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Record W2320298945 · doi:10.1097/bot.0000000000000311

Dynamizations and Exchanges

2015· article· en· W2320298945 on OpenAlexaff
Jody Litrenta, Paul Tornetta, Heather A. Vallier, Reza Firoozabadi, Ross Leighton, Kenneth A. Egol, Christiane Kruppa, Clifford B. Jones, Cory A. Collinge, Mohit Bhandari, Emil H. Schemitsch, David Sanders, Brian Mullis

Bibliographic record

VenueJournal of Orthopaedic Trauma · 2015
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsSt. Michael's HospitalLondon Health Sciences CentreUniversity of TorontoMcMaster UniversityDalhousie University
Fundersnot available
KeywordsMedicineNonunionRadiographyTibiaIntervention (counseling)Psychological interventionRetrospective cohort studySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To characterize the timing, indications, and "success rates of secondary interventions, dynamization and exchange nailing, in a large series of tibial nonunions" (dynamization and exchange nailing are types of secondary interventions). SETTING: Retrospective multicenter analysis from level 1 trauma hospitals. PATIENTS: A total of 194 tibia fractures that underwent dynamization or exchange nailing for delayed/nonunion. INTERVENTION: Records and radiographs to characterize demographic data, fracture type, and cortical contact after tibial nailing were gathered. The radiographic union score for tibias (RUST) and the timing of intervention and time to union were calculated. MAIN OUTCOME MEASURES: The primary outcome was success of either intervention, defined as achieving union, with the need for further intervention defining failure. Other outcomes included RUST scores at intervention and union, and timing to intervention and union for both techniques. Two-tailed t tests and Fisher exact with P set at <0.05 for significance were used as indicated. RESULTS: A total of 194 tibia fractures underwent dynamization (97) or exchange nailing (97). No statistical differences were found between groups with demographic characteristics. The presence of a fracture gap (P = 0.01) and comminuted fractures (P = 0.002) was more common in the exchange group. The success rates of the interventions and RUST scores were not different when performed before versus after 6 months; therefore, data were pooled. The RUST scores at the time of intervention were not different for successful or failed dynamizations (7.13 vs. 7.07, P = 0.83) or exchanges (6.8 vs. 7.3, P = 0.37). Likewise, the time to successful versus failed dynamization (165 vs. 158 days, P = 0.91) or exchange nailing (224 vs. 201 days, P = 0.48) was not different. No cortical contact or a gap was a statistically negative factor for both exchange nails (P = 0.09) and dynamizations (P = 0.06). When combined, the success in the face of a gap was 78% versus 92% when no gap was present (P = 0.02). CONCLUSIONS: Previous literature has few reports of the success rates of secondary interventions for tibial nonunions. The indications for dynamization and exchange were similar. Comminuted fractures, and fractures with no cortical contact or "gap" present after intramedullary nailing, favored having an exchange nail performed over dynamization. Fracture gap was also found to be a negative prognostic factor for both procedures. Overall, this study demonstrates high rates of union for both interventions, making them both viable options. LEVEL OF EVIDENCE: Therapeutic 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.003

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 head0.036
GPT teacher head0.296
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), 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

Citations49
Published2015
Admission routes1
Has abstractyes

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