = 0.240).
Table V.
Part II Performance metrics of estimating loss of threshold alignment on radiographs and CT.
| Variable | Accuracy, % (95% CI)* | Sensitivity, % (95% CI) | Specificity, % (95% CI) | Positive predictive value, % (95% CI) | Negative predictive value, % (95% CI) |
|---|---|---|---|---|---|
| Pre- and post-reduction radiograph and CT | 70 (64 to 77) | 68 (64 to 72) | 43 (39 to 47) | 74 (70 to 77) | 37 (33 to 41) |
| Pre- and post-reduction radiograph | 64 (61 to 67) | 65 (62 to 68) | 51 (48 to 54) | 71 (68 to 74) | 45 (41 to 48) |
Value displayed as a percentage with total amount of correct predictions/total amount of predictions.
Patient factors associated with estimating loss of threshold alignment
For Part I: patient factors associated with surgeons’ prediction of loss of threshold alignment were female patient sex (regression coefficient (RC) -1.0; 95% CI -1.3 to -0.65; p < 0.001), and older patient age (RC 0.077; 95% CI 0.67 to 0.86; p < 0.001) (Table VI).
Table VI.
Mixed multi-level logistic regression analysis of patient factors associated with prediction of loss of threshold alignment (yes/no).
| Variable | Part I | Part II | ||||||
|---|---|---|---|---|---|---|---|---|
| Regression coefficient (95% CI) | Standard error | p-value | Δ Akaike* | Regression coefficient (95% CI) | Standard error | p-value | Δ Akaike* | |
| Sex | 28 | 26 | ||||||
| Male | Reference | Reference | ||||||
| Female | -1.0 (-1.3 to -0.65) | 0.18 | < 0.001 | 0.75 (0.52 to 0.98) | 0.12 | < 0.001 | ||
| Fall mechanism | 28 | 27 | ||||||
| High-energy trauma | Reference | Reference | ||||||
| Low-energy trauma | 18 (-232 to 267) | 127.0 | 0.887 | -0.22 (-0.49 to 0.046) | 0.14 | 0.114 | ||
| Age | 0.077 (0.67 to 0.86) | 0.0048 | < 0.001 | 28 | 0.013 (0.0066 to 0.019) | 0.0033 | < 0.001 | 29 |
Δ Akaike indicates the model-fit, with lower scores indicating a better model fit.
For Part II, similar results were found; patient factors associated with surgeon prediction of loss of threshold alignment were female patient sex (RC 0.75; 95% CI 0.52 to 0,98; p < 0.001), and older patient age (RC 0.013; 95% CI 0.0066 to 0.019; p < 0.001) (Table VI).
Discussion
To guide DRF treatment effectively, it would be helpful to accurately estimate loss of alignment after reduction and immobilization. In answering the question if surgeons can accurately estimate this instability of DRFs, this study found that surgeons have limited accuracy in estimating loss of threshold alignment on both radiographs and CT imaging. Female sex and increased age were associated with estimating instability. From a clinical perspective, the inability to accurately assess the fracture can result in patients being immobilized in a cast for a longer period. In cases of secondary displacement of the radius fracture, surgery may still be required later. Patients whose fracture will not secondary displace might undergo an unnecessary surgery. This suggests that more insight and new techniques are needed to optimize the estimation of instability and, subsequently, early personalized treatment, including patient factors.
This study has limitations. First, this is a survey-based online randomized experiment, which may not fully represent actual patient care. Participating surgeons were provided with radiographs, as well as age, sex, and for only Part II trauma mechanism. Other clinical aspects or patient characteristics were not shown in the surveys, as previous research indicates that these factors do not necessarily correlate with treatment recommendations.22
Second, the included cases encompassed two different hospitals. However, both hospitals were comparable level one trauma centres with comparable populations. The requirement in Part II for CT imaging availability might have biased the selection towards cases already considered ‘unstable’, complicating the direct comparison between Part I and II. Nevertheless, this criterion aids in understanding a range of more complex or severe cases, potentially broadening the applicability of our findings to similar clinical situations.
Third, due to the retrospective design of this study, neither the specific type of immobilization (short-arm cast, circumferential cast, plaster splint, or sugar-tong splint) nor the quality of the casting could be assessed. According to the Dutch guidelines, only short-arm immobilization is recommended for DRFs, either as a circumferential cast or a plaster splint. Moreover, a previous study demonstrated that the choice between circumferential casting and a plaster splint did not result in a significantly different rate of fracture redisplacement.2
Lastly, the radiological parameters used in the Dutch guidelines, used in both parts of this study, are somewhat arbitrary. Using other parameters might result in different estimations. However, these guidelines are evidence-based, have recently been revised in 2021, and align with other standards like the AAOS guidelines.19
Can surgeons estimate loss of threshold alignment?
This study showed a poor accuracy in estimating loss of threshold alignment of DRF on pre- and post-reduction radiographs. There was no significant difference found in accuracy when participants assessed pre- and post-reduction radiographs compared with only assessing post-reduction radiographs. This highlights the fact that surgeons have limited accuracy in estimating the probability of loss of threshold alignment at all, independent of the radiological information provided.8,10,23 Furthermore, this finding might indicate that the degree of displacement pre-reduction is not associated with post-reduction loss of threshold alignment. However, research to date has shown that there is a correlation between pre-reduction fracture position and post-reduction loss of threshold alignment. The Edinburgh Wrist Probability Calculator (EWC) uses pre-reduction radiographs to estimate the probability of loss of threshold alignment. However, the poor diagnostic performance (area under the curve (AUC) of 0.47) and attempts to validate this tool suggest it may need more accuracy,3,8,12 which aligns with the current findings. In addition, one prior study reported a moderate accuracy of estimation of alignment loss on only radiographs.11 From this it should be concluded that despite knowledge on risk factors for fracture instability and high-quality radiological investigations, surgeons are to date not able to predict distal radius instability with adequate accuracy.
