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Record W2493895368 · doi:10.1302/0301-620x.98b8.35687

Results of non-operative treatment of fractures of the glenoid fossa

2016· article· en· W2493895368 on OpenAlexaboutno aff
Matthias Königshausen, M Coulibaly, V. Nicolas, Thomas A. Schildhauer, D. Seybold

Bibliographic record

VenueThe Bone & Joint Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicShoulder and Clavicle Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMalunionDisplacement (psychology)NonunionSurgeryFossaOrthodontics

Abstract

fetched live from OpenAlex

AIMS: Our aim was to investigate the outcomes of patients with a displaced fracture of the glenoid fossa who are treated conservatively. There is little information in the literature about the treatment of these rare injuries non-operatively. PATIENTS AND METHODS: We reviewed 24 patients with a mean age of 52 years (19 to 81) at a mean of 5.6 years (11 months to 18 years) after the injury. RESULTS: At final follow-up, the mean Constant and Murley score was 79 points (18 to 98); the mean Western Ontario Shoulder Instability Index score (WOSI) was 77% (12 to 100) and the mean Rowe score was 93 points (50 to 100). Fractures with little intra-articular displacement (≤ 3 mm) had an uneventful outcome. Those with intra-articular displacement of ≤ 3 mm had a significant better mean Constant and Murley score than those with displacement of ≥ 5 mm and/or a fracture gap of ≥ 5 mm. Poor clinical results such as nonunion and post-traumatic osteoarthritis were associated with displaced or angulated glenoid fragments and significant intra-articular displacement. CONCLUSION: Glenoid fossa fractures with displacement of ≥ 5 mm should be treated surgically if the patient's condition allows. Displacement and angulation can lead to nonunion and a poor outcome if the degree of displacement results in a persistent fracture gap in the glenoid fossa or if the angulation of fragments leads to malunion. Cite this article: Bone Joint J 2016;98-B:1074-9.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.152

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.022
GPT teacher head0.373
Teacher spread0.351 · 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 designBench or experimental
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

Citations36
Published2016
Admission routes1
Has abstractyes

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