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Record W4415439280 · doi:10.1302/1358-992x.2025.10.089

HUMERAL DIAPHYSEAL NONUNION OCCURS MORE COMMONLY WITH ELEVATED BODY MASS INDEX AND SIMPLE FRACTURE TYPES

2025· article· en· W4415439280 on OpenAlexaff
Prism Schneider, M. Amedeo, S. Yee, K. Rondeau, Rudolf Reindl, Gregory K. Berry

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNonunionInternal fixationRadiographyBody mass indexRandomized controlled trialComplicationHumerusBone healingRetrospective cohort study

Abstract

fetched live from OpenAlex

Fractures of the humeral diaphysis occur in a bimodal distribution and represent 3–5% of all fractures. Nonunion remains a common complication following humeral diaphyseal fractures, with reports of 4% nonunion rates for surgically treated fractures and up to 33% for non-operative treatment. Prior risk factors from small studies or retrospective reviews have suggested advanced age, current smoking status, obesity, and unstable fracture pattern as possible risk factors for nonunion. This study aimed to systematically evaluate risk factors for humeral diaphyseal nonunion. This is a prespecified secondary analysis from a large randomized controlled trial (RCT) comparing open reduction and internal fixation (ORIF) with non-operative treatment (functional bracing) of humeral diaphyseal fractures. Inclusion criteria were patients 18 years or older with a displaced humeral diaphyseal fracture (AO/OTA 12-A, B, C) amenable to both treatments and presentation within 21 days from injury. Patients were excluded if there was an open fracture, multiple injuries, or nerve injury requiring repair. Eligible patients were followed clinically and radiographically for 1-year post-injury. Non-union was defined as lack of radiographic progression of fracture healing on orthogonal radiographs combined with failure to improve clinically. T-tests and chi-square were used to compare those with and without nonunion, and logistic regression was used to evaluate potential risk factors for nonunion. A total of 168 adult patients were enrolled (n=84 per treatment group), with an 85% 1-year follow-up rate. There were no significant differences between treatment groups for age, sex, smoking status, body mass index (BMI), or fracture classification (Table 1). Time to union was achieved earlier in the ORIF group (p=0.02). There were 13 patients diagnosed with nonunion, with 12 (92.3%) being in the non-operative treatment group. There was no difference between age for those who went on to nonunion (46.7 ± 16.2 years) and those who healed without complication (43.3 ± 17.0 years; p = 0.62). Sex distribution between those with (53.8% female) and without nonunion (37.4%) was similar (p = 0.48). All nonunions occurred in simple AO/OTA A-type fractures (A1 = 38.5%, A2 = 23.1%, and A3 = 38.5%). Regression analysis identified elevated BMI (OR = 1.12; 95% CI = 1.02 to 1.25; p = 0.027) as a risk factor for nonunion. There were 32 current smokers, with three patients experiencing nonunions (9.4%; p = 0.16). Surgical intervention for nonunion management in those initially treated non-operatively occurred at an average of 18.3 (± 10.5) weeks after their initial fracture. Our large, multi-centre RCT reported improved function with ORIF for 4–6 months and inferior outcomes have been reported for non-operatively treated humeral fractures requiring subsequent surgical treatment; therefore, early identification of risk factors for nonunion is important in guiding decision making. This large RCT confirms that elevated BMI is a risk factor for nonunion, that all nonunions in this cohort occurred in simple transverse, short oblique, or spiral fracture patterns, and that non-operative treatment carries a minimum of 15% risk for nonunion. 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)0.000
metaresearch head score (Gemma)0.000
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 score0.031
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.005
GPT teacher head0.256
Teacher spread0.251 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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