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Record W4411413422 · doi:10.2106/jbjs.24.01182

Performance of the OTA-OFC3 Classification System for Open Fractures

2025· article· en· W4411413422 on OpenAlexaff
Vivian Li, Alice C. Bell, David Okhuereigbe, Sara Kheiri, Christina A. Stennett, Robert V. O’Toole, Nathan N. O’Hara, Christopher M. Domes, Samir Mehta, Sheila Sprague, Meir Marmor, Gerard P. Slobogean

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsMedicineConfidence intervalReceiver operating characteristicSurgeryRetrospective cohort studyCohortArea under the curveCohort studyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The purpose of this study was to compare the simplified modification of the Orthopaedic Trauma Association-Open Fracture Classification (OTA-OFC3) with the original OTA-OFC and Gustilo-Anderson classification systems in predicting surgical site infection and unplanned reoperation. METHODS: This was a retrospective cohort study conducted using the PREP-IT (A Program of Randomized Trials to Evaluate Preoperative Antiseptic Skin Solutions in Orthopaedic Trauma) trial data of patients with open fractures. The OTA-OFC and Gustilo-Anderson classifications for each included fracture were determined by the treating surgeon at the initial irrigation and debridement. The OTA-OFC3 classification was determined on the basis of the highest severity level in any OTA-OFC domain. The study outcomes included surgical site infection and unplanned reoperations within 1 year of injury. Prognostic performance was measured by the area under the receiver operating characteristic curve (AUC), and AUCs were compared between classifications with z-tests. RESULTS: This cohort study included 3,338 patients with 3,627 open fractures. Surgical site infections occurred for 11% of the open fractures, and unplanned reoperations occurred for 15%. The prognostic performance of the new OTA-OFC3 score (AUC, 0.61; 95% confidence interval [CI], 0.58 to 0.64) did not differ significantly from that of the Gustilo-Anderson classification (AUC, 0.63; p = 0.40) or the 5 OTA-OFC domains (AUC, 0.64; p = 0.32) in predicting surgical site infection. The prognostic performance of the OTA-OFC3 system (AUC, 0.62; 95% CI, 0.59 to 0.64) was similar to that of the Gustilo-Anderson classification (AUC, 0.63; p = 0.34) but was significantly worse than that of the 5 OTA-OFC domains (AUC, 0.69; p < 0.001) in predicting unplanned reoperations. CONCLUSIONS: Simplifying the OTA-OFC to the new OTA-OFC3 significantly decreased its ability to predict unplanned reoperations and did not improve the ability to predict surgical site infection. These findings indicate that this newly proposed classification system, although clinically simpler, omits important prognostic information captured in the original OTA-OFC. Despite this limitation, the OTA-OFC3 demonstrated prognostic performance similar to that of the commonly used Gustilo-Anderson classification, and it may provide a clinically convenient way to communicate critical OTA-OFC information when all OTA-OFC domains are being assessed for research or quality-improvement purposes. LEVEL OF EVIDENCE: Prognostic Level III. 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 score0.201
Threshold uncertainty score0.144

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.039
GPT teacher head0.301
Teacher spread0.263 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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