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Record W4386250305 · doi:10.1007/s00590-023-03697-6

Do working length and proximal screw density influence the velocity of callus formation in distal tibia fractures treated with a medial bridge plate?

2023· article· en· W4386250305 on OpenAlexaff
A Gilli, Stefano Ghirardelli, Pierrenzo Pozzi, Georgios Touloupakis, Matteo Messori, Emmanouil Theodorakis, Guido Antonini

Bibliographic record

VenueEuropean Journal of Orthopaedic Surgery & Traumatology · 2023
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsWomen's College HospitalUniversity of Toronto
FundersUniversità degli Studi di Milano
KeywordsMedicineCallusTibiaBridge (graph theory)RadiographySurgeryOrthodonticsAnatomyHorticultureBiology

Abstract

fetched live from OpenAlex

INTRODUCTION: Aim of our study was to evaluate the influence of working length and screw density on callus formation in distal tibial fractures fixed with a medial bridge plate. MATERIALS AND METHODS: 42 distal tibia fractures treated with a bridge plate were analyzed. Minimum follow-up was 12 months. mRUST score (modified Radiographic Union Scale for Tibial fractures) was used to assess callus formation. Working length and screw density were measured from post-operative radiographs. RESULTS: 39 (92.9%) fractures healed uneventfully. 32 (76.19%) patients showed signs of early callus formation 3 months post-surgery. In these patients a lower screw density was used compared to patients who didn't show early callus (33.4 vs. 26.6; p = 0.04). No differences was noticed in working length. CONCLUSION: Bridge plate osteosynthesis is a good treatment option in distal tibia fractures. In our series increasing the working length was not associated with a faster callus formation in distal tibia fractures. Conversely, a lower screw density proximally to the fracture site was associated to a faster callus growth.

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 score0.038
Threshold uncertainty score0.439

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 head0.029
GPT teacher head0.260
Teacher spread0.231 · 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
Published2023
Admission routes1
Has abstractyes

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Same venueEuropean Journal of Orthopaedic Surgery & TraumatologySame topicBone fractures and treatmentsFrench-language works237,207