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Record W4415439070 · doi:10.1302/1358-992x.2025.10.110

ASSESSMENT OF RADIOLOGICAL HEALING RELIABILITY AND ACCURACY IN DISTAL RADIUS FRACTURES

2025· article· en· W4415439070 on OpenAlexaff
Phillip Spanswick, D. You, Man‐Chung Wong, Robert Korley, Ryan Martin, Ifaz T. Haider, Prism Schneider

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsAlberta Bible College
Fundersnot available
KeywordsRadiographyRadiological weaponReliability (semiconductor)Intraclass correlationWristBone healingCohortProspective cohort study

Abstract

fetched live from OpenAlex

Distal radius fractures (DRFs) are commonly managed non-operatively through closed reduction and cast immobilization; however, complications may arise if the immobilization period is too long or short. There are no standardized guidelines to determine the optimal duration of immobilization, so radiographic assessment of healing progression is common. However, there is no consensus on criteria to assess union. Scoring cortical continuity has been used with some success in lower limb fractures,1 but it remains unclear if a similar technique can reliably determine union after DRFs. In this study, we hypothesized that radiographic assessment based on cortical continuity and fracture line visibility of non-operatively treated DRFs would provide a reliable measure of fracture healing. We assessed inter- and intra-rater reliability of radiographic scoring, with and without access to patient demographics and injury characteristics. We also determined the association of radiographic scoring against Patient-Rated Wrist Evaluation (PRWE) and predictions of bone stiffness. Consecutive adults who underwent non-operative treatment for a DRF were enrolled in this prospective cohort study. Orthogonal radiographs were taken at initial assessment and 2-weeks, 4–6 weeks, and 26-weeks post-fracture. Six independent raters (two attending surgeons, two orthopaedic trauma fellows, and two senior residents) determined radiographic cortex score (RCS) based on callus and fracture line visibility. Raters scored each image thrice, with a minimum two-week washout period between scorings. Patient and injury information was provided at the third scoring. Raters also scored fracture union and whether the cast should be removed (yes/no responses). Intra-class correlation coefficients (ICC) and repeated measures correlation coefficients (rm) were calculated for within and between raters. PRWE was collected at each timepoint, as was a high-resolution peripheral quantitative computed tomography (HR-qQCT) image of the wrist (61 μm isotropic resolution). The latter was used to develop image-based micro-finite element models (μFE) to estimate apparent stiffness under uniaxial compression and torsional loading. Twenty participants (18 female, mean age = 50.5 ± 15.8 years) were enrolled. As shown in Figure 1, the inter-rater agreement was fair at the first and second round, with respective ICCs of 0.69 and 0.68. Inter-rater agreement was stronger at the third round, when patient information was provided (ICC=0.80). Finally, inter-rater agreement for the RCS was consistently stronger than the agreement for union or cast removal. Finally, RCS was strongly associated with μFE-estimated stiffness (rm = 0.74 to 0.84) and PRWE (rm = −0.83 to −0.75). Intra-rater reliability across the first two rounds and rounds one and three were stronger for RCS (mean ICC = 0.69 and 0.73, respectively) than fracture union (ICC = 0.57 and 0.56, respectively) or cast removal (ICC = 0.51 and 0.49, respectively). RCS had fair-to-good inter-rater reliability, across multiple rounds of scoring. Scores were strongly associated with μFE-estimated stiffness and PRWE, suggesting it is a good measure of mechanical and function changes indicative of healing. We observed weaker reliability of more subjective determination of fracture union and the decision to continue cast immobilization. Thus, we recommend the use of the RCS to aid clinical decision-making in non-operatively treated DRFs. For any figures or tables, please contact the authors directly.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.323
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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