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Record W4415571033 · doi:10.1302/1358-992x.2025.11.004

A RANDOMIZED CONTROLLED TRIAL COMPARING OPERATIVE AND NONOPERATIVE TREATMENT OF ULNAR DIAPHYSEAL FRACTURES

2025· article· en· W4415571033 on OpenAlexaff
Prism Schneider, Robert L. Leighton, R. Buckley, Robert Korley, Stephanie S. Yee, K. Rondeau, Paul Duffy

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsAlberta Bible College
Fundersnot available
KeywordsRandomized controlled trialElbowGrip strengthRandomizationVisual analogue scaleInternal fixationForearmHand strength

Abstract

fetched live from OpenAlex

Isolated ulnar diaphyseal fractures are relatively uncommon, with an incidence of 0.02 to 0.04 per 1,000. Despite being uncommon, complications surrounding this injury are frequent, including high non-union rates, decreased forearm pronation and supination, decreased elbow range of motion, radioulnar synostosis, and prolonged pain. Research investigating the best treatment option for this injury is scarce, and there is no consensus on optimal treatment methods. Therefore, this large randomized controlled trial (RCT) aims to compare clinical, radiographic, and functional outcomes between open reduction and internal fixation (ORIF) and non-operative treatment in patients with isolated ulnar diaphyseal fractures. This is a multi-centre, open-label, parallel RCT of patients with isolated, closed AO/OTA type 22-A and 22-B injuries, without extension into the proximal or distal radio-ulnar joints. Patients were excluded if the fracture was displaced 30-degrees of angulation. Eligible patients were randomized to one of the two treatment arms: non-operative treatment with closed reduction and below-elbow casting, or surgical treatment with ORIF with a limited contact dynamic compression plate and screw construct. Randomization was conducted electronically with a 1:1 ratio using variable block sizes and stratification by recruiting site. The primary outcome measure is the Disability Shoulder, Arm, Hand (DASH) score at 12 weeks post-injury. In addition, the Short Form 36 (SF-36) and Pain Visual Analogue Scale (VAS) are used to compare functional outcomes between groups. The secondary outcome measures include clinical (range of motion, grip strength), radiologic (time to union), and economic outcomes, assessed throughout patient follow-up until 12 months post-injury. Descriptive statistics will be used to characterize the study population. Intention-to-treat analysis will be performed with independent samples t-tests to compare the mean DASH, SF-36, and VAS questionnaire scores and for time to return to work. For secondary analysis, analysis of variance (ANOVA) and pairwise comparisons will be completed for the DASH, SF-36, and ROM data at each follow-up time interval. Independent samples t-test will be used for time to union data. Exploratory subgroup analyses are planned to examine treatment effects for covariates including age, sex, site, handedness, and injury classification. A total of 100 participants were enrolled and randomized (49 ORIF and 51 non-operative) across 11 participating sites (Table 1). The mean age of the overall cohort is 40.0 (± 18.0) years, with 72% being male. The final follow-up for this large, multi-centre RCT will be completed in March 2023; therefore, the study final results will be available for the 2023 COA meeting. This will be the largest RCT of operative compared with non-operative management of isolated ulnar diaphyseal fractures. This is a multi-centre study with a large loss to follow-up rate included in the sample size calculation, in order to ensure appropriate statistical power, given historical difficulty in following this patient population. Patients were enrolled at 11 participating sites to maximize generalizability of the study findings. 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.013
GPT teacher head0.315
Teacher spread0.302 · 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 designRandomized trial
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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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