Potential predictive ability of the orthopaedic trauma association open fracture classification

Julie Agel, Todd Rockwood, Richard Barber, J. Lawrence Marsh

Research output: Contribution to journalReview articlepeer-review

19 Scopus citations

Abstract

OBJECTIVE: Is the OTA open fracture classification (OTA-OFC) potentially predictive of early amputation and specific clinical treatments? DESIGN: Retrospective chart review of prospectively collected data. SETTING: Level I trauma center, Seattle, WA. PATIENTS/PARTICIPANTS: Three hundred fifty-six patients with open fractures of the femur, tibia, malleoli, humerus, radius/ulna, pelvis, acetabulum, foot, or clavicle. INTERVENTION: No intervention. MAIN OUTCOME MEASUREMENTS: Vacuum-assisted closure placement, 3+ irrigation and debridements, antibiotic bead placement, and early amputation. RESULTS: The OTA-OFC is related to the type of treatment used to treat an open fracture. The model demonstrated that the strongest potential predictor of vacuum-assisted closure use is the severity of the skin injury; multiple debridements (≥ 2) is best predicted by the severity of the skin injury and muscle injury; bone loss was the strongest potential predictor of antibiotic bead placement; and the strongest predictors of early amputation are skin injury, contamination, and arterial injury. CONCLUSIONS: Exploratory analysis of these data demonstrates that variations in muscle damage, skin injury, bone loss, arterial injury, and contamination sustained in an open fracture are related to different treatments in the total study population and for anatomical regions. The information provided by this study demonstrates that the OTA-OFC may have predictive abilities relative to how an open fracture is treated. LEVEL OF EVIDENCE: Prognostic level II. See Instructions for Authors for a complete description of levels of evidence.

Original languageEnglish (US)
Pages (from-to)300-306
Number of pages7
JournalJournal of orthopaedic trauma
Volume28
Issue number5
DOIs
StatePublished - May 2014

Keywords

  • Open fracture classification
  • Prediction of outcome
  • Prediction of treatment

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