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Intramedullary Nailing Following External Fixation in Femoral and Tibial Shaft Fractures

2005· article· en· W2010475152 on OpenAlexaff
Mohit Bhandari, Michael Zlowodzki, Paul Tornetta, Andrew H. Schmidt, David C. Templeman

Bibliographic record

VenueJournal of Orthopaedic Trauma · 2005
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsMcMaster UniversityHamilton General HospitalHamilton Health Sciences
Fundersnot available
KeywordsIntramedullary rodMedicineExternal fixationNonunionSurgeryFixation (population genetics)External fixator

Abstract

fetched live from OpenAlex

BACKGROUND: Intramedullary nailing is the standard of care for the definitive management of lower extremity long bone fractures. Occasionally, temporary external fixation is used in fractures with severe open wounds or vascular injury before definitive intramedullary nailing. Secondary intramedullary nailing following external fixation is somewhat controversial, especially with respect to the duration of external fixation that is allowable before the risk of infection following later nailing becomes too great. Several recent studies have provided further insight into this issue. OBJECTIVE: The primary objective is to evaluate infection and nonunion rates in patients treated with temporary external fixation and secondary intramedullary nailing for lower extremity long bone fractures. The secondary objective is to evaluate whether the duration of external fixation and the interval time (defined as the time from external fixator removal to intramedullary nailing) influence the risk of infection after intramedullary nailing.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.299
Teacher spread0.286 · 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

Citations194
Published2005
Admission routes1
Has abstractyes

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