Furthermore, Part II of this study showed that the surgeons have moderate accuracy in estimating loss of thresholds alignment with or without the addition of post-reduction CT scans. The observation that assessing additional CT did not improve the moderate accuracy in estimation of loss of threshold alignment on only pre- and post-reduction radiographs might argue against its routine use. CT-scans are known for its ability to expose more detail on fragmentation and alignment of reduced DRFs; it did however not lead to more accurate predictions.24 One study found that CT-scan was associated with greater interobserver agreement on treatment planning of fractures with high therapeutic uncertainty.18 Meaning that when considering surgery, surgeons consider using a CT for surgical planning.
When comparing the diagnostic accuracies of the two parts of our study (55% vs 70%), this showed a slight improvement in the accuracy of estimation of loss of threshold alignment when a CT scan was available. However, the direct comparison of accuracy’s made between the two groups in Part II was not significant. This discrepancy may be attributed to the fact that Part II specifically included cases with a CT scan available. However, the including centres have a low threshold for making CT-scans in distal radius fracture care, this is not protocolized and the reason for CT can be surgical planning rather than evaluation of alignment, introducing an inclusion bias for unstable fractures. Therefore, contrasting the poor accuracy of pre-and/or post-reduction radiographs from Part I with those enhanced by additional CT imaging in Part II provides a more accurate reflection of daily clinical practice and enhances the generalizability of the findings.
The observation that older patient age and female patient sex were associated with estimation of loss of threshold alignment is consistent with prior evidence that female and age are related to potential for loss of alignment, perhaps through increased degree of osteoporosis.1,9,25
Current data show that the estimation of loss of threshold alignment by surgeons, despite knowledge on risk factors for instability, is insufficient for daily clinical practice. Future research should focus on techniques or models to further improve the reliability and accuracy of these estimations, taking these individual patient factors into account. Furthermore, using artificial intelligence (AI), particularly in the field of computer vision, might help to overcome these shortcomings.26,27 An improved estimation of the probability for loss of threshold alignment may facilitate shared decision-making, in which we can highlight the importance of patient values and preferences, perceived invasiveness, and complications rather than discussing uncertain probabilities of radiological outcome.
In conclusion, this survey-based randomized online experiment demonstrates limited accuracy in estimations of loss of threshold alignment of DRFs after closed reduction and cast immobilization in both pre- and post-reduction plain radiographs and with or without additional CT imaging, showing poor to moderate accuracy, respectively. This underscores the need for new techniques to predict fracture displacement in the acute setting and to counsel patients with reliable information for optimal treatment. Ongoing advances in AI may offer decision-support tools that improve morbidity outcomes and efficiency, benefiting both individual patients and society.
Take home message
- Fracture instability of the distal radius cannot be reliably assessed by surgeons using 2D imaging, such as radiographs or CT scans, alone.
Author contributions
L. H. M. Dankelman: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft
K. D. Oude Nijhuis: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft
M. M. Broekman: Data curation, Formal analysis, Methodology, Writing – review & editing
F. F. A. IJpma: Conceptualization, Supervision, Writing – review & editing
B. Barvelink: Writing – review & editing
R. L. Jaarsma: Conceptualization, Supervision, Writing – review & editing
J. W. Colaris: Conceptualization, Supervision, Writing – review & editing
M. H. Verhofstad: Conceptualization, Supervision, Writing – review & editing
J. N. Doornberg: Conceptualization, Methodology, Supervision, Writing – review & editing
D. Ring: Conceptualization, Methodology, Supervision, Writing – original draft, Writing – review & editing
M. Wijffels: Conceptualization, Methodology, Supervision, Visualization, Writing – review & editing
Funding statement
The author(s) received no financial or material support for the research, authorship, and/or publication of this article, other than the open access funding outlined below.
ICMJE COI statement
R. L. Jaarsma is a board member of the Executive Australian Orthopaedic Association. D. Ring reports royalties from Skeletal Dynamics and Wolters Kluwer, consulting fees from Patient+, Pre-litigation expert review, Medplace, Logica Ratio, Vertex, Best in Class MD, and Ashibo, payment or honoraria from universities, hospitals, and CME providers, payment for expert testimony from multiple lawyers, Logica Ratio, and QTC Leidos, stock or stock options with MyMedicalHub and Patient+, philanthropy to his institution from Tapestry Foundation and Buena Vista Foundation, and being deputy editor of Clinical Orthopedics and Related Research, and partial employment of Logica Ratio. All other authors have no conflicts of interest to disclose.
Data sharing
The datasets generated and analyzed in the current study are not publicly available due to data protection regulations. Access to data is limited to the researchers who have obtained permission for data processing. Further inquiries can be made to the corresponding author.
Ethical review statement
This study was performed under IRB approval of the Erasmus MC, Rotterdam, Netherlands (MEC-2020-0258) and Groningen University Medical Centre (202200114).
Open access funding
The open access fee was funded by the research department of surgery, Erasmus MC, University Medical Center Rotterdam, Netherlands.
© 2026 Dankelman et al. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND 4.0) licence, which permits the copying and redistribution of the work only, and provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc-nd/4.0/
Data Availability
The datasets generated and analyzed in the current study are not publicly available due to data protection regulations. Access to data is limited to the researchers who have obtained permission for data processing. Further inquiries can be made to the corresponding author.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and analyzed in the current study are not publicly available due to data protection regulations. Access to data is limited to the researchers who have obtained permission for data processing. Further inquiries can be made to the corresponding author.