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Record W4416827250 · doi:10.2106/jbjs.24.01055

Infection and Nonunion Rates in Open Fractures

2025· article· en· W4416827250 on OpenAlexafffund
Roman M. Natoli, Lucas S. Marchand, Sofia Bzovsky, Jennifer E. Hagen, Mark J. Gage, Christina A. Stennett, Nathan N. O’Hara, Kyle J. Jeray, Brad Petrisor, Sheila Sprague, Gerard P. Slobogean

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsImpactMcMaster University
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesUniversity of California, Los AngelesNational Institutes of HealthSchool of Medicine, Stanford UniversityCanadian Institutes of Health ResearchUniversity of WashingtonGreenville Health SystemMcMaster UniversityOttawa Hospital Research InstituteStrykerU.S. ArmyU.S. Army Institute of Surgical ResearchU.S. Department of DefenseUniversity of MissouriUniversity of Southern California
KeywordsNonunionIncidence (geometry)MEDLINEMediastinitisDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Infection and nonunion are common sequelae of open fractures. Studies have shown infection and nonunion rates ranging from 2% to 52% and 12% to 17%, respectively. The present article describes the rates of surgical site infection (SSI) and delayed union/nonunion following open fractures in a large contemporary series of patients from prospective clinical trials with adjudicated outcomes. METHODS: A descriptive analysis was performed with use of patient data from the FLOW, Aqueous-PREP, and PREPARE-Open studies. These studies, published within the past 10 years, included multiple international trauma centers and shared definitions for SSI and delayed union/nonunion. SSI and delayed union/nonunion rates were stratified by the OTA/AO fracture and Gustilo-Anderson open fracture classification systems. Kaplan-Meier estimators were utilized to obtain point estimates, and the log-log transformation approach was utilized to calculate 95% confidence intervals (CIs) for outcome rates. RESULTS: A total of 6,042 open fractures were included. The cumulative SSI rates at 12 months for Gustilo-Anderson Types 1, 2, 3A, 3B, and 3C were 5.1%, 9.7%, 13.8%, 28.9%, and 26.2%, respectively. The cumulative rates of delayed union/nonunion at 12 months for Gustilo-Anderson Types 1, 2, 3A, 3B, and 3C were 3.0%, 5.2%, 8.0%, 14.0%, and 17.0%, respectively. Utilizing the OTA/AO fracture classification to increase the point estimate granularity, the estimated 12-month SSI and delayed union/nonunion rates in 156 Gustilo-Anderson type 3B open tibial shaft fractures (OTA/AO 42) were 34.7% (95% CI, 26.7% to 41.9%) and 18.4% (95% CI, 12.0% to 24.4%), respectively. A companion website with SSI and delayed union/nonunion rates was developed to supplement this article. CONCLUSIONS: Open fractures are a substantial problem with complications that include infection and nonunion. The present data are useful for prognosis, research study design, and informing public awareness and policy. These results show that, despite current treatment approaches, the rates of SSI and delayed union/nonunion following treatment of open fractures remain high at 1 year and are not substantially improved from historical rates spanning several decades. Although open fracture sequelae remain a burden for patients, orthopaedic surgeons, and health-care systems, there may be opportunities for improvement in outcomes. LEVEL OF EVIDENCE: Prognostic Level I. See Instructions for Authors for a complete description of levels of evidence.

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)0.000
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 score0.037
Threshold uncertainty score0.188

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.323
Teacher spread0.300 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